1 /*
2 * Copyright (c) 2017, 2021, Oracle and/or its affiliates. All rights reserved.
3 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
4 *
5 * This code is free software; you can redistribute it and/or modify it
6 * under the terms of the GNU General Public License version 2 only, as
7 * published by the Free Software Foundation. Oracle designates this
8 * particular file as subject to the "Classpath" exception as provided
9 * by Oracle in the LICENSE file that accompanied this code.
10 *
11 * This code is distributed in the hope that it will be useful, but WITHOUT
12 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
14 * version 2 for more details (a copy is included in the LICENSE file that
15 * accompanied this code).
16 *
17 * You should have received a copy of the GNU General Public License version
18 * 2 along with this work; if not, write to the Free Software Foundation,
19 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
20 *
21 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
22 * or visit www.oracle.com if you need additional information or have any
23 * questions.
24 */
25 package jdk.incubator.vector;
26
27 import java.nio.ByteBuffer;
28 import java.nio.ByteOrder;
29 import java.nio.ReadOnlyBufferException;
30 import java.util.Arrays;
31 import java.util.Objects;
32 import java.util.function.Function;
33 import java.util.function.UnaryOperator;
34
35 import jdk.internal.misc.ScopedMemoryAccess;
36 import jdk.internal.misc.Unsafe;
37 import jdk.internal.vm.annotation.ForceInline;
38 import jdk.internal.vm.vector.VectorSupport;
39
40 import static jdk.internal.vm.vector.VectorSupport.*;
41 import static jdk.incubator.vector.VectorIntrinsics.*;
42
43 import static jdk.incubator.vector.VectorOperators.*;
44
45 #warn This file is preprocessed before being compiled
46
47 /**
48 * A specialized {@link Vector} representing an ordered immutable sequence of
49 * {@code $type$} values.
50 */
51 @SuppressWarnings("cast") // warning: redundant cast
52 public abstract class $abstractvectortype$ extends AbstractVector<$Boxtype$> {
53
54 $abstractvectortype$($type$[] vec) {
55 super(vec);
56 }
57
58 #if[FP]
59 static final int FORBID_OPCODE_KIND = VO_NOFP;
60 #else[FP]
61 static final int FORBID_OPCODE_KIND = VO_ONLYFP;
62 #end[FP]
63
64 @ForceInline
65 static int opCode(Operator op) {
66 return VectorOperators.opCode(op, VO_OPCODE_VALID, FORBID_OPCODE_KIND);
67 }
68 @ForceInline
69 static int opCode(Operator op, int requireKind) {
70 requireKind |= VO_OPCODE_VALID;
71 return VectorOperators.opCode(op, requireKind, FORBID_OPCODE_KIND);
72 }
73 @ForceInline
74 static boolean opKind(Operator op, int bit) {
75 return VectorOperators.opKind(op, bit);
76 }
77
78 // Virtualized factories and operators,
79 // coded with portable definitions.
80 // These are all @ForceInline in case
81 // they need to be used performantly.
82 // The various shape-specific subclasses
83 // also specialize them by wrapping
84 // them in a call like this:
85 // return (Byte128Vector)
86 // super.bOp((Byte128Vector) o);
87 // The purpose of that is to forcibly inline
88 // the generic definition from this file
89 // into a sharply type- and size-specific
90 // wrapper in the subclass file, so that
91 // the JIT can specialize the code.
92 // The code is only inlined and expanded
93 // if it gets hot. Think of it as a cheap
94 // and lazy version of C++ templates.
95
96 // Virtualized getter
97
98 /*package-private*/
99 abstract $type$[] vec();
100
101 // Virtualized constructors
102
103 /**
104 * Build a vector directly using my own constructor.
105 * It is an error if the array is aliased elsewhere.
106 */
107 /*package-private*/
108 abstract $abstractvectortype$ vectorFactory($type$[] vec);
109
110 /**
111 * Build a mask directly using my species.
112 * It is an error if the array is aliased elsewhere.
113 */
114 /*package-private*/
115 @ForceInline
116 final
117 AbstractMask<$Boxtype$> maskFactory(boolean[] bits) {
118 return vspecies().maskFactory(bits);
119 }
120
121 // Constant loader (takes dummy as vector arg)
122 interface FVOp {
123 $type$ apply(int i);
124 }
125
126 /*package-private*/
127 @ForceInline
128 final
129 $abstractvectortype$ vOp(FVOp f) {
130 $type$[] res = new $type$[length()];
131 for (int i = 0; i < res.length; i++) {
132 res[i] = f.apply(i);
133 }
134 return vectorFactory(res);
135 }
136
137 @ForceInline
138 final
139 $abstractvectortype$ vOp(VectorMask<$Boxtype$> m, FVOp f) {
140 $type$[] res = new $type$[length()];
141 boolean[] mbits = ((AbstractMask<$Boxtype$>)m).getBits();
142 for (int i = 0; i < res.length; i++) {
143 if (mbits[i]) {
144 res[i] = f.apply(i);
145 }
146 }
147 return vectorFactory(res);
148 }
149
150 // Unary operator
151
152 /*package-private*/
153 interface FUnOp {
154 $type$ apply(int i, $type$ a);
155 }
156
157 /*package-private*/
158 abstract
159 $abstractvectortype$ uOp(FUnOp f);
160 @ForceInline
161 final
162 $abstractvectortype$ uOpTemplate(FUnOp f) {
163 $type$[] vec = vec();
164 $type$[] res = new $type$[length()];
165 for (int i = 0; i < res.length; i++) {
166 res[i] = f.apply(i, vec[i]);
167 }
168 return vectorFactory(res);
169 }
170
171 /*package-private*/
172 abstract
173 $abstractvectortype$ uOp(VectorMask<$Boxtype$> m,
174 FUnOp f);
175 @ForceInline
176 final
177 $abstractvectortype$ uOpTemplate(VectorMask<$Boxtype$> m,
178 FUnOp f) {
179 if (m == null) {
180 return uOpTemplate(f);
181 }
182 $type$[] vec = vec();
183 $type$[] res = new $type$[length()];
184 boolean[] mbits = ((AbstractMask<$Boxtype$>)m).getBits();
185 for (int i = 0; i < res.length; i++) {
186 res[i] = mbits[i] ? f.apply(i, vec[i]) : vec[i];
187 }
188 return vectorFactory(res);
189 }
190
191 // Binary operator
192
193 /*package-private*/
194 interface FBinOp {
195 $type$ apply(int i, $type$ a, $type$ b);
196 }
197
198 /*package-private*/
199 abstract
200 $abstractvectortype$ bOp(Vector<$Boxtype$> o,
201 FBinOp f);
202 @ForceInline
203 final
204 $abstractvectortype$ bOpTemplate(Vector<$Boxtype$> o,
205 FBinOp f) {
206 $type$[] res = new $type$[length()];
207 $type$[] vec1 = this.vec();
208 $type$[] vec2 = (($abstractvectortype$)o).vec();
209 for (int i = 0; i < res.length; i++) {
210 res[i] = f.apply(i, vec1[i], vec2[i]);
211 }
212 return vectorFactory(res);
213 }
214
215 /*package-private*/
216 abstract
217 $abstractvectortype$ bOp(Vector<$Boxtype$> o,
218 VectorMask<$Boxtype$> m,
219 FBinOp f);
220 @ForceInline
221 final
222 $abstractvectortype$ bOpTemplate(Vector<$Boxtype$> o,
223 VectorMask<$Boxtype$> m,
224 FBinOp f) {
225 if (m == null) {
226 return bOpTemplate(o, f);
227 }
228 $type$[] res = new $type$[length()];
229 $type$[] vec1 = this.vec();
230 $type$[] vec2 = (($abstractvectortype$)o).vec();
231 boolean[] mbits = ((AbstractMask<$Boxtype$>)m).getBits();
232 for (int i = 0; i < res.length; i++) {
233 res[i] = mbits[i] ? f.apply(i, vec1[i], vec2[i]) : vec1[i];
234 }
235 return vectorFactory(res);
236 }
237
238 // Ternary operator
239
240 /*package-private*/
241 interface FTriOp {
242 $type$ apply(int i, $type$ a, $type$ b, $type$ c);
243 }
244
245 /*package-private*/
246 abstract
247 $abstractvectortype$ tOp(Vector<$Boxtype$> o1,
248 Vector<$Boxtype$> o2,
249 FTriOp f);
250 @ForceInline
251 final
252 $abstractvectortype$ tOpTemplate(Vector<$Boxtype$> o1,
253 Vector<$Boxtype$> o2,
254 FTriOp f) {
255 $type$[] res = new $type$[length()];
256 $type$[] vec1 = this.vec();
257 $type$[] vec2 = (($abstractvectortype$)o1).vec();
258 $type$[] vec3 = (($abstractvectortype$)o2).vec();
259 for (int i = 0; i < res.length; i++) {
260 res[i] = f.apply(i, vec1[i], vec2[i], vec3[i]);
261 }
262 return vectorFactory(res);
263 }
264
265 /*package-private*/
266 abstract
267 $abstractvectortype$ tOp(Vector<$Boxtype$> o1,
268 Vector<$Boxtype$> o2,
269 VectorMask<$Boxtype$> m,
270 FTriOp f);
271 @ForceInline
272 final
273 $abstractvectortype$ tOpTemplate(Vector<$Boxtype$> o1,
274 Vector<$Boxtype$> o2,
275 VectorMask<$Boxtype$> m,
276 FTriOp f) {
277 if (m == null) {
278 return tOpTemplate(o1, o2, f);
279 }
280 $type$[] res = new $type$[length()];
281 $type$[] vec1 = this.vec();
282 $type$[] vec2 = (($abstractvectortype$)o1).vec();
283 $type$[] vec3 = (($abstractvectortype$)o2).vec();
284 boolean[] mbits = ((AbstractMask<$Boxtype$>)m).getBits();
285 for (int i = 0; i < res.length; i++) {
286 res[i] = mbits[i] ? f.apply(i, vec1[i], vec2[i], vec3[i]) : vec1[i];
287 }
288 return vectorFactory(res);
289 }
290
291 // Reduction operator
292
293 /*package-private*/
294 abstract
295 $type$ rOp($type$ v, VectorMask<$Boxtype$> m, FBinOp f);
296
297 @ForceInline
298 final
299 $type$ rOpTemplate($type$ v, VectorMask<$Boxtype$> m, FBinOp f) {
300 if (m == null) {
301 return rOpTemplate(v, f);
302 }
303 $type$[] vec = vec();
304 boolean[] mbits = ((AbstractMask<$Boxtype$>)m).getBits();
305 for (int i = 0; i < vec.length; i++) {
306 v = mbits[i] ? f.apply(i, v, vec[i]) : v;
307 }
308 return v;
309 }
310
311 @ForceInline
312 final
313 $type$ rOpTemplate($type$ v, FBinOp f) {
314 $type$[] vec = vec();
315 for (int i = 0; i < vec.length; i++) {
316 v = f.apply(i, v, vec[i]);
317 }
318 return v;
319 }
320
321 // Memory reference
322
323 /*package-private*/
324 interface FLdOp<M> {
325 $type$ apply(M memory, int offset, int i);
326 }
327
328 /*package-private*/
329 @ForceInline
330 final
331 <M> $abstractvectortype$ ldOp(M memory, int offset,
332 FLdOp<M> f) {
333 //dummy; no vec = vec();
334 $type$[] res = new $type$[length()];
335 for (int i = 0; i < res.length; i++) {
336 res[i] = f.apply(memory, offset, i);
337 }
338 return vectorFactory(res);
339 }
340
341 /*package-private*/
342 @ForceInline
343 final
344 <M> $abstractvectortype$ ldOp(M memory, int offset,
345 VectorMask<$Boxtype$> m,
346 FLdOp<M> f) {
347 //$type$[] vec = vec();
348 $type$[] res = new $type$[length()];
349 boolean[] mbits = ((AbstractMask<$Boxtype$>)m).getBits();
350 for (int i = 0; i < res.length; i++) {
351 if (mbits[i]) {
352 res[i] = f.apply(memory, offset, i);
353 }
354 }
355 return vectorFactory(res);
356 }
357
358 interface FStOp<M> {
359 void apply(M memory, int offset, int i, $type$ a);
360 }
361
362 /*package-private*/
363 @ForceInline
364 final
365 <M> void stOp(M memory, int offset,
366 FStOp<M> f) {
367 $type$[] vec = vec();
368 for (int i = 0; i < vec.length; i++) {
369 f.apply(memory, offset, i, vec[i]);
370 }
371 }
372
373 /*package-private*/
374 @ForceInline
375 final
376 <M> void stOp(M memory, int offset,
377 VectorMask<$Boxtype$> m,
378 FStOp<M> f) {
379 $type$[] vec = vec();
380 boolean[] mbits = ((AbstractMask<$Boxtype$>)m).getBits();
381 for (int i = 0; i < vec.length; i++) {
382 if (mbits[i]) {
383 f.apply(memory, offset, i, vec[i]);
384 }
385 }
386 }
387
388 // Binary test
389
390 /*package-private*/
391 interface FBinTest {
392 boolean apply(int cond, int i, $type$ a, $type$ b);
393 }
394
395 /*package-private*/
396 @ForceInline
397 final
398 AbstractMask<$Boxtype$> bTest(int cond,
399 Vector<$Boxtype$> o,
400 FBinTest f) {
401 $type$[] vec1 = vec();
402 $type$[] vec2 = (($abstractvectortype$)o).vec();
403 boolean[] bits = new boolean[length()];
404 for (int i = 0; i < length(); i++){
405 bits[i] = f.apply(cond, i, vec1[i], vec2[i]);
406 }
407 return maskFactory(bits);
408 }
409
410 #if[BITWISE]
411 /*package-private*/
412 @ForceInline
413 static $type$ rotateLeft($type$ a, int n) {
414 #if[intOrLong]
415 return $Boxtype$.rotateLeft(a, n);
416 #else[intOrLong]
417 return ($type$)((((($type$)a) & $Boxtype$.toUnsignedInt(($type$)-1)) << (n & $Boxtype$.SIZE-1)) | (((($type$)a) & $Boxtype$.toUnsignedInt(($type$)-1)) >>> ($Boxtype$.SIZE - (n & $Boxtype$.SIZE-1))));
418 #end[intOrLong]
419 }
420
421 /*package-private*/
422 @ForceInline
423 static $type$ rotateRight($type$ a, int n) {
424 #if[intOrLong]
425 return $Boxtype$.rotateRight(a, n);
426 #else[intOrLong]
427 return ($type$)((((($type$)a) & $Boxtype$.toUnsignedInt(($type$)-1)) >>> (n & $Boxtype$.SIZE-1)) | (((($type$)a) & $Boxtype$.toUnsignedInt(($type$)-1)) << ($Boxtype$.SIZE - (n & $Boxtype$.SIZE-1))));
428 #end[intOrLong]
429 }
430 #end[BITWISE]
431
432 /*package-private*/
433 @Override
434 abstract $Type$Species vspecies();
435
436 /*package-private*/
437 @ForceInline
438 static long toBits($type$ e) {
439 return {#if[FP]? $Type$.$type$ToRaw$Bitstype$Bits(e): e};
440 }
441
442 /*package-private*/
443 @ForceInline
444 static $type$ fromBits(long bits) {
445 return {#if[FP]?$Type$.$bitstype$BitsTo$Type$}(($bitstype$)bits);
446 }
447
448 // Static factories (other than memory operations)
449
450 // Note: A surprising behavior in javadoc
451 // sometimes makes a lone /** {@inheritDoc} */
452 // comment drop the method altogether,
453 // apparently if the method mentions an
454 // parameter or return type of Vector<$Boxtype$>
455 // instead of Vector<E> as originally specified.
456 // Adding an empty HTML fragment appears to
457 // nudge javadoc into providing the desired
458 // inherited documentation. We use the HTML
459 // comment <!--workaround--> for this.
460
461 /**
462 * Returns a vector of the given species
463 * where all lane elements are set to
464 * zero, the default primitive value.
465 *
466 * @param species species of the desired zero vector
467 * @return a zero vector
468 */
469 @ForceInline
470 public static $abstractvectortype$ zero(VectorSpecies<$Boxtype$> species) {
471 $Type$Species vsp = ($Type$Species) species;
472 #if[FP]
473 return VectorSupport.broadcastCoerced(vsp.vectorType(), $type$.class, species.length(),
474 toBits(0.0f), vsp,
475 ((bits_, s_) -> s_.rvOp(i -> bits_)));
476 #else[FP]
477 return VectorSupport.broadcastCoerced(vsp.vectorType(), $type$.class, species.length(),
478 0, vsp,
479 ((bits_, s_) -> s_.rvOp(i -> bits_)));
480 #end[FP]
481 }
482
483 /**
484 * Returns a vector of the same species as this one
485 * where all lane elements are set to
486 * the primitive value {@code e}.
487 *
488 * The contents of the current vector are discarded;
489 * only the species is relevant to this operation.
490 *
491 * <p> This method returns the value of this expression:
492 * {@code $abstractvectortype$.broadcast(this.species(), e)}.
493 *
494 * @apiNote
495 * Unlike the similar method named {@code broadcast()}
496 * in the supertype {@code Vector}, this method does not
497 * need to validate its argument, and cannot throw
498 * {@code IllegalArgumentException}. This method is
499 * therefore preferable to the supertype method.
500 *
501 * @param e the value to broadcast
502 * @return a vector where all lane elements are set to
503 * the primitive value {@code e}
504 * @see #broadcast(VectorSpecies,long)
505 * @see Vector#broadcast(long)
506 * @see VectorSpecies#broadcast(long)
507 */
508 public abstract $abstractvectortype$ broadcast($type$ e);
509
510 /**
511 * Returns a vector of the given species
512 * where all lane elements are set to
513 * the primitive value {@code e}.
514 *
515 * @param species species of the desired vector
516 * @param e the value to broadcast
517 * @return a vector where all lane elements are set to
518 * the primitive value {@code e}
519 * @see #broadcast(long)
520 * @see Vector#broadcast(long)
521 * @see VectorSpecies#broadcast(long)
522 */
523 @ForceInline
524 public static $abstractvectortype$ broadcast(VectorSpecies<$Boxtype$> species, $type$ e) {
525 $Type$Species vsp = ($Type$Species) species;
526 return vsp.broadcast(e);
527 }
528
529 /*package-private*/
530 @ForceInline
531 final $abstractvectortype$ broadcastTemplate($type$ e) {
532 $Type$Species vsp = vspecies();
533 return vsp.broadcast(e);
534 }
535
536 #if[!long]
537 /**
538 * {@inheritDoc} <!--workaround-->
539 * @apiNote
540 * When working with vector subtypes like {@code $abstractvectortype$},
541 * {@linkplain #broadcast($type$) the more strongly typed method}
542 * is typically selected. It can be explicitly selected
543 * using a cast: {@code v.broadcast(($type$)e)}.
544 * The two expressions will produce numerically identical results.
545 */
546 @Override
547 public abstract $abstractvectortype$ broadcast(long e);
548
549 /**
550 * Returns a vector of the given species
551 * where all lane elements are set to
552 * the primitive value {@code e}.
553 *
554 * The {@code long} value must be accurately representable
555 * by the {@code ETYPE} of the vector species, so that
556 * {@code e==(long)(ETYPE)e}.
557 *
558 * @param species species of the desired vector
559 * @param e the value to broadcast
560 * @return a vector where all lane elements are set to
561 * the primitive value {@code e}
562 * @throws IllegalArgumentException
563 * if the given {@code long} value cannot
564 * be represented by the vector's {@code ETYPE}
565 * @see #broadcast(VectorSpecies,$type$)
566 * @see VectorSpecies#checkValue(long)
567 */
568 @ForceInline
569 public static $abstractvectortype$ broadcast(VectorSpecies<$Boxtype$> species, long e) {
570 $Type$Species vsp = ($Type$Species) species;
571 return vsp.broadcast(e);
572 }
573
574 /*package-private*/
575 @ForceInline
576 final $abstractvectortype$ broadcastTemplate(long e) {
577 return vspecies().broadcast(e);
578 }
579 #end[!long]
580
581 // Unary lanewise support
582
583 /**
584 * {@inheritDoc} <!--workaround-->
585 */
586 public abstract
587 $abstractvectortype$ lanewise(VectorOperators.Unary op);
588
589 @ForceInline
590 final
591 $abstractvectortype$ lanewiseTemplate(VectorOperators.Unary op) {
592 if (opKind(op, VO_SPECIAL)) {
593 if (op == ZOMO) {
594 return blend(broadcast(-1), compare(NE, 0));
595 }
596 #if[BITWISE]
597 if (op == NOT) {
598 return broadcast(-1).lanewise(XOR, this);
599 } else if (op == NEG) {
600 // FIXME: Support this in the JIT.
601 return broadcast(0).lanewise(SUB, this);
602 }
603 #end[BITWISE]
604 }
605 int opc = opCode(op);
606 return VectorSupport.unaryOp(
607 opc, getClass(), null, $type$.class, length(),
608 this, null,
609 UN_IMPL.find(op, opc, $abstractvectortype$::unaryOperations));
610 }
611
612 /**
613 * {@inheritDoc} <!--workaround-->
614 */
615 @Override
616 public abstract
617 $abstractvectortype$ lanewise(VectorOperators.Unary op,
618 VectorMask<$Boxtype$> m);
619 @ForceInline
620 final
621 $abstractvectortype$ lanewiseTemplate(VectorOperators.Unary op,
622 Class<? extends VectorMask<$Boxtype$>> maskClass,
623 VectorMask<$Boxtype$> m) {
624 m.check(maskClass, this);
625 if (opKind(op, VO_SPECIAL)) {
626 if (op == ZOMO) {
627 return blend(broadcast(-1), compare(NE, 0, m));
628 }
629 #if[BITWISE]
630 if (op == NOT) {
631 return lanewise(XOR, broadcast(-1), m);
632 } else if (op == NEG) {
633 return lanewise(NOT, m).lanewise(ADD, broadcast(1), m);
634 }
635 #end[BITWISE]
636 }
637 int opc = opCode(op);
638 return VectorSupport.unaryOp(
639 opc, getClass(), maskClass, $type$.class, length(),
640 this, m,
641 UN_IMPL.find(op, opc, $abstractvectortype$::unaryOperations));
642 }
643
644 private static final
645 ImplCache<Unary, UnaryOperation<$abstractvectortype$, VectorMask<$Boxtype$>>>
646 UN_IMPL = new ImplCache<>(Unary.class, $Type$Vector.class);
647
648 private static UnaryOperation<$abstractvectortype$, VectorMask<$Boxtype$>> unaryOperations(int opc_) {
649 switch (opc_) {
650 case VECTOR_OP_NEG: return (v0, m) ->
651 v0.uOp(m, (i, a) -> ($type$) -a);
652 case VECTOR_OP_ABS: return (v0, m) ->
653 v0.uOp(m, (i, a) -> ($type$) Math.abs(a));
654 #if[FP]
655 case VECTOR_OP_SIN: return (v0, m) ->
656 v0.uOp(m, (i, a) -> ($type$) Math.sin(a));
657 case VECTOR_OP_COS: return (v0, m) ->
658 v0.uOp(m, (i, a) -> ($type$) Math.cos(a));
659 case VECTOR_OP_TAN: return (v0, m) ->
660 v0.uOp(m, (i, a) -> ($type$) Math.tan(a));
661 case VECTOR_OP_ASIN: return (v0, m) ->
662 v0.uOp(m, (i, a) -> ($type$) Math.asin(a));
663 case VECTOR_OP_ACOS: return (v0, m) ->
664 v0.uOp(m, (i, a) -> ($type$) Math.acos(a));
665 case VECTOR_OP_ATAN: return (v0, m) ->
666 v0.uOp(m, (i, a) -> ($type$) Math.atan(a));
667 case VECTOR_OP_EXP: return (v0, m) ->
668 v0.uOp(m, (i, a) -> ($type$) Math.exp(a));
669 case VECTOR_OP_LOG: return (v0, m) ->
670 v0.uOp(m, (i, a) -> ($type$) Math.log(a));
671 case VECTOR_OP_LOG10: return (v0, m) ->
672 v0.uOp(m, (i, a) -> ($type$) Math.log10(a));
673 case VECTOR_OP_SQRT: return (v0, m) ->
674 v0.uOp(m, (i, a) -> ($type$) Math.sqrt(a));
675 case VECTOR_OP_CBRT: return (v0, m) ->
676 v0.uOp(m, (i, a) -> ($type$) Math.cbrt(a));
677 case VECTOR_OP_SINH: return (v0, m) ->
678 v0.uOp(m, (i, a) -> ($type$) Math.sinh(a));
679 case VECTOR_OP_COSH: return (v0, m) ->
680 v0.uOp(m, (i, a) -> ($type$) Math.cosh(a));
681 case VECTOR_OP_TANH: return (v0, m) ->
682 v0.uOp(m, (i, a) -> ($type$) Math.tanh(a));
683 case VECTOR_OP_EXPM1: return (v0, m) ->
684 v0.uOp(m, (i, a) -> ($type$) Math.expm1(a));
685 case VECTOR_OP_LOG1P: return (v0, m) ->
686 v0.uOp(m, (i, a) -> ($type$) Math.log1p(a));
687 #end[FP]
688 default: return null;
689 }
690 }
691
692 // Binary lanewise support
693
694 /**
695 * {@inheritDoc} <!--workaround-->
696 * @see #lanewise(VectorOperators.Binary,$type$)
697 * @see #lanewise(VectorOperators.Binary,$type$,VectorMask)
698 */
699 @Override
700 public abstract
701 $abstractvectortype$ lanewise(VectorOperators.Binary op,
702 Vector<$Boxtype$> v);
703 @ForceInline
704 final
705 $abstractvectortype$ lanewiseTemplate(VectorOperators.Binary op,
706 Vector<$Boxtype$> v) {
707 $abstractvectortype$ that = ($abstractvectortype$) v;
708 that.check(this);
709
710 if (opKind(op, VO_SPECIAL {#if[!FP]? | VO_SHIFT})) {
711 if (op == FIRST_NONZERO) {
712 // FIXME: Support this in the JIT.
713 VectorMask<$Boxbitstype$> thisNZ
714 = this.viewAsIntegralLanes().compare(NE, ($bitstype$) 0);
715 that = that.blend(($type$) 0, thisNZ.cast(vspecies()));
716 op = OR_UNCHECKED;
717 #if[FP]
718 // FIXME: Support OR_UNCHECKED on float/double also!
719 return this.viewAsIntegralLanes()
720 .lanewise(op, that.viewAsIntegralLanes())
721 .viewAsFloatingLanes();
722 #end[FP]
723 }
724 #if[BITWISE]
725 #if[!FP]
726 if (opKind(op, VO_SHIFT)) {
727 // As per shift specification for Java, mask the shift count.
728 // This allows the JIT to ignore some ISA details.
729 that = that.lanewise(AND, SHIFT_MASK);
730 }
731 #end[!FP]
732 if (op == AND_NOT) {
733 // FIXME: Support this in the JIT.
734 that = that.lanewise(NOT);
735 op = AND;
736 } else if (op == DIV) {
737 VectorMask<$Boxtype$> eqz = that.eq(($type$) 0);
738 if (eqz.anyTrue()) {
739 throw that.divZeroException();
740 }
741 }
742 #end[BITWISE]
743 }
744
745 int opc = opCode(op);
746 return VectorSupport.binaryOp(
747 opc, getClass(), null, $type$.class, length(),
748 this, that, null,
749 BIN_IMPL.find(op, opc, $abstractvectortype$::binaryOperations));
750 }
751
752 /**
753 * {@inheritDoc} <!--workaround-->
754 * @see #lanewise(VectorOperators.Binary,$type$,VectorMask)
755 */
756 @Override
757 public abstract
758 $abstractvectortype$ lanewise(VectorOperators.Binary op,
759 Vector<$Boxtype$> v,
760 VectorMask<$Boxtype$> m);
761 @ForceInline
762 final
763 $abstractvectortype$ lanewiseTemplate(VectorOperators.Binary op,
764 Class<? extends VectorMask<$Boxtype$>> maskClass,
765 Vector<$Boxtype$> v, VectorMask<$Boxtype$> m) {
766 $abstractvectortype$ that = ($abstractvectortype$) v;
767 that.check(this);
768 m.check(maskClass, this);
769
770 if (opKind(op, VO_SPECIAL {#if[!FP]? | VO_SHIFT})) {
771 if (op == FIRST_NONZERO) {
772 #if[FP]
773 return blend(lanewise(op, v), m);
774 #else[FP]
775 // FIXME: Support this in the JIT.
776 VectorMask<$Boxbitstype$> thisNZ
777 = this.viewAsIntegralLanes().compare(NE, ($bitstype$) 0);
778 that = that.blend(($type$) 0, thisNZ.cast(vspecies()));
779 op = OR_UNCHECKED;
780 #end[FP]
781 }
782 #if[BITWISE]
783 #if[!FP]
784 if (opKind(op, VO_SHIFT)) {
785 // As per shift specification for Java, mask the shift count.
786 // This allows the JIT to ignore some ISA details.
787 that = that.lanewise(AND, SHIFT_MASK);
788 }
789 #end[!FP]
790 if (op == AND_NOT) {
791 // FIXME: Support this in the JIT.
792 that = that.lanewise(NOT);
793 op = AND;
794 } else if (op == DIV) {
795 VectorMask<$Boxtype$> eqz = that.eq(($type$)0);
796 if (eqz.and(m).anyTrue()) {
797 throw that.divZeroException();
798 }
799 // suppress div/0 exceptions in unset lanes
800 that = that.lanewise(NOT, eqz);
801 }
802 #end[BITWISE]
803 }
804
805 int opc = opCode(op);
806 return VectorSupport.binaryOp(
807 opc, getClass(), maskClass, $type$.class, length(),
808 this, that, m,
809 BIN_IMPL.find(op, opc, $abstractvectortype$::binaryOperations));
810 }
811
812 private static final
813 ImplCache<Binary, BinaryOperation<$abstractvectortype$, VectorMask<$Boxtype$>>>
814 BIN_IMPL = new ImplCache<>(Binary.class, $Type$Vector.class);
815
816 private static BinaryOperation<$abstractvectortype$, VectorMask<$Boxtype$>> binaryOperations(int opc_) {
817 switch (opc_) {
818 case VECTOR_OP_ADD: return (v0, v1, vm) ->
819 v0.bOp(v1, vm, (i, a, b) -> ($type$)(a + b));
820 case VECTOR_OP_SUB: return (v0, v1, vm) ->
821 v0.bOp(v1, vm, (i, a, b) -> ($type$)(a - b));
822 case VECTOR_OP_MUL: return (v0, v1, vm) ->
823 v0.bOp(v1, vm, (i, a, b) -> ($type$)(a * b));
824 case VECTOR_OP_DIV: return (v0, v1, vm) ->
825 v0.bOp(v1, vm, (i, a, b) -> ($type$)(a / b));
826 case VECTOR_OP_MAX: return (v0, v1, vm) ->
827 v0.bOp(v1, vm, (i, a, b) -> ($type$)Math.max(a, b));
828 case VECTOR_OP_MIN: return (v0, v1, vm) ->
829 v0.bOp(v1, vm, (i, a, b) -> ($type$)Math.min(a, b));
830 #if[BITWISE]
831 case VECTOR_OP_AND: return (v0, v1, vm) ->
832 v0.bOp(v1, vm, (i, a, b) -> ($type$)(a & b));
833 case VECTOR_OP_OR: return (v0, v1, vm) ->
834 v0.bOp(v1, vm, (i, a, b) -> ($type$)(a | b));
835 case VECTOR_OP_XOR: return (v0, v1, vm) ->
836 v0.bOp(v1, vm, (i, a, b) -> ($type$)(a ^ b));
837 case VECTOR_OP_LSHIFT: return (v0, v1, vm) ->
838 v0.bOp(v1, vm, (i, a, n) -> ($type$)(a << n));
839 case VECTOR_OP_RSHIFT: return (v0, v1, vm) ->
840 v0.bOp(v1, vm, (i, a, n) -> ($type$)(a >> n));
841 case VECTOR_OP_URSHIFT: return (v0, v1, vm) ->
842 v0.bOp(v1, vm, (i, a, n) -> ($type$)((a & LSHR_SETUP_MASK) >>> n));
843 case VECTOR_OP_LROTATE: return (v0, v1, vm) ->
844 v0.bOp(v1, vm, (i, a, n) -> rotateLeft(a, (int)n));
845 case VECTOR_OP_RROTATE: return (v0, v1, vm) ->
846 v0.bOp(v1, vm, (i, a, n) -> rotateRight(a, (int)n));
847 #end[BITWISE]
848 #if[FP]
849 case VECTOR_OP_OR: return (v0, v1, vm) ->
850 v0.bOp(v1, vm, (i, a, b) -> fromBits(toBits(a) | toBits(b)));
851 case VECTOR_OP_ATAN2: return (v0, v1, vm) ->
852 v0.bOp(v1, vm, (i, a, b) -> ($type$) Math.atan2(a, b));
853 case VECTOR_OP_POW: return (v0, v1, vm) ->
854 v0.bOp(v1, vm, (i, a, b) -> ($type$) Math.pow(a, b));
855 case VECTOR_OP_HYPOT: return (v0, v1, vm) ->
856 v0.bOp(v1, vm, (i, a, b) -> ($type$) Math.hypot(a, b));
857 #end[FP]
858 default: return null;
859 }
860 }
861
862 // FIXME: Maybe all of the public final methods in this file (the
863 // simple ones that just call lanewise) should be pushed down to
864 // the X-VectorBits template. They can't optimize properly at
865 // this level, and must rely on inlining. Does it work?
866 // (If it works, of course keep the code here.)
867
868 /**
869 * Combines the lane values of this vector
870 * with the value of a broadcast scalar.
871 *
872 * This is a lane-wise binary operation which applies
873 * the selected operation to each lane.
874 * The return value will be equal to this expression:
875 * {@code this.lanewise(op, this.broadcast(e))}.
876 *
877 * @param op the operation used to process lane values
878 * @param e the input scalar
879 * @return the result of applying the operation lane-wise
880 * to the two input vectors
881 * @throws UnsupportedOperationException if this vector does
882 * not support the requested operation
883 * @see #lanewise(VectorOperators.Binary,Vector)
884 * @see #lanewise(VectorOperators.Binary,$type$,VectorMask)
885 */
886 @ForceInline
887 public final
888 $abstractvectortype$ lanewise(VectorOperators.Binary op,
889 $type$ e) {
890 #if[BITWISE]
891 if (opKind(op, VO_SHIFT) && ($type$)(int)e == e) {
892 return lanewiseShift(op, (int) e);
893 }
894 if (op == AND_NOT) {
895 op = AND; e = ($type$) ~e;
896 }
897 #end[BITWISE]
898 return lanewise(op, broadcast(e));
899 }
900
901 /**
902 * Combines the lane values of this vector
903 * with the value of a broadcast scalar,
904 * with selection of lane elements controlled by a mask.
905 *
906 * This is a masked lane-wise binary operation which applies
907 * the selected operation to each lane.
908 * The return value will be equal to this expression:
909 * {@code this.lanewise(op, this.broadcast(e), m)}.
910 *
911 * @param op the operation used to process lane values
912 * @param e the input scalar
913 * @param m the mask controlling lane selection
914 * @return the result of applying the operation lane-wise
915 * to the input vector and the scalar
916 * @throws UnsupportedOperationException if this vector does
917 * not support the requested operation
918 * @see #lanewise(VectorOperators.Binary,Vector,VectorMask)
919 * @see #lanewise(VectorOperators.Binary,$type$)
920 */
921 @ForceInline
922 public final
923 $abstractvectortype$ lanewise(VectorOperators.Binary op,
924 $type$ e,
925 VectorMask<$Boxtype$> m) {
926 #if[BITWISE]
927 if (opKind(op, VO_SHIFT) && ($type$)(int)e == e) {
928 return lanewiseShift(op, (int) e, m);
929 }
930 if (op == AND_NOT) {
931 op = AND; e = ($type$) ~e;
932 }
933 #end[BITWISE]
934 return lanewise(op, broadcast(e), m);
935 }
936
937 #if[!long]
938 /**
939 * {@inheritDoc} <!--workaround-->
940 * @apiNote
941 * When working with vector subtypes like {@code $abstractvectortype$},
942 * {@linkplain #lanewise(VectorOperators.Binary,$type$)
943 * the more strongly typed method}
944 * is typically selected. It can be explicitly selected
945 * using a cast: {@code v.lanewise(op,($type$)e)}.
946 * The two expressions will produce numerically identical results.
947 */
948 @ForceInline
949 public final
950 $abstractvectortype$ lanewise(VectorOperators.Binary op,
951 long e) {
952 $type$ e1 = ($type$) e;
953 #if[BITWISE]
954 if ((long)e1 != e
955 // allow shift ops to clip down their int parameters
956 && !(opKind(op, VO_SHIFT) && (int)e1 == e)) {
957 #else[BITWISE]
958 if ((long)e1 != e) {
959 #end[BITWISE]
960 vspecies().checkValue(e); // for exception
961 }
962 return lanewise(op, e1);
963 }
964
965 /**
966 * {@inheritDoc} <!--workaround-->
967 * @apiNote
968 * When working with vector subtypes like {@code $abstractvectortype$},
969 * {@linkplain #lanewise(VectorOperators.Binary,$type$,VectorMask)
970 * the more strongly typed method}
971 * is typically selected. It can be explicitly selected
972 * using a cast: {@code v.lanewise(op,($type$)e,m)}.
973 * The two expressions will produce numerically identical results.
974 */
975 @ForceInline
976 public final
977 $abstractvectortype$ lanewise(VectorOperators.Binary op,
978 long e, VectorMask<$Boxtype$> m) {
979 $type$ e1 = ($type$) e;
980 #if[BITWISE]
981 if ((long)e1 != e
982 // allow shift ops to clip down their int parameters
983 && !(opKind(op, VO_SHIFT) && (int)e1 == e)) {
984 #else[BITWISE]
985 if ((long)e1 != e) {
986 #end[BITWISE]
987 vspecies().checkValue(e); // for exception
988 }
989 return lanewise(op, e1, m);
990 }
991 #end[!long]
992
993 #if[BITWISE]
994 /*package-private*/
995 abstract $abstractvectortype$
996 lanewiseShift(VectorOperators.Binary op, int e);
997
998 /*package-private*/
999 @ForceInline
1000 final $abstractvectortype$
1001 lanewiseShiftTemplate(VectorOperators.Binary op, int e) {
1002 // Special handling for these. FIXME: Refactor?
1003 assert(opKind(op, VO_SHIFT));
1004 // As per shift specification for Java, mask the shift count.
1005 e &= SHIFT_MASK;
1006 int opc = opCode(op);
1007 return VectorSupport.broadcastInt(
1008 opc, getClass(), null, $type$.class, length(),
1009 this, e, null,
1010 BIN_INT_IMPL.find(op, opc, $abstractvectortype$::broadcastIntOperations));
1011 }
1012
1013 /*package-private*/
1014 abstract $abstractvectortype$
1015 lanewiseShift(VectorOperators.Binary op, int e, VectorMask<$Boxtype$> m);
1016
1017 /*package-private*/
1018 @ForceInline
1019 final $abstractvectortype$
1020 lanewiseShiftTemplate(VectorOperators.Binary op,
1021 Class<? extends VectorMask<$Boxtype$>> maskClass,
1022 int e, VectorMask<$Boxtype$> m) {
1023 m.check(maskClass, this);
1024 assert(opKind(op, VO_SHIFT));
1025 // As per shift specification for Java, mask the shift count.
1026 e &= SHIFT_MASK;
1027 int opc = opCode(op);
1028 return VectorSupport.broadcastInt(
1029 opc, getClass(), maskClass, $type$.class, length(),
1030 this, e, m,
1031 BIN_INT_IMPL.find(op, opc, $abstractvectortype$::broadcastIntOperations));
1032 }
1033
1034 private static final
1035 ImplCache<Binary,VectorBroadcastIntOp<$abstractvectortype$, VectorMask<$Boxtype$>>> BIN_INT_IMPL
1036 = new ImplCache<>(Binary.class, $Type$Vector.class);
1037
1038 private static VectorBroadcastIntOp<$abstractvectortype$, VectorMask<$Boxtype$>> broadcastIntOperations(int opc_) {
1039 switch (opc_) {
1040 case VECTOR_OP_LSHIFT: return (v, n, m) ->
1041 v.uOp(m, (i, a) -> ($type$)(a << n));
1042 case VECTOR_OP_RSHIFT: return (v, n, m) ->
1043 v.uOp(m, (i, a) -> ($type$)(a >> n));
1044 case VECTOR_OP_URSHIFT: return (v, n, m) ->
1045 v.uOp(m, (i, a) -> ($type$)((a & LSHR_SETUP_MASK) >>> n));
1046 case VECTOR_OP_LROTATE: return (v, n, m) ->
1047 v.uOp(m, (i, a) -> rotateLeft(a, (int)n));
1048 case VECTOR_OP_RROTATE: return (v, n, m) ->
1049 v.uOp(m, (i, a) -> rotateRight(a, (int)n));
1050 default: return null;
1051 }
1052 }
1053
1054 // As per shift specification for Java, mask the shift count.
1055 // We mask 0X3F (long), 0X1F (int), 0x0F (short), 0x7 (byte).
1056 // The latter two maskings go beyond the JLS, but seem reasonable
1057 // since our lane types are first-class types, not just dressed
1058 // up ints.
1059 private static final int SHIFT_MASK = ($Boxtype$.SIZE - 1);
1060 #if[byteOrShort]
1061 // Also simulate >>> on sub-word variables with a mask.
1062 private static final int LSHR_SETUP_MASK = ((1 << $Boxtype$.SIZE) - 1);
1063 #else[byteOrShort]
1064 private static final $type$ LSHR_SETUP_MASK = -1;
1065 #end[byteOrShort]
1066 #end[BITWISE]
1067
1068 // Ternary lanewise support
1069
1070 // Ternary operators come in eight variations:
1071 // lanewise(op, [broadcast(e1)|v1], [broadcast(e2)|v2])
1072 // lanewise(op, [broadcast(e1)|v1], [broadcast(e2)|v2], mask)
1073
1074 // It is annoying to support all of these variations of masking
1075 // and broadcast, but it would be more surprising not to continue
1076 // the obvious pattern started by unary and binary.
1077
1078 /**
1079 * {@inheritDoc} <!--workaround-->
1080 * @see #lanewise(VectorOperators.Ternary,$type$,$type$,VectorMask)
1081 * @see #lanewise(VectorOperators.Ternary,Vector,$type$,VectorMask)
1082 * @see #lanewise(VectorOperators.Ternary,$type$,Vector,VectorMask)
1083 * @see #lanewise(VectorOperators.Ternary,$type$,$type$)
1084 * @see #lanewise(VectorOperators.Ternary,Vector,$type$)
1085 * @see #lanewise(VectorOperators.Ternary,$type$,Vector)
1086 */
1087 @Override
1088 public abstract
1089 $abstractvectortype$ lanewise(VectorOperators.Ternary op,
1090 Vector<$Boxtype$> v1,
1091 Vector<$Boxtype$> v2);
1092 @ForceInline
1093 final
1094 $abstractvectortype$ lanewiseTemplate(VectorOperators.Ternary op,
1095 Vector<$Boxtype$> v1,
1096 Vector<$Boxtype$> v2) {
1097 $abstractvectortype$ that = ($abstractvectortype$) v1;
1098 $abstractvectortype$ tother = ($abstractvectortype$) v2;
1099 // It's a word: https://www.dictionary.com/browse/tother
1100 // See also Chapter 11 of Dickens, Our Mutual Friend:
1101 // "Totherest Governor," replied Mr Riderhood...
1102 that.check(this);
1103 tother.check(this);
1104 #if[BITWISE]
1105 if (op == BITWISE_BLEND) {
1106 // FIXME: Support this in the JIT.
1107 that = this.lanewise(XOR, that).lanewise(AND, tother);
1108 return this.lanewise(XOR, that);
1109 }
1110 #end[BITWISE]
1111 int opc = opCode(op);
1112 return VectorSupport.ternaryOp(
1113 opc, getClass(), null, $type$.class, length(),
1114 this, that, tother, null,
1115 TERN_IMPL.find(op, opc, $abstractvectortype$::ternaryOperations));
1116 }
1117
1118 /**
1119 * {@inheritDoc} <!--workaround-->
1120 * @see #lanewise(VectorOperators.Ternary,$type$,$type$,VectorMask)
1121 * @see #lanewise(VectorOperators.Ternary,Vector,$type$,VectorMask)
1122 * @see #lanewise(VectorOperators.Ternary,$type$,Vector,VectorMask)
1123 */
1124 @Override
1125 public abstract
1126 $abstractvectortype$ lanewise(VectorOperators.Ternary op,
1127 Vector<$Boxtype$> v1,
1128 Vector<$Boxtype$> v2,
1129 VectorMask<$Boxtype$> m);
1130 @ForceInline
1131 final
1132 $abstractvectortype$ lanewiseTemplate(VectorOperators.Ternary op,
1133 Class<? extends VectorMask<$Boxtype$>> maskClass,
1134 Vector<$Boxtype$> v1,
1135 Vector<$Boxtype$> v2,
1136 VectorMask<$Boxtype$> m) {
1137 $abstractvectortype$ that = ($abstractvectortype$) v1;
1138 $abstractvectortype$ tother = ($abstractvectortype$) v2;
1139 // It's a word: https://www.dictionary.com/browse/tother
1140 // See also Chapter 11 of Dickens, Our Mutual Friend:
1141 // "Totherest Governor," replied Mr Riderhood...
1142 that.check(this);
1143 tother.check(this);
1144 m.check(maskClass, this);
1145
1146 #if[BITWISE]
1147 if (op == BITWISE_BLEND) {
1148 // FIXME: Support this in the JIT.
1149 that = this.lanewise(XOR, that).lanewise(AND, tother);
1150 return this.lanewise(XOR, that, m);
1151 }
1152 #end[BITWISE]
1153 int opc = opCode(op);
1154 return VectorSupport.ternaryOp(
1155 opc, getClass(), maskClass, $type$.class, length(),
1156 this, that, tother, m,
1157 TERN_IMPL.find(op, opc, $abstractvectortype$::ternaryOperations));
1158 }
1159
1160 private static final
1161 ImplCache<Ternary, TernaryOperation<$abstractvectortype$, VectorMask<$Boxtype$>>>
1162 TERN_IMPL = new ImplCache<>(Ternary.class, $Type$Vector.class);
1163
1164 private static TernaryOperation<$abstractvectortype$, VectorMask<$Boxtype$>> ternaryOperations(int opc_) {
1165 switch (opc_) {
1166 #if[FP]
1167 case VECTOR_OP_FMA: return (v0, v1_, v2_, m) ->
1168 v0.tOp(v1_, v2_, m, (i, a, b, c) -> Math.fma(a, b, c));
1169 #end[FP]
1170 default: return null;
1171 }
1172 }
1173
1174 /**
1175 * Combines the lane values of this vector
1176 * with the values of two broadcast scalars.
1177 *
1178 * This is a lane-wise ternary operation which applies
1179 * the selected operation to each lane.
1180 * The return value will be equal to this expression:
1181 * {@code this.lanewise(op, this.broadcast(e1), this.broadcast(e2))}.
1182 *
1183 * @param op the operation used to combine lane values
1184 * @param e1 the first input scalar
1185 * @param e2 the second input scalar
1186 * @return the result of applying the operation lane-wise
1187 * to the input vector and the scalars
1188 * @throws UnsupportedOperationException if this vector does
1189 * not support the requested operation
1190 * @see #lanewise(VectorOperators.Ternary,Vector,Vector)
1191 * @see #lanewise(VectorOperators.Ternary,$type$,$type$,VectorMask)
1192 */
1193 @ForceInline
1194 public final
1195 $abstractvectortype$ lanewise(VectorOperators.Ternary op, //(op,e1,e2)
1196 $type$ e1,
1197 $type$ e2) {
1198 return lanewise(op, broadcast(e1), broadcast(e2));
1199 }
1200
1201 /**
1202 * Combines the lane values of this vector
1203 * with the values of two broadcast scalars,
1204 * with selection of lane elements controlled by a mask.
1205 *
1206 * This is a masked lane-wise ternary operation which applies
1207 * the selected operation to each lane.
1208 * The return value will be equal to this expression:
1209 * {@code this.lanewise(op, this.broadcast(e1), this.broadcast(e2), m)}.
1210 *
1211 * @param op the operation used to combine lane values
1212 * @param e1 the first input scalar
1213 * @param e2 the second input scalar
1214 * @param m the mask controlling lane selection
1215 * @return the result of applying the operation lane-wise
1216 * to the input vector and the scalars
1217 * @throws UnsupportedOperationException if this vector does
1218 * not support the requested operation
1219 * @see #lanewise(VectorOperators.Ternary,Vector,Vector,VectorMask)
1220 * @see #lanewise(VectorOperators.Ternary,$type$,$type$)
1221 */
1222 @ForceInline
1223 public final
1224 $abstractvectortype$ lanewise(VectorOperators.Ternary op, //(op,e1,e2,m)
1225 $type$ e1,
1226 $type$ e2,
1227 VectorMask<$Boxtype$> m) {
1228 return lanewise(op, broadcast(e1), broadcast(e2), m);
1229 }
1230
1231 /**
1232 * Combines the lane values of this vector
1233 * with the values of another vector and a broadcast scalar.
1234 *
1235 * This is a lane-wise ternary operation which applies
1236 * the selected operation to each lane.
1237 * The return value will be equal to this expression:
1238 * {@code this.lanewise(op, v1, this.broadcast(e2))}.
1239 *
1240 * @param op the operation used to combine lane values
1241 * @param v1 the other input vector
1242 * @param e2 the input scalar
1243 * @return the result of applying the operation lane-wise
1244 * to the input vectors and the scalar
1245 * @throws UnsupportedOperationException if this vector does
1246 * not support the requested operation
1247 * @see #lanewise(VectorOperators.Ternary,$type$,$type$)
1248 * @see #lanewise(VectorOperators.Ternary,Vector,$type$,VectorMask)
1249 */
1250 @ForceInline
1251 public final
1252 $abstractvectortype$ lanewise(VectorOperators.Ternary op, //(op,v1,e2)
1253 Vector<$Boxtype$> v1,
1254 $type$ e2) {
1255 return lanewise(op, v1, broadcast(e2));
1256 }
1257
1258 /**
1259 * Combines the lane values of this vector
1260 * with the values of another vector and a broadcast scalar,
1261 * with selection of lane elements controlled by a mask.
1262 *
1263 * This is a masked lane-wise ternary operation which applies
1264 * the selected operation to each lane.
1265 * The return value will be equal to this expression:
1266 * {@code this.lanewise(op, v1, this.broadcast(e2), m)}.
1267 *
1268 * @param op the operation used to combine lane values
1269 * @param v1 the other input vector
1270 * @param e2 the input scalar
1271 * @param m the mask controlling lane selection
1272 * @return the result of applying the operation lane-wise
1273 * to the input vectors and the scalar
1274 * @throws UnsupportedOperationException if this vector does
1275 * not support the requested operation
1276 * @see #lanewise(VectorOperators.Ternary,Vector,Vector)
1277 * @see #lanewise(VectorOperators.Ternary,$type$,$type$,VectorMask)
1278 * @see #lanewise(VectorOperators.Ternary,Vector,$type$)
1279 */
1280 @ForceInline
1281 public final
1282 $abstractvectortype$ lanewise(VectorOperators.Ternary op, //(op,v1,e2,m)
1283 Vector<$Boxtype$> v1,
1284 $type$ e2,
1285 VectorMask<$Boxtype$> m) {
1286 return lanewise(op, v1, broadcast(e2), m);
1287 }
1288
1289 /**
1290 * Combines the lane values of this vector
1291 * with the values of another vector and a broadcast scalar.
1292 *
1293 * This is a lane-wise ternary operation which applies
1294 * the selected operation to each lane.
1295 * The return value will be equal to this expression:
1296 * {@code this.lanewise(op, this.broadcast(e1), v2)}.
1297 *
1298 * @param op the operation used to combine lane values
1299 * @param e1 the input scalar
1300 * @param v2 the other input vector
1301 * @return the result of applying the operation lane-wise
1302 * to the input vectors and the scalar
1303 * @throws UnsupportedOperationException if this vector does
1304 * not support the requested operation
1305 * @see #lanewise(VectorOperators.Ternary,Vector,Vector)
1306 * @see #lanewise(VectorOperators.Ternary,$type$,Vector,VectorMask)
1307 */
1308 @ForceInline
1309 public final
1310 $abstractvectortype$ lanewise(VectorOperators.Ternary op, //(op,e1,v2)
1311 $type$ e1,
1312 Vector<$Boxtype$> v2) {
1313 return lanewise(op, broadcast(e1), v2);
1314 }
1315
1316 /**
1317 * Combines the lane values of this vector
1318 * with the values of another vector and a broadcast scalar,
1319 * with selection of lane elements controlled by a mask.
1320 *
1321 * This is a masked lane-wise ternary operation which applies
1322 * the selected operation to each lane.
1323 * The return value will be equal to this expression:
1324 * {@code this.lanewise(op, this.broadcast(e1), v2, m)}.
1325 *
1326 * @param op the operation used to combine lane values
1327 * @param e1 the input scalar
1328 * @param v2 the other input vector
1329 * @param m the mask controlling lane selection
1330 * @return the result of applying the operation lane-wise
1331 * to the input vectors and the scalar
1332 * @throws UnsupportedOperationException if this vector does
1333 * not support the requested operation
1334 * @see #lanewise(VectorOperators.Ternary,Vector,Vector,VectorMask)
1335 * @see #lanewise(VectorOperators.Ternary,$type$,Vector)
1336 */
1337 @ForceInline
1338 public final
1339 $abstractvectortype$ lanewise(VectorOperators.Ternary op, //(op,e1,v2,m)
1340 $type$ e1,
1341 Vector<$Boxtype$> v2,
1342 VectorMask<$Boxtype$> m) {
1343 return lanewise(op, broadcast(e1), v2, m);
1344 }
1345
1346 // (Thus endeth the Great and Mighty Ternary Ogdoad.)
1347 // https://en.wikipedia.org/wiki/Ogdoad
1348
1349 /// FULL-SERVICE BINARY METHODS: ADD, SUB, MUL, DIV
1350 //
1351 // These include masked and non-masked versions.
1352 // This subclass adds broadcast (masked or not).
1353
1354 /**
1355 * {@inheritDoc} <!--workaround-->
1356 * @see #add($type$)
1357 */
1358 @Override
1359 @ForceInline
1360 public final $abstractvectortype$ add(Vector<$Boxtype$> v) {
1361 return lanewise(ADD, v);
1362 }
1363
1364 /**
1365 * Adds this vector to the broadcast of an input scalar.
1366 *
1367 * This is a lane-wise binary operation which applies
1368 * the primitive addition operation ({@code +}) to each lane.
1369 *
1370 * This method is also equivalent to the expression
1371 * {@link #lanewise(VectorOperators.Binary,$type$)
1372 * lanewise}{@code (}{@link VectorOperators#ADD
1373 * ADD}{@code , e)}.
1374 *
1375 * @param e the input scalar
1376 * @return the result of adding each lane of this vector to the scalar
1377 * @see #add(Vector)
1378 * @see #broadcast($type$)
1379 * @see #add($type$,VectorMask)
1380 * @see VectorOperators#ADD
1381 * @see #lanewise(VectorOperators.Binary,Vector)
1382 * @see #lanewise(VectorOperators.Binary,$type$)
1383 */
1384 @ForceInline
1385 public final
1386 $abstractvectortype$ add($type$ e) {
1387 return lanewise(ADD, e);
1388 }
1389
1390 /**
1391 * {@inheritDoc} <!--workaround-->
1392 * @see #add($type$,VectorMask)
1393 */
1394 @Override
1395 @ForceInline
1396 public final $abstractvectortype$ add(Vector<$Boxtype$> v,
1397 VectorMask<$Boxtype$> m) {
1398 return lanewise(ADD, v, m);
1399 }
1400
1401 /**
1402 * Adds this vector to the broadcast of an input scalar,
1403 * selecting lane elements controlled by a mask.
1404 *
1405 * This is a masked lane-wise binary operation which applies
1406 * the primitive addition operation ({@code +}) to each lane.
1407 *
1408 * This method is also equivalent to the expression
1409 * {@link #lanewise(VectorOperators.Binary,$type$,VectorMask)
1410 * lanewise}{@code (}{@link VectorOperators#ADD
1411 * ADD}{@code , s, m)}.
1412 *
1413 * @param e the input scalar
1414 * @param m the mask controlling lane selection
1415 * @return the result of adding each lane of this vector to the scalar
1416 * @see #add(Vector,VectorMask)
1417 * @see #broadcast($type$)
1418 * @see #add($type$)
1419 * @see VectorOperators#ADD
1420 * @see #lanewise(VectorOperators.Binary,Vector)
1421 * @see #lanewise(VectorOperators.Binary,$type$)
1422 */
1423 @ForceInline
1424 public final $abstractvectortype$ add($type$ e,
1425 VectorMask<$Boxtype$> m) {
1426 return lanewise(ADD, e, m);
1427 }
1428
1429 /**
1430 * {@inheritDoc} <!--workaround-->
1431 * @see #sub($type$)
1432 */
1433 @Override
1434 @ForceInline
1435 public final $abstractvectortype$ sub(Vector<$Boxtype$> v) {
1436 return lanewise(SUB, v);
1437 }
1438
1439 /**
1440 * Subtracts an input scalar from this vector.
1441 *
1442 * This is a masked lane-wise binary operation which applies
1443 * the primitive subtraction operation ({@code -}) to each lane.
1444 *
1445 * This method is also equivalent to the expression
1446 * {@link #lanewise(VectorOperators.Binary,$type$)
1447 * lanewise}{@code (}{@link VectorOperators#SUB
1448 * SUB}{@code , e)}.
1449 *
1450 * @param e the input scalar
1451 * @return the result of subtracting the scalar from each lane of this vector
1452 * @see #sub(Vector)
1453 * @see #broadcast($type$)
1454 * @see #sub($type$,VectorMask)
1455 * @see VectorOperators#SUB
1456 * @see #lanewise(VectorOperators.Binary,Vector)
1457 * @see #lanewise(VectorOperators.Binary,$type$)
1458 */
1459 @ForceInline
1460 public final $abstractvectortype$ sub($type$ e) {
1461 return lanewise(SUB, e);
1462 }
1463
1464 /**
1465 * {@inheritDoc} <!--workaround-->
1466 * @see #sub($type$,VectorMask)
1467 */
1468 @Override
1469 @ForceInline
1470 public final $abstractvectortype$ sub(Vector<$Boxtype$> v,
1471 VectorMask<$Boxtype$> m) {
1472 return lanewise(SUB, v, m);
1473 }
1474
1475 /**
1476 * Subtracts an input scalar from this vector
1477 * under the control of a mask.
1478 *
1479 * This is a masked lane-wise binary operation which applies
1480 * the primitive subtraction operation ({@code -}) to each lane.
1481 *
1482 * This method is also equivalent to the expression
1483 * {@link #lanewise(VectorOperators.Binary,$type$,VectorMask)
1484 * lanewise}{@code (}{@link VectorOperators#SUB
1485 * SUB}{@code , s, m)}.
1486 *
1487 * @param e the input scalar
1488 * @param m the mask controlling lane selection
1489 * @return the result of subtracting the scalar from each lane of this vector
1490 * @see #sub(Vector,VectorMask)
1491 * @see #broadcast($type$)
1492 * @see #sub($type$)
1493 * @see VectorOperators#SUB
1494 * @see #lanewise(VectorOperators.Binary,Vector)
1495 * @see #lanewise(VectorOperators.Binary,$type$)
1496 */
1497 @ForceInline
1498 public final $abstractvectortype$ sub($type$ e,
1499 VectorMask<$Boxtype$> m) {
1500 return lanewise(SUB, e, m);
1501 }
1502
1503 /**
1504 * {@inheritDoc} <!--workaround-->
1505 * @see #mul($type$)
1506 */
1507 @Override
1508 @ForceInline
1509 public final $abstractvectortype$ mul(Vector<$Boxtype$> v) {
1510 return lanewise(MUL, v);
1511 }
1512
1513 /**
1514 * Multiplies this vector by the broadcast of an input scalar.
1515 *
1516 * This is a lane-wise binary operation which applies
1517 * the primitive multiplication operation ({@code *}) to each lane.
1518 *
1519 * This method is also equivalent to the expression
1520 * {@link #lanewise(VectorOperators.Binary,$type$)
1521 * lanewise}{@code (}{@link VectorOperators#MUL
1522 * MUL}{@code , e)}.
1523 *
1524 * @param e the input scalar
1525 * @return the result of multiplying this vector by the given scalar
1526 * @see #mul(Vector)
1527 * @see #broadcast($type$)
1528 * @see #mul($type$,VectorMask)
1529 * @see VectorOperators#MUL
1530 * @see #lanewise(VectorOperators.Binary,Vector)
1531 * @see #lanewise(VectorOperators.Binary,$type$)
1532 */
1533 @ForceInline
1534 public final $abstractvectortype$ mul($type$ e) {
1535 return lanewise(MUL, e);
1536 }
1537
1538 /**
1539 * {@inheritDoc} <!--workaround-->
1540 * @see #mul($type$,VectorMask)
1541 */
1542 @Override
1543 @ForceInline
1544 public final $abstractvectortype$ mul(Vector<$Boxtype$> v,
1545 VectorMask<$Boxtype$> m) {
1546 return lanewise(MUL, v, m);
1547 }
1548
1549 /**
1550 * Multiplies this vector by the broadcast of an input scalar,
1551 * selecting lane elements controlled by a mask.
1552 *
1553 * This is a masked lane-wise binary operation which applies
1554 * the primitive multiplication operation ({@code *}) to each lane.
1555 *
1556 * This method is also equivalent to the expression
1557 * {@link #lanewise(VectorOperators.Binary,$type$,VectorMask)
1558 * lanewise}{@code (}{@link VectorOperators#MUL
1559 * MUL}{@code , s, m)}.
1560 *
1561 * @param e the input scalar
1562 * @param m the mask controlling lane selection
1563 * @return the result of muling each lane of this vector to the scalar
1564 * @see #mul(Vector,VectorMask)
1565 * @see #broadcast($type$)
1566 * @see #mul($type$)
1567 * @see VectorOperators#MUL
1568 * @see #lanewise(VectorOperators.Binary,Vector)
1569 * @see #lanewise(VectorOperators.Binary,$type$)
1570 */
1571 @ForceInline
1572 public final $abstractvectortype$ mul($type$ e,
1573 VectorMask<$Boxtype$> m) {
1574 return lanewise(MUL, e, m);
1575 }
1576
1577 /**
1578 * {@inheritDoc} <!--workaround-->
1579 #if[FP]
1580 * @apiNote Because the underlying scalar operator is an IEEE
1581 * floating point number, division by zero in fact will
1582 * not throw an exception, but will yield a signed
1583 * infinity or NaN.
1584 #else[FP]
1585 * @apiNote If there is a zero divisor, {@code
1586 * ArithmeticException} will be thrown.
1587 #end[FP]
1588 */
1589 @Override
1590 @ForceInline
1591 public final $abstractvectortype$ div(Vector<$Boxtype$> v) {
1592 return lanewise(DIV, v);
1593 }
1594
1595 /**
1596 * Divides this vector by the broadcast of an input scalar.
1597 *
1598 * This is a lane-wise binary operation which applies
1599 * the primitive division operation ({@code /}) to each lane.
1600 *
1601 * This method is also equivalent to the expression
1602 * {@link #lanewise(VectorOperators.Binary,$type$)
1603 * lanewise}{@code (}{@link VectorOperators#DIV
1604 * DIV}{@code , e)}.
1605 *
1606 #if[FP]
1607 * @apiNote Because the underlying scalar operator is an IEEE
1608 * floating point number, division by zero in fact will
1609 * not throw an exception, but will yield a signed
1610 * infinity or NaN.
1611 #else[FP]
1612 * @apiNote If there is a zero divisor, {@code
1613 * ArithmeticException} will be thrown.
1614 #end[FP]
1615 *
1616 * @param e the input scalar
1617 * @return the result of dividing each lane of this vector by the scalar
1618 * @see #div(Vector)
1619 * @see #broadcast($type$)
1620 * @see #div($type$,VectorMask)
1621 * @see VectorOperators#DIV
1622 * @see #lanewise(VectorOperators.Binary,Vector)
1623 * @see #lanewise(VectorOperators.Binary,$type$)
1624 */
1625 @ForceInline
1626 public final $abstractvectortype$ div($type$ e) {
1627 return lanewise(DIV, e);
1628 }
1629
1630 /**
1631 * {@inheritDoc} <!--workaround-->
1632 * @see #div($type$,VectorMask)
1633 #if[FP]
1634 * @apiNote Because the underlying scalar operator is an IEEE
1635 * floating point number, division by zero in fact will
1636 * not throw an exception, but will yield a signed
1637 * infinity or NaN.
1638 #else[FP]
1639 * @apiNote If there is a zero divisor, {@code
1640 * ArithmeticException} will be thrown.
1641 #end[FP]
1642 */
1643 @Override
1644 @ForceInline
1645 public final $abstractvectortype$ div(Vector<$Boxtype$> v,
1646 VectorMask<$Boxtype$> m) {
1647 return lanewise(DIV, v, m);
1648 }
1649
1650 /**
1651 * Divides this vector by the broadcast of an input scalar,
1652 * selecting lane elements controlled by a mask.
1653 *
1654 * This is a masked lane-wise binary operation which applies
1655 * the primitive division operation ({@code /}) to each lane.
1656 *
1657 * This method is also equivalent to the expression
1658 * {@link #lanewise(VectorOperators.Binary,$type$,VectorMask)
1659 * lanewise}{@code (}{@link VectorOperators#DIV
1660 * DIV}{@code , s, m)}.
1661 *
1662 #if[FP]
1663 * @apiNote Because the underlying scalar operator is an IEEE
1664 * floating point number, division by zero in fact will
1665 * not throw an exception, but will yield a signed
1666 * infinity or NaN.
1667 #else[FP]
1668 * @apiNote If there is a zero divisor, {@code
1669 * ArithmeticException} will be thrown.
1670 #end[FP]
1671 *
1672 * @param e the input scalar
1673 * @param m the mask controlling lane selection
1674 * @return the result of dividing each lane of this vector by the scalar
1675 * @see #div(Vector,VectorMask)
1676 * @see #broadcast($type$)
1677 * @see #div($type$)
1678 * @see VectorOperators#DIV
1679 * @see #lanewise(VectorOperators.Binary,Vector)
1680 * @see #lanewise(VectorOperators.Binary,$type$)
1681 */
1682 @ForceInline
1683 public final $abstractvectortype$ div($type$ e,
1684 VectorMask<$Boxtype$> m) {
1685 return lanewise(DIV, e, m);
1686 }
1687
1688 /// END OF FULL-SERVICE BINARY METHODS
1689
1690 /// SECOND-TIER BINARY METHODS
1691 //
1692 // There are no masked versions.
1693
1694 /**
1695 * {@inheritDoc} <!--workaround-->
1696 #if[FP]
1697 * @apiNote
1698 * For this method, floating point negative
1699 * zero {@code -0.0} is treated as a value distinct from, and less
1700 * than the default value (positive zero).
1701 #end[FP]
1702 */
1703 @Override
1704 @ForceInline
1705 public final $abstractvectortype$ min(Vector<$Boxtype$> v) {
1706 return lanewise(MIN, v);
1707 }
1708
1709 // FIXME: "broadcast of an input scalar" is really wordy. Reduce?
1710 /**
1711 * Computes the smaller of this vector and the broadcast of an input scalar.
1712 *
1713 * This is a lane-wise binary operation which applies the
1714 * operation {@code Math.min()} to each pair of
1715 * corresponding lane values.
1716 *
1717 * This method is also equivalent to the expression
1718 * {@link #lanewise(VectorOperators.Binary,$type$)
1719 * lanewise}{@code (}{@link VectorOperators#MIN
1720 * MIN}{@code , e)}.
1721 *
1722 * @param e the input scalar
1723 * @return the result of multiplying this vector by the given scalar
1724 * @see #min(Vector)
1725 * @see #broadcast($type$)
1726 * @see VectorOperators#MIN
1727 * @see #lanewise(VectorOperators.Binary,$type$,VectorMask)
1728 #if[FP]
1729 * @apiNote
1730 * For this method, floating point negative
1731 * zero {@code -0.0} is treated as a value distinct from, and less
1732 * than the default value (positive zero).
1733 #end[FP]
1734 */
1735 @ForceInline
1736 public final $abstractvectortype$ min($type$ e) {
1737 return lanewise(MIN, e);
1738 }
1739
1740 /**
1741 * {@inheritDoc} <!--workaround-->
1742 #if[FP]
1743 * @apiNote
1744 * For this method, floating point negative
1745 * zero {@code -0.0} is treated as a value distinct from, and less
1746 * than the default value (positive zero).
1747 #end[FP]
1748 */
1749 @Override
1750 @ForceInline
1751 public final $abstractvectortype$ max(Vector<$Boxtype$> v) {
1752 return lanewise(MAX, v);
1753 }
1754
1755 /**
1756 * Computes the larger of this vector and the broadcast of an input scalar.
1757 *
1758 * This is a lane-wise binary operation which applies the
1759 * operation {@code Math.max()} to each pair of
1760 * corresponding lane values.
1761 *
1762 * This method is also equivalent to the expression
1763 * {@link #lanewise(VectorOperators.Binary,$type$)
1764 * lanewise}{@code (}{@link VectorOperators#MAX
1765 * MAX}{@code , e)}.
1766 *
1767 * @param e the input scalar
1768 * @return the result of multiplying this vector by the given scalar
1769 * @see #max(Vector)
1770 * @see #broadcast($type$)
1771 * @see VectorOperators#MAX
1772 * @see #lanewise(VectorOperators.Binary,$type$,VectorMask)
1773 #if[FP]
1774 * @apiNote
1775 * For this method, floating point negative
1776 * zero {@code -0.0} is treated as a value distinct from, and less
1777 * than the default value (positive zero).
1778 #end[FP]
1779 */
1780 @ForceInline
1781 public final $abstractvectortype$ max($type$ e) {
1782 return lanewise(MAX, e);
1783 }
1784
1785 #if[BITWISE]
1786 // common bitwise operators: and, or, not (with scalar versions)
1787 /**
1788 * Computes the bitwise logical conjunction ({@code &})
1789 * of this vector and a second input vector.
1790 *
1791 * This is a lane-wise binary operation which applies the
1792 * the primitive bitwise "and" operation ({@code &})
1793 * to each pair of corresponding lane values.
1794 *
1795 * This method is also equivalent to the expression
1796 * {@link #lanewise(VectorOperators.Binary,Vector)
1797 * lanewise}{@code (}{@link VectorOperators#AND
1798 * AND}{@code , v)}.
1799 *
1800 * <p>
1801 * This is not a full-service named operation like
1802 * {@link #add(Vector) add}. A masked version of
1803 * this operation is not directly available
1804 * but may be obtained via the masked version of
1805 * {@code lanewise}.
1806 *
1807 * @param v a second input vector
1808 * @return the bitwise {@code &} of this vector and the second input vector
1809 * @see #and($type$)
1810 * @see #or(Vector)
1811 * @see #not()
1812 * @see VectorOperators#AND
1813 * @see #lanewise(VectorOperators.Binary,Vector,VectorMask)
1814 */
1815 @ForceInline
1816 public final $abstractvectortype$ and(Vector<$Boxtype$> v) {
1817 return lanewise(AND, v);
1818 }
1819
1820 /**
1821 * Computes the bitwise logical conjunction ({@code &})
1822 * of this vector and a scalar.
1823 *
1824 * This is a lane-wise binary operation which applies the
1825 * the primitive bitwise "and" operation ({@code &})
1826 * to each pair of corresponding lane values.
1827 *
1828 * This method is also equivalent to the expression
1829 * {@link #lanewise(VectorOperators.Binary,Vector)
1830 * lanewise}{@code (}{@link VectorOperators#AND
1831 * AND}{@code , e)}.
1832 *
1833 * @param e an input scalar
1834 * @return the bitwise {@code &} of this vector and scalar
1835 * @see #and(Vector)
1836 * @see VectorOperators#AND
1837 * @see #lanewise(VectorOperators.Binary,Vector,VectorMask)
1838 */
1839 @ForceInline
1840 public final $abstractvectortype$ and($type$ e) {
1841 return lanewise(AND, e);
1842 }
1843
1844 /**
1845 * Computes the bitwise logical disjunction ({@code |})
1846 * of this vector and a second input vector.
1847 *
1848 * This is a lane-wise binary operation which applies the
1849 * the primitive bitwise "or" operation ({@code |})
1850 * to each pair of corresponding lane values.
1851 *
1852 * This method is also equivalent to the expression
1853 * {@link #lanewise(VectorOperators.Binary,Vector)
1854 * lanewise}{@code (}{@link VectorOperators#OR
1855 * AND}{@code , v)}.
1856 *
1857 * <p>
1858 * This is not a full-service named operation like
1859 * {@link #add(Vector) add}. A masked version of
1860 * this operation is not directly available
1861 * but may be obtained via the masked version of
1862 * {@code lanewise}.
1863 *
1864 * @param v a second input vector
1865 * @return the bitwise {@code |} of this vector and the second input vector
1866 * @see #or($type$)
1867 * @see #and(Vector)
1868 * @see #not()
1869 * @see VectorOperators#OR
1870 * @see #lanewise(VectorOperators.Binary,Vector,VectorMask)
1871 */
1872 @ForceInline
1873 public final $abstractvectortype$ or(Vector<$Boxtype$> v) {
1874 return lanewise(OR, v);
1875 }
1876
1877 /**
1878 * Computes the bitwise logical disjunction ({@code |})
1879 * of this vector and a scalar.
1880 *
1881 * This is a lane-wise binary operation which applies the
1882 * the primitive bitwise "or" operation ({@code |})
1883 * to each pair of corresponding lane values.
1884 *
1885 * This method is also equivalent to the expression
1886 * {@link #lanewise(VectorOperators.Binary,Vector)
1887 * lanewise}{@code (}{@link VectorOperators#OR
1888 * OR}{@code , e)}.
1889 *
1890 * @param e an input scalar
1891 * @return the bitwise {@code |} of this vector and scalar
1892 * @see #or(Vector)
1893 * @see VectorOperators#OR
1894 * @see #lanewise(VectorOperators.Binary,Vector,VectorMask)
1895 */
1896 @ForceInline
1897 public final $abstractvectortype$ or($type$ e) {
1898 return lanewise(OR, e);
1899 }
1900
1901 #end[BITWISE]
1902
1903 #if[FP]
1904 // common FP operator: pow
1905 /**
1906 * Raises this vector to the power of a second input vector.
1907 *
1908 * This is a lane-wise binary operation which applies an operation
1909 * conforming to the specification of
1910 * {@link Math#pow Math.pow(a,b)}
1911 * to each pair of corresponding lane values.
1912 #if[intOrFloat]
1913 * The operation is adapted to cast the operands and the result,
1914 * specifically widening {@code float} operands to {@code double}
1915 * operands and narrowing the {@code double} result to a {@code float}
1916 * result.
1917 #end[intOrFloat]
1918 *
1919 * This method is also equivalent to the expression
1920 * {@link #lanewise(VectorOperators.Binary,Vector)
1921 * lanewise}{@code (}{@link VectorOperators#POW
1922 * POW}{@code , b)}.
1923 *
1924 * <p>
1925 * This is not a full-service named operation like
1926 * {@link #add(Vector) add}. A masked version of
1927 * this operation is not directly available
1928 * but may be obtained via the masked version of
1929 * {@code lanewise}.
1930 *
1931 * @param b a vector exponent by which to raise this vector
1932 * @return the {@code b}-th power of this vector
1933 * @see #pow($type$)
1934 * @see VectorOperators#POW
1935 * @see #lanewise(VectorOperators.Binary,Vector,VectorMask)
1936 */
1937 @ForceInline
1938 public final $abstractvectortype$ pow(Vector<$Boxtype$> b) {
1939 return lanewise(POW, b);
1940 }
1941
1942 /**
1943 * Raises this vector to a scalar power.
1944 *
1945 * This is a lane-wise binary operation which applies an operation
1946 * conforming to the specification of
1947 * {@link Math#pow Math.pow(a,b)}
1948 * to each pair of corresponding lane values.
1949 #if[intOrFloat]
1950 * The operation is adapted to cast the operands and the result,
1951 * specifically widening {@code float} operands to {@code double}
1952 * operands and narrowing the {@code double} result to a {@code float}
1953 * result.
1954 #end[intOrFloat]
1955 *
1956 * This method is also equivalent to the expression
1957 * {@link #lanewise(VectorOperators.Binary,Vector)
1958 * lanewise}{@code (}{@link VectorOperators#POW
1959 * POW}{@code , b)}.
1960 *
1961 * @param b a scalar exponent by which to raise this vector
1962 * @return the {@code b}-th power of this vector
1963 * @see #pow(Vector)
1964 * @see VectorOperators#POW
1965 * @see #lanewise(VectorOperators.Binary,$type$,VectorMask)
1966 */
1967 @ForceInline
1968 public final $abstractvectortype$ pow($type$ b) {
1969 return lanewise(POW, b);
1970 }
1971 #end[FP]
1972
1973 /// UNARY METHODS
1974
1975 /**
1976 * {@inheritDoc} <!--workaround-->
1977 */
1978 @Override
1979 @ForceInline
1980 public final
1981 $abstractvectortype$ neg() {
1982 return lanewise(NEG);
1983 }
1984
1985 /**
1986 * {@inheritDoc} <!--workaround-->
1987 */
1988 @Override
1989 @ForceInline
1990 public final
1991 $abstractvectortype$ abs() {
1992 return lanewise(ABS);
1993 }
1994
1995 #if[BITWISE]
1996 // not (~)
1997 /**
1998 * Computes the bitwise logical complement ({@code ~})
1999 * of this vector.
2000 *
2001 * This is a lane-wise binary operation which applies the
2002 * the primitive bitwise "not" operation ({@code ~})
2003 * to each lane value.
2004 *
2005 * This method is also equivalent to the expression
2006 * {@link #lanewise(VectorOperators.Unary)
2007 * lanewise}{@code (}{@link VectorOperators#NOT
2008 * NOT}{@code )}.
2009 *
2010 * <p>
2011 * This is not a full-service named operation like
2012 * {@link #add(Vector) add}. A masked version of
2013 * this operation is not directly available
2014 * but may be obtained via the masked version of
2015 * {@code lanewise}.
2016 *
2017 * @return the bitwise complement {@code ~} of this vector
2018 * @see #and(Vector)
2019 * @see VectorOperators#NOT
2020 * @see #lanewise(VectorOperators.Unary,VectorMask)
2021 */
2022 @ForceInline
2023 public final $abstractvectortype$ not() {
2024 return lanewise(NOT);
2025 }
2026 #end[BITWISE]
2027
2028 #if[FP]
2029 // sqrt
2030 /**
2031 * Computes the square root of this vector.
2032 *
2033 * This is a lane-wise unary operation which applies an operation
2034 * conforming to the specification of
2035 * {@link Math#sqrt Math.sqrt(a)}
2036 * to each lane value.
2037 #if[intOrFloat]
2038 * The operation is adapted to cast the operand and the result,
2039 * specifically widening the {@code float} operand to a {@code double}
2040 * operand and narrowing the {@code double} result to a {@code float}
2041 * result.
2042 #end[intOrFloat]
2043 *
2044 * This method is also equivalent to the expression
2045 * {@link #lanewise(VectorOperators.Unary)
2046 * lanewise}{@code (}{@link VectorOperators#SQRT
2047 * SQRT}{@code )}.
2048 *
2049 * @return the square root of this vector
2050 * @see VectorOperators#SQRT
2051 * @see #lanewise(VectorOperators.Unary,VectorMask)
2052 */
2053 @ForceInline
2054 public final $abstractvectortype$ sqrt() {
2055 return lanewise(SQRT);
2056 }
2057 #end[FP]
2058
2059 /// COMPARISONS
2060
2061 /**
2062 * {@inheritDoc} <!--workaround-->
2063 */
2064 @Override
2065 @ForceInline
2066 public final
2067 VectorMask<$Boxtype$> eq(Vector<$Boxtype$> v) {
2068 return compare(EQ, v);
2069 }
2070
2071 /**
2072 * Tests if this vector is equal to an input scalar.
2073 *
2074 * This is a lane-wise binary test operation which applies
2075 * the primitive equals operation ({@code ==}) to each lane.
2076 * The result is the same as {@code compare(VectorOperators.Comparison.EQ, e)}.
2077 *
2078 * @param e the input scalar
2079 * @return the result mask of testing if this vector
2080 * is equal to {@code e}
2081 * @see #compare(VectorOperators.Comparison,$type$)
2082 */
2083 @ForceInline
2084 public final
2085 VectorMask<$Boxtype$> eq($type$ e) {
2086 return compare(EQ, e);
2087 }
2088
2089 /**
2090 * {@inheritDoc} <!--workaround-->
2091 */
2092 @Override
2093 @ForceInline
2094 public final
2095 VectorMask<$Boxtype$> lt(Vector<$Boxtype$> v) {
2096 return compare(LT, v);
2097 }
2098
2099 /**
2100 * Tests if this vector is less than an input scalar.
2101 *
2102 * This is a lane-wise binary test operation which applies
2103 * the primitive less than operation ({@code <}) to each lane.
2104 * The result is the same as {@code compare(VectorOperators.LT, e)}.
2105 *
2106 * @param e the input scalar
2107 * @return the mask result of testing if this vector
2108 * is less than the input scalar
2109 * @see #compare(VectorOperators.Comparison,$type$)
2110 */
2111 @ForceInline
2112 public final
2113 VectorMask<$Boxtype$> lt($type$ e) {
2114 return compare(LT, e);
2115 }
2116
2117 /**
2118 * {@inheritDoc} <!--workaround-->
2119 */
2120 @Override
2121 public abstract
2122 VectorMask<$Boxtype$> test(VectorOperators.Test op);
2123
2124 /*package-private*/
2125 @ForceInline
2126 final
2127 <M extends VectorMask<$Boxtype$>>
2128 M testTemplate(Class<M> maskType, Test op) {
2129 $Type$Species vsp = vspecies();
2130 if (opKind(op, VO_SPECIAL)) {
2131 $Bitstype$Vector bits = this.viewAsIntegralLanes();
2132 VectorMask<$Boxbitstype$> m;
2133 if (op == IS_DEFAULT) {
2134 m = bits.compare(EQ, ($bitstype$) 0);
2135 } else if (op == IS_NEGATIVE) {
2136 m = bits.compare(LT, ($bitstype$) 0);
2137 }
2138 #if[FP]
2139 else if (op == IS_FINITE ||
2140 op == IS_NAN ||
2141 op == IS_INFINITE) {
2142 // first kill the sign:
2143 bits = bits.and($Boxbitstype$.MAX_VALUE);
2144 // next find the bit pattern for infinity:
2145 $bitstype$ infbits = ($bitstype$) toBits($Boxtype$.POSITIVE_INFINITY);
2146 // now compare:
2147 if (op == IS_FINITE) {
2148 m = bits.compare(LT, infbits);
2149 } else if (op == IS_NAN) {
2150 m = bits.compare(GT, infbits);
2151 } else {
2152 m = bits.compare(EQ, infbits);
2153 }
2154 }
2155 #end[FP]
2156 else {
2157 throw new AssertionError(op);
2158 }
2159 return maskType.cast(m{#if[FP]?.cast(this.vspecies())});
2160 }
2161 int opc = opCode(op);
2162 throw new AssertionError(op);
2163 }
2164
2165 /**
2166 * {@inheritDoc} <!--workaround-->
2167 */
2168 @Override
2169 @ForceInline
2170 public final
2171 VectorMask<$Boxtype$> test(VectorOperators.Test op,
2172 VectorMask<$Boxtype$> m) {
2173 return test(op).and(m);
2174 }
2175
2176 /**
2177 * {@inheritDoc} <!--workaround-->
2178 */
2179 @Override
2180 public abstract
2181 VectorMask<$Boxtype$> compare(VectorOperators.Comparison op, Vector<$Boxtype$> v);
2182
2183 /*package-private*/
2184 @ForceInline
2185 final
2186 <M extends VectorMask<$Boxtype$>>
2187 M compareTemplate(Class<M> maskType, Comparison op, Vector<$Boxtype$> v) {
2188 $abstractvectortype$ that = ($abstractvectortype$) v;
2189 that.check(this);
2190 int opc = opCode(op);
2191 return VectorSupport.compare(
2192 opc, getClass(), maskType, $type$.class, length(),
2193 this, that, null,
2194 (cond, v0, v1, m1) -> {
2195 AbstractMask<$Boxtype$> m
2196 = v0.bTest(cond, v1, (cond_, i, a, b)
2197 -> compareWithOp(cond, a, b));
2198 @SuppressWarnings("unchecked")
2199 M m2 = (M) m;
2200 return m2;
2201 });
2202 }
2203
2204 /*package-private*/
2205 @ForceInline
2206 final
2207 <M extends VectorMask<$Boxtype$>>
2208 M compareTemplate(Class<M> maskType, Comparison op, Vector<$Boxtype$> v, M m) {
2209 $abstractvectortype$ that = ($abstractvectortype$) v;
2210 that.check(this);
2211 m.check(maskType, this);
2212 int opc = opCode(op);
2213 return VectorSupport.compare(
2214 opc, getClass(), maskType, $type$.class, length(),
2215 this, that, m,
2216 (cond, v0, v1, m1) -> {
2217 AbstractMask<$Boxtype$> cmpM
2218 = v0.bTest(cond, v1, (cond_, i, a, b)
2219 -> compareWithOp(cond, a, b));
2220 @SuppressWarnings("unchecked")
2221 M m2 = (M) cmpM.and(m1);
2222 return m2;
2223 });
2224 }
2225
2226 @ForceInline
2227 private static boolean compareWithOp(int cond, $type$ a, $type$ b) {
2228 return switch (cond) {
2229 case BT_eq -> a == b;
2230 case BT_ne -> a != b;
2231 case BT_lt -> a < b;
2232 case BT_le -> a <= b;
2233 case BT_gt -> a > b;
2234 case BT_ge -> a >= b;
2235 #if[!FP]
2236 case BT_ult -> $Boxtype$.compareUnsigned(a, b) < 0;
2237 case BT_ule -> $Boxtype$.compareUnsigned(a, b) <= 0;
2238 case BT_ugt -> $Boxtype$.compareUnsigned(a, b) > 0;
2239 case BT_uge -> $Boxtype$.compareUnsigned(a, b) >= 0;
2240 #end[!FP]
2241 default -> throw new AssertionError();
2242 };
2243 }
2244
2245 /**
2246 * Tests this vector by comparing it with an input scalar,
2247 * according to the given comparison operation.
2248 *
2249 * This is a lane-wise binary test operation which applies
2250 * the comparison operation to each lane.
2251 * <p>
2252 * The result is the same as
2253 * {@code compare(op, broadcast(species(), e))}.
2254 * That is, the scalar may be regarded as broadcast to
2255 * a vector of the same species, and then compared
2256 * against the original vector, using the selected
2257 * comparison operation.
2258 *
2259 * @param op the operation used to compare lane values
2260 * @param e the input scalar
2261 * @return the mask result of testing lane-wise if this vector
2262 * compares to the input, according to the selected
2263 * comparison operator
2264 * @see $abstractvectortype$#compare(VectorOperators.Comparison,Vector)
2265 * @see #eq($type$)
2266 * @see #lt($type$)
2267 */
2268 public abstract
2269 VectorMask<$Boxtype$> compare(Comparison op, $type$ e);
2270
2271 /*package-private*/
2272 @ForceInline
2273 final
2274 <M extends VectorMask<$Boxtype$>>
2275 M compareTemplate(Class<M> maskType, Comparison op, $type$ e) {
2276 return compareTemplate(maskType, op, broadcast(e));
2277 }
2278
2279 /**
2280 * Tests this vector by comparing it with an input scalar,
2281 * according to the given comparison operation,
2282 * in lanes selected by a mask.
2283 *
2284 * This is a masked lane-wise binary test operation which applies
2285 * to each pair of corresponding lane values.
2286 *
2287 * The returned result is equal to the expression
2288 * {@code compare(op,s).and(m)}.
2289 *
2290 * @param op the operation used to compare lane values
2291 * @param e the input scalar
2292 * @param m the mask controlling lane selection
2293 * @return the mask result of testing lane-wise if this vector
2294 * compares to the input, according to the selected
2295 * comparison operator,
2296 * and only in the lanes selected by the mask
2297 * @see $abstractvectortype$#compare(VectorOperators.Comparison,Vector,VectorMask)
2298 */
2299 @ForceInline
2300 public final VectorMask<$Boxtype$> compare(VectorOperators.Comparison op,
2301 $type$ e,
2302 VectorMask<$Boxtype$> m) {
2303 return compare(op, broadcast(e), m);
2304 }
2305
2306 #if[!long]
2307 /**
2308 * {@inheritDoc} <!--workaround-->
2309 */
2310 @Override
2311 public abstract
2312 VectorMask<$Boxtype$> compare(Comparison op, long e);
2313
2314 /*package-private*/
2315 @ForceInline
2316 final
2317 <M extends VectorMask<$Boxtype$>>
2318 M compareTemplate(Class<M> maskType, Comparison op, long e) {
2319 return compareTemplate(maskType, op, broadcast(e));
2320 }
2321
2322 /**
2323 * {@inheritDoc} <!--workaround-->
2324 */
2325 @Override
2326 @ForceInline
2327 public final
2328 VectorMask<$Boxtype$> compare(Comparison op, long e, VectorMask<$Boxtype$> m) {
2329 return compare(op, broadcast(e), m);
2330 }
2331
2332
2333 #end[!long]
2334
2335 /**
2336 * {@inheritDoc} <!--workaround-->
2337 */
2338 @Override public abstract
2339 $abstractvectortype$ blend(Vector<$Boxtype$> v, VectorMask<$Boxtype$> m);
2340
2341 /*package-private*/
2342 @ForceInline
2343 final
2344 <M extends VectorMask<$Boxtype$>>
2345 $abstractvectortype$
2346 blendTemplate(Class<M> maskType, $abstractvectortype$ v, M m) {
2347 v.check(this);
2348 return VectorSupport.blend(
2349 getClass(), maskType, $type$.class, length(),
2350 this, v, m,
2351 (v0, v1, m_) -> v0.bOp(v1, m_, (i, a, b) -> b));
2352 }
2353
2354 /**
2355 * {@inheritDoc} <!--workaround-->
2356 */
2357 @Override public abstract $abstractvectortype$ addIndex(int scale);
2358
2359 /*package-private*/
2360 @ForceInline
2361 final $abstractvectortype$ addIndexTemplate(int scale) {
2362 $Type$Species vsp = vspecies();
2363 // make sure VLENGTH*scale doesn't overflow:
2364 vsp.checkScale(scale);
2365 return VectorSupport.indexVector(
2366 getClass(), $type$.class, length(),
2367 this, scale, vsp,
2368 (v, scale_, s)
2369 -> {
2370 // If the platform doesn't support an INDEX
2371 // instruction directly, load IOTA from memory
2372 // and multiply.
2373 $abstractvectortype$ iota = s.iota();
2374 $type$ sc = ($type$) scale_;
2375 return v.add(sc == 1 ? iota : iota.mul(sc));
2376 });
2377 }
2378
2379 /**
2380 * Replaces selected lanes of this vector with
2381 * a scalar value
2382 * under the control of a mask.
2383 *
2384 * This is a masked lane-wise binary operation which
2385 * selects each lane value from one or the other input.
2386 *
2387 * The returned result is equal to the expression
2388 * {@code blend(broadcast(e),m)}.
2389 *
2390 * @param e the input scalar, containing the replacement lane value
2391 * @param m the mask controlling lane selection of the scalar
2392 * @return the result of blending the lane elements of this vector with
2393 * the scalar value
2394 */
2395 @ForceInline
2396 public final $abstractvectortype$ blend($type$ e,
2397 VectorMask<$Boxtype$> m) {
2398 return blend(broadcast(e), m);
2399 }
2400
2401 #if[!long]
2402 /**
2403 * Replaces selected lanes of this vector with
2404 * a scalar value
2405 * under the control of a mask.
2406 *
2407 * This is a masked lane-wise binary operation which
2408 * selects each lane value from one or the other input.
2409 *
2410 * The returned result is equal to the expression
2411 * {@code blend(broadcast(e),m)}.
2412 *
2413 * @param e the input scalar, containing the replacement lane value
2414 * @param m the mask controlling lane selection of the scalar
2415 * @return the result of blending the lane elements of this vector with
2416 * the scalar value
2417 */
2418 @ForceInline
2419 public final $abstractvectortype$ blend(long e,
2420 VectorMask<$Boxtype$> m) {
2421 return blend(broadcast(e), m);
2422 }
2423 #end[!long]
2424
2425 /**
2426 * {@inheritDoc} <!--workaround-->
2427 */
2428 @Override
2429 public abstract
2430 $abstractvectortype$ slice(int origin, Vector<$Boxtype$> v1);
2431
2432 /*package-private*/
2433 final
2434 @ForceInline
2435 $abstractvectortype$ sliceTemplate(int origin, Vector<$Boxtype$> v1) {
2436 $abstractvectortype$ that = ($abstractvectortype$) v1;
2437 that.check(this);
2438 Objects.checkIndex(origin, length() + 1);
2439 VectorShuffle<$Boxtype$> iota = iotaShuffle();
2440 VectorMask<$Boxtype$> blendMask = iota.toVector().compare(VectorOperators.LT, (broadcast(($type$)(length() - origin))));
2441 iota = iotaShuffle(origin, 1, true);
2442 return that.rearrange(iota).blend(this.rearrange(iota), blendMask);
2443 }
2444
2445 /**
2446 * {@inheritDoc} <!--workaround-->
2447 */
2448 @Override
2449 @ForceInline
2450 public final
2451 $abstractvectortype$ slice(int origin,
2452 Vector<$Boxtype$> w,
2453 VectorMask<$Boxtype$> m) {
2454 return broadcast(0).blend(slice(origin, w), m);
2455 }
2456
2457 /**
2458 * {@inheritDoc} <!--workaround-->
2459 */
2460 @Override
2461 public abstract
2462 $abstractvectortype$ slice(int origin);
2463
2464 /*package-private*/
2465 final
2466 @ForceInline
2467 $abstractvectortype$ sliceTemplate(int origin) {
2468 Objects.checkIndex(origin, length() + 1);
2469 VectorShuffle<$Boxtype$> iota = iotaShuffle();
2470 VectorMask<$Boxtype$> blendMask = iota.toVector().compare(VectorOperators.LT, (broadcast(($type$)(length() - origin))));
2471 iota = iotaShuffle(origin, 1, true);
2472 return vspecies().zero().blend(this.rearrange(iota), blendMask);
2473 }
2474
2475 /**
2476 * {@inheritDoc} <!--workaround-->
2477 */
2478 @Override
2479 public abstract
2480 $abstractvectortype$ unslice(int origin, Vector<$Boxtype$> w, int part);
2481
2482 /*package-private*/
2483 final
2484 @ForceInline
2485 $abstractvectortype$
2486 unsliceTemplate(int origin, Vector<$Boxtype$> w, int part) {
2487 $abstractvectortype$ that = ($abstractvectortype$) w;
2488 that.check(this);
2489 Objects.checkIndex(origin, length() + 1);
2490 VectorShuffle<$Boxtype$> iota = iotaShuffle();
2491 VectorMask<$Boxtype$> blendMask = iota.toVector().compare((part == 0) ? VectorOperators.GE : VectorOperators.LT,
2492 (broadcast(($type$)(origin))));
2493 iota = iotaShuffle(-origin, 1, true);
2494 return that.blend(this.rearrange(iota), blendMask);
2495 }
2496
2497 /*package-private*/
2498 final
2499 @ForceInline
2500 <M extends VectorMask<$Boxtype$>>
2501 $abstractvectortype$
2502 unsliceTemplate(Class<M> maskType, int origin, Vector<$Boxtype$> w, int part, M m) {
2503 $abstractvectortype$ that = ($abstractvectortype$) w;
2504 that.check(this);
2505 $abstractvectortype$ slice = that.sliceTemplate(origin, that);
2506 slice = slice.blendTemplate(maskType, this, m);
2507 return slice.unsliceTemplate(origin, w, part);
2508 }
2509
2510 /**
2511 * {@inheritDoc} <!--workaround-->
2512 */
2513 @Override
2514 public abstract
2515 $abstractvectortype$ unslice(int origin, Vector<$Boxtype$> w, int part, VectorMask<$Boxtype$> m);
2516
2517 /**
2518 * {@inheritDoc} <!--workaround-->
2519 */
2520 @Override
2521 public abstract
2522 $abstractvectortype$ unslice(int origin);
2523
2524 /*package-private*/
2525 final
2526 @ForceInline
2527 $abstractvectortype$
2528 unsliceTemplate(int origin) {
2529 Objects.checkIndex(origin, length() + 1);
2530 VectorShuffle<$Boxtype$> iota = iotaShuffle();
2531 VectorMask<$Boxtype$> blendMask = iota.toVector().compare(VectorOperators.GE,
2532 (broadcast(($type$)(origin))));
2533 iota = iotaShuffle(-origin, 1, true);
2534 return vspecies().zero().blend(this.rearrange(iota), blendMask);
2535 }
2536
2537 private ArrayIndexOutOfBoundsException
2538 wrongPartForSlice(int part) {
2539 String msg = String.format("bad part number %d for slice operation",
2540 part);
2541 return new ArrayIndexOutOfBoundsException(msg);
2542 }
2543
2544 /**
2545 * {@inheritDoc} <!--workaround-->
2546 */
2547 @Override
2548 public abstract
2549 $abstractvectortype$ rearrange(VectorShuffle<$Boxtype$> m);
2550
2551 /*package-private*/
2552 @ForceInline
2553 final
2554 <S extends VectorShuffle<$Boxtype$>>
2555 $abstractvectortype$ rearrangeTemplate(Class<S> shuffletype, S shuffle) {
2556 shuffle.checkIndexes();
2557 return VectorSupport.rearrangeOp(
2558 getClass(), shuffletype, null, $type$.class, length(),
2559 this, shuffle, null,
2560 (v1, s_, m_) -> v1.uOp((i, a) -> {
2561 int ei = s_.laneSource(i);
2562 return v1.lane(ei);
2563 }));
2564 }
2565
2566 /**
2567 * {@inheritDoc} <!--workaround-->
2568 */
2569 @Override
2570 public abstract
2571 $abstractvectortype$ rearrange(VectorShuffle<$Boxtype$> s,
2572 VectorMask<$Boxtype$> m);
2573
2574 /*package-private*/
2575 @ForceInline
2576 final
2577 <S extends VectorShuffle<$Boxtype$>, M extends VectorMask<$Boxtype$>>
2578 $abstractvectortype$ rearrangeTemplate(Class<S> shuffletype,
2579 Class<M> masktype,
2580 S shuffle,
2581 M m) {
2582
2583 m.check(masktype, this);
2584 VectorMask<$Boxtype$> valid = shuffle.laneIsValid();
2585 if (m.andNot(valid).anyTrue()) {
2586 shuffle.checkIndexes();
2587 throw new AssertionError();
2588 }
2589 return VectorSupport.rearrangeOp(
2590 getClass(), shuffletype, masktype, $type$.class, length(),
2591 this, shuffle, m,
2592 (v1, s_, m_) -> v1.uOp((i, a) -> {
2593 int ei = s_.laneSource(i);
2594 return ei < 0 || !m_.laneIsSet(i) ? 0 : v1.lane(ei);
2595 }));
2596 }
2597
2598 /**
2599 * {@inheritDoc} <!--workaround-->
2600 */
2601 @Override
2602 public abstract
2603 $abstractvectortype$ rearrange(VectorShuffle<$Boxtype$> s,
2604 Vector<$Boxtype$> v);
2605
2606 /*package-private*/
2607 @ForceInline
2608 final
2609 <S extends VectorShuffle<$Boxtype$>>
2610 $abstractvectortype$ rearrangeTemplate(Class<S> shuffletype,
2611 S shuffle,
2612 $abstractvectortype$ v) {
2613 VectorMask<$Boxtype$> valid = shuffle.laneIsValid();
2614 @SuppressWarnings("unchecked")
2615 S ws = (S) shuffle.wrapIndexes();
2616 $abstractvectortype$ r0 =
2617 VectorSupport.rearrangeOp(
2618 getClass(), shuffletype, null, $type$.class, length(),
2619 this, ws, null,
2620 (v0, s_, m_) -> v0.uOp((i, a) -> {
2621 int ei = s_.laneSource(i);
2622 return v0.lane(ei);
2623 }));
2624 $abstractvectortype$ r1 =
2625 VectorSupport.rearrangeOp(
2626 getClass(), shuffletype, null, $type$.class, length(),
2627 v, ws, null,
2628 (v1, s_, m_) -> v1.uOp((i, a) -> {
2629 int ei = s_.laneSource(i);
2630 return v1.lane(ei);
2631 }));
2632 return r1.blend(r0, valid);
2633 }
2634
2635 @ForceInline
2636 private final
2637 VectorShuffle<$Boxtype$> toShuffle0($Type$Species dsp) {
2638 $type$[] a = toArray();
2639 int[] sa = new int[a.length];
2640 for (int i = 0; i < a.length; i++) {
2641 sa[i] = (int) a[i];
2642 }
2643 return VectorShuffle.fromArray(dsp, sa, 0);
2644 }
2645
2646 /*package-private*/
2647 @ForceInline
2648 final
2649 VectorShuffle<$Boxtype$> toShuffleTemplate(Class<?> shuffleType) {
2650 $Type$Species vsp = vspecies();
2651 return VectorSupport.convert(VectorSupport.VECTOR_OP_CAST,
2652 getClass(), $type$.class, length(),
2653 shuffleType, byte.class, length(),
2654 this, vsp,
2655 $Type$Vector::toShuffle0);
2656 }
2657
2658 /**
2659 * {@inheritDoc} <!--workaround-->
2660 */
2661 @Override
2662 public abstract
2663 $abstractvectortype$ selectFrom(Vector<$Boxtype$> v);
2664
2665 /*package-private*/
2666 @ForceInline
2667 final $abstractvectortype$ selectFromTemplate($abstractvectortype$ v) {
2668 return v.rearrange(this.toShuffle());
2669 }
2670
2671 /**
2672 * {@inheritDoc} <!--workaround-->
2673 */
2674 @Override
2675 public abstract
2676 $abstractvectortype$ selectFrom(Vector<$Boxtype$> s, VectorMask<$Boxtype$> m);
2677
2678 /*package-private*/
2679 @ForceInline
2680 final $abstractvectortype$ selectFromTemplate($abstractvectortype$ v,
2681 AbstractMask<$Boxtype$> m) {
2682 return v.rearrange(this.toShuffle(), m);
2683 }
2684
2685 /// Ternary operations
2686
2687 #if[BITWISE]
2688 /**
2689 * Blends together the bits of two vectors under
2690 * the control of a third, which supplies mask bits.
2691 *
2692 * This is a lane-wise ternary operation which performs
2693 * a bitwise blending operation {@code (a&~c)|(b&c)}
2694 * to each lane.
2695 *
2696 * This method is also equivalent to the expression
2697 * {@link #lanewise(VectorOperators.Ternary,Vector,Vector)
2698 * lanewise}{@code (}{@link VectorOperators#BITWISE_BLEND
2699 * BITWISE_BLEND}{@code , bits, mask)}.
2700 *
2701 * @param bits input bits to blend into the current vector
2702 * @param mask a bitwise mask to enable blending of the input bits
2703 * @return the bitwise blend of the given bits into the current vector,
2704 * under control of the bitwise mask
2705 * @see #bitwiseBlend($type$,$type$)
2706 * @see #bitwiseBlend($type$,Vector)
2707 * @see #bitwiseBlend(Vector,$type$)
2708 * @see VectorOperators#BITWISE_BLEND
2709 * @see #lanewise(VectorOperators.Ternary,Vector,Vector,VectorMask)
2710 */
2711 @ForceInline
2712 public final
2713 $abstractvectortype$ bitwiseBlend(Vector<$Boxtype$> bits, Vector<$Boxtype$> mask) {
2714 return lanewise(BITWISE_BLEND, bits, mask);
2715 }
2716
2717 /**
2718 * Blends together the bits of a vector and a scalar under
2719 * the control of another scalar, which supplies mask bits.
2720 *
2721 * This is a lane-wise ternary operation which performs
2722 * a bitwise blending operation {@code (a&~c)|(b&c)}
2723 * to each lane.
2724 *
2725 * This method is also equivalent to the expression
2726 * {@link #lanewise(VectorOperators.Ternary,Vector,Vector)
2727 * lanewise}{@code (}{@link VectorOperators#BITWISE_BLEND
2728 * BITWISE_BLEND}{@code , bits, mask)}.
2729 *
2730 * @param bits input bits to blend into the current vector
2731 * @param mask a bitwise mask to enable blending of the input bits
2732 * @return the bitwise blend of the given bits into the current vector,
2733 * under control of the bitwise mask
2734 * @see #bitwiseBlend(Vector,Vector)
2735 * @see VectorOperators#BITWISE_BLEND
2736 * @see #lanewise(VectorOperators.Ternary,$type$,$type$,VectorMask)
2737 */
2738 @ForceInline
2739 public final
2740 $abstractvectortype$ bitwiseBlend($type$ bits, $type$ mask) {
2741 return lanewise(BITWISE_BLEND, bits, mask);
2742 }
2743
2744 /**
2745 * Blends together the bits of a vector and a scalar under
2746 * the control of another vector, which supplies mask bits.
2747 *
2748 * This is a lane-wise ternary operation which performs
2749 * a bitwise blending operation {@code (a&~c)|(b&c)}
2750 * to each lane.
2751 *
2752 * This method is also equivalent to the expression
2753 * {@link #lanewise(VectorOperators.Ternary,Vector,Vector)
2754 * lanewise}{@code (}{@link VectorOperators#BITWISE_BLEND
2755 * BITWISE_BLEND}{@code , bits, mask)}.
2756 *
2757 * @param bits input bits to blend into the current vector
2758 * @param mask a bitwise mask to enable blending of the input bits
2759 * @return the bitwise blend of the given bits into the current vector,
2760 * under control of the bitwise mask
2761 * @see #bitwiseBlend(Vector,Vector)
2762 * @see VectorOperators#BITWISE_BLEND
2763 * @see #lanewise(VectorOperators.Ternary,$type$,Vector,VectorMask)
2764 */
2765 @ForceInline
2766 public final
2767 $abstractvectortype$ bitwiseBlend($type$ bits, Vector<$Boxtype$> mask) {
2768 return lanewise(BITWISE_BLEND, bits, mask);
2769 }
2770
2771 /**
2772 * Blends together the bits of two vectors under
2773 * the control of a scalar, which supplies mask bits.
2774 *
2775 * This is a lane-wise ternary operation which performs
2776 * a bitwise blending operation {@code (a&~c)|(b&c)}
2777 * to each lane.
2778 *
2779 * This method is also equivalent to the expression
2780 * {@link #lanewise(VectorOperators.Ternary,Vector,Vector)
2781 * lanewise}{@code (}{@link VectorOperators#BITWISE_BLEND
2782 * BITWISE_BLEND}{@code , bits, mask)}.
2783 *
2784 * @param bits input bits to blend into the current vector
2785 * @param mask a bitwise mask to enable blending of the input bits
2786 * @return the bitwise blend of the given bits into the current vector,
2787 * under control of the bitwise mask
2788 * @see #bitwiseBlend(Vector,Vector)
2789 * @see VectorOperators#BITWISE_BLEND
2790 * @see #lanewise(VectorOperators.Ternary,Vector,$type$,VectorMask)
2791 */
2792 @ForceInline
2793 public final
2794 $abstractvectortype$ bitwiseBlend(Vector<$Boxtype$> bits, $type$ mask) {
2795 return lanewise(BITWISE_BLEND, bits, mask);
2796 }
2797 #end[BITWISE]
2798
2799 #if[FP]
2800 /**
2801 * Multiplies this vector by a second input vector, and sums
2802 * the result with a third.
2803 *
2804 * Extended precision is used for the intermediate result,
2805 * avoiding possible loss of precision from rounding once
2806 * for each of the two operations.
2807 * The result is numerically close to {@code this.mul(b).add(c)},
2808 * and is typically closer to the true mathematical result.
2809 *
2810 * This is a lane-wise ternary operation which applies an operation
2811 * conforming to the specification of
2812 * {@link Math#fma($type$,$type$,$type$) Math.fma(a,b,c)}
2813 * to each lane.
2814 #if[intOrFloat]
2815 * The operation is adapted to cast the operands and the result,
2816 * specifically widening {@code float} operands to {@code double}
2817 * operands and narrowing the {@code double} result to a {@code float}
2818 * result.
2819 #end[intOrFloat]
2820 *
2821 * This method is also equivalent to the expression
2822 * {@link #lanewise(VectorOperators.Ternary,Vector,Vector)
2823 * lanewise}{@code (}{@link VectorOperators#FMA
2824 * FMA}{@code , b, c)}.
2825 *
2826 * @param b the second input vector, supplying multiplier values
2827 * @param c the third input vector, supplying addend values
2828 * @return the product of this vector and the second input vector
2829 * summed with the third input vector, using extended precision
2830 * for the intermediate result
2831 * @see #fma($type$,$type$)
2832 * @see VectorOperators#FMA
2833 * @see #lanewise(VectorOperators.Ternary,Vector,Vector,VectorMask)
2834 */
2835 @ForceInline
2836 public final
2837 $abstractvectortype$ fma(Vector<$Boxtype$> b, Vector<$Boxtype$> c) {
2838 return lanewise(FMA, b, c);
2839 }
2840
2841 /**
2842 * Multiplies this vector by a scalar multiplier, and sums
2843 * the result with a scalar addend.
2844 *
2845 * Extended precision is used for the intermediate result,
2846 * avoiding possible loss of precision from rounding once
2847 * for each of the two operations.
2848 * The result is numerically close to {@code this.mul(b).add(c)},
2849 * and is typically closer to the true mathematical result.
2850 *
2851 * This is a lane-wise ternary operation which applies an operation
2852 * conforming to the specification of
2853 * {@link Math#fma($type$,$type$,$type$) Math.fma(a,b,c)}
2854 * to each lane.
2855 #if[intOrFloat]
2856 * The operation is adapted to cast the operands and the result,
2857 * specifically widening {@code float} operands to {@code double}
2858 * operands and narrowing the {@code double} result to a {@code float}
2859 * result.
2860 #end[intOrFloat]
2861 *
2862 * This method is also equivalent to the expression
2863 * {@link #lanewise(VectorOperators.Ternary,Vector,Vector)
2864 * lanewise}{@code (}{@link VectorOperators#FMA
2865 * FMA}{@code , b, c)}.
2866 *
2867 * @param b the scalar multiplier
2868 * @param c the scalar addend
2869 * @return the product of this vector and the scalar multiplier
2870 * summed with scalar addend, using extended precision
2871 * for the intermediate result
2872 * @see #fma(Vector,Vector)
2873 * @see VectorOperators#FMA
2874 * @see #lanewise(VectorOperators.Ternary,$type$,$type$,VectorMask)
2875 */
2876 @ForceInline
2877 public final
2878 $abstractvectortype$ fma($type$ b, $type$ c) {
2879 return lanewise(FMA, b, c);
2880 }
2881
2882 // Don't bother with (Vector,$type$) and ($type$,Vector) overloadings.
2883 #end[FP]
2884
2885 // Type specific horizontal reductions
2886
2887 /**
2888 * Returns a value accumulated from all the lanes of this vector.
2889 *
2890 * This is an associative cross-lane reduction operation which
2891 * applies the specified operation to all the lane elements.
2892 * <p>
2893 * A few reduction operations do not support arbitrary reordering
2894 * of their operands, yet are included here because of their
2895 * usefulness.
2896 * <ul>
2897 * <li>
2898 * In the case of {@code FIRST_NONZERO}, the reduction returns
2899 * the value from the lowest-numbered non-zero lane.
2900 #if[FP]
2901 * (As with {@code MAX} and {@code MIN}, floating point negative
2902 * zero {@code -0.0} is treated as a value distinct from
2903 * the default value, positive zero. So a first-nonzero lane reduction
2904 * might return {@code -0.0} even in the presence of non-zero
2905 * lane values.)
2906 * <li>
2907 * In the case of {@code ADD} and {@code MUL}, the
2908 * precise result will reflect the choice of an arbitrary order
2909 * of operations, which may even vary over time.
2910 * For further details see the section
2911 * <a href="VectorOperators.html#fp_assoc">Operations on floating point vectors</a>.
2912 #end[FP]
2913 * <li>
2914 * All other reduction operations are fully commutative and
2915 * associative. The implementation can choose any order of
2916 * processing, yet it will always produce the same result.
2917 * </ul>
2918 *
2919 * @param op the operation used to combine lane values
2920 * @return the accumulated result
2921 * @throws UnsupportedOperationException if this vector does
2922 * not support the requested operation
2923 * @see #reduceLanes(VectorOperators.Associative,VectorMask)
2924 * @see #add(Vector)
2925 * @see #mul(Vector)
2926 * @see #min(Vector)
2927 * @see #max(Vector)
2928 #if[BITWISE]
2929 * @see #and(Vector)
2930 * @see #or(Vector)
2931 * @see VectorOperators#XOR
2932 #end[BITWISE]
2933 * @see VectorOperators#FIRST_NONZERO
2934 */
2935 public abstract $type$ reduceLanes(VectorOperators.Associative op);
2936
2937 /**
2938 * Returns a value accumulated from selected lanes of this vector,
2939 * controlled by a mask.
2940 *
2941 * This is an associative cross-lane reduction operation which
2942 * applies the specified operation to the selected lane elements.
2943 * <p>
2944 * If no elements are selected, an operation-specific identity
2945 * value is returned.
2946 * <ul>
2947 * <li>
2948 * If the operation is
2949 #if[BITWISE]
2950 * {@code ADD}, {@code XOR}, {@code OR},
2951 #else[BITWISE]
2952 * {@code ADD}
2953 #end[BITWISE]
2954 * or {@code FIRST_NONZERO},
2955 * then the identity value is {#if[FP]?positive }zero, the default {@code $type$} value.
2956 * <li>
2957 * If the operation is {@code MUL},
2958 * then the identity value is one.
2959 #if[BITWISE]
2960 * <li>
2961 * If the operation is {@code AND},
2962 * then the identity value is minus one (all bits set).
2963 * <li>
2964 * If the operation is {@code MAX},
2965 * then the identity value is {@code $Boxtype$.MIN_VALUE}.
2966 * <li>
2967 * If the operation is {@code MIN},
2968 * then the identity value is {@code $Boxtype$.MAX_VALUE}.
2969 #end[BITWISE]
2970 #if[FP]
2971 * <li>
2972 * If the operation is {@code MAX},
2973 * then the identity value is {@code $Boxtype$.NEGATIVE_INFINITY}.
2974 * <li>
2975 * If the operation is {@code MIN},
2976 * then the identity value is {@code $Boxtype$.POSITIVE_INFINITY}.
2977 #end[FP]
2978 * </ul>
2979 * <p>
2980 * A few reduction operations do not support arbitrary reordering
2981 * of their operands, yet are included here because of their
2982 * usefulness.
2983 * <ul>
2984 * <li>
2985 * In the case of {@code FIRST_NONZERO}, the reduction returns
2986 * the value from the lowest-numbered non-zero lane.
2987 #if[FP]
2988 * (As with {@code MAX} and {@code MIN}, floating point negative
2989 * zero {@code -0.0} is treated as a value distinct from
2990 * the default value, positive zero. So a first-nonzero lane reduction
2991 * might return {@code -0.0} even in the presence of non-zero
2992 * lane values.)
2993 * <li>
2994 * In the case of {@code ADD} and {@code MUL}, the
2995 * precise result will reflect the choice of an arbitrary order
2996 * of operations, which may even vary over time.
2997 * For further details see the section
2998 * <a href="VectorOperators.html#fp_assoc">Operations on floating point vectors</a>.
2999 #end[FP]
3000 * <li>
3001 * All other reduction operations are fully commutative and
3002 * associative. The implementation can choose any order of
3003 * processing, yet it will always produce the same result.
3004 * </ul>
3005 *
3006 * @param op the operation used to combine lane values
3007 * @param m the mask controlling lane selection
3008 * @return the reduced result accumulated from the selected lane values
3009 * @throws UnsupportedOperationException if this vector does
3010 * not support the requested operation
3011 * @see #reduceLanes(VectorOperators.Associative)
3012 */
3013 public abstract $type$ reduceLanes(VectorOperators.Associative op,
3014 VectorMask<$Boxtype$> m);
3015
3016 /*package-private*/
3017 @ForceInline
3018 final
3019 $type$ reduceLanesTemplate(VectorOperators.Associative op,
3020 Class<? extends VectorMask<$Boxtype$>> maskClass,
3021 VectorMask<$Boxtype$> m) {
3022 m.check(maskClass, this);
3023 if (op == FIRST_NONZERO) {
3024 $abstractvectortype$ v = reduceIdentityVector(op).blend(this, m);
3025 return v.reduceLanesTemplate(op);
3026 }
3027 int opc = opCode(op);
3028 return fromBits(VectorSupport.reductionCoerced(
3029 opc, getClass(), maskClass, $type$.class, length(),
3030 this, m,
3031 REDUCE_IMPL.find(op, opc, $abstractvectortype$::reductionOperations)));
3032 }
3033
3034 /*package-private*/
3035 @ForceInline
3036 final
3037 $type$ reduceLanesTemplate(VectorOperators.Associative op) {
3038 if (op == FIRST_NONZERO) {
3039 // FIXME: The JIT should handle this, and other scan ops alos.
3040 VectorMask<$Boxbitstype$> thisNZ
3041 = this.viewAsIntegralLanes().compare(NE, ($bitstype$) 0);
3042 return this.lane(thisNZ.firstTrue());
3043 }
3044 int opc = opCode(op);
3045 return fromBits(VectorSupport.reductionCoerced(
3046 opc, getClass(), null, $type$.class, length(),
3047 this, null,
3048 REDUCE_IMPL.find(op, opc, $abstractvectortype$::reductionOperations)));
3049 }
3050
3051 private static final
3052 ImplCache<Associative, ReductionOperation<$abstractvectortype$, VectorMask<$Boxtype$>>>
3053 REDUCE_IMPL = new ImplCache<>(Associative.class, $Type$Vector.class);
3054
3055 private static ReductionOperation<$abstractvectortype$, VectorMask<$Boxtype$>> reductionOperations(int opc_) {
3056 switch (opc_) {
3057 case VECTOR_OP_ADD: return (v, m) ->
3058 toBits(v.rOp(($type$)0, m, (i, a, b) -> ($type$)(a + b)));
3059 case VECTOR_OP_MUL: return (v, m) ->
3060 toBits(v.rOp(($type$)1, m, (i, a, b) -> ($type$)(a * b)));
3061 case VECTOR_OP_MIN: return (v, m) ->
3062 toBits(v.rOp(MAX_OR_INF, m, (i, a, b) -> ($type$) Math.min(a, b)));
3063 case VECTOR_OP_MAX: return (v, m) ->
3064 toBits(v.rOp(MIN_OR_INF, m, (i, a, b) -> ($type$) Math.max(a, b)));
3065 #if[BITWISE]
3066 case VECTOR_OP_AND: return (v, m) ->
3067 toBits(v.rOp(($type$)-1, m, (i, a, b) -> ($type$)(a & b)));
3068 case VECTOR_OP_OR: return (v, m) ->
3069 toBits(v.rOp(($type$)0, m, (i, a, b) -> ($type$)(a | b)));
3070 case VECTOR_OP_XOR: return (v, m) ->
3071 toBits(v.rOp(($type$)0, m, (i, a, b) -> ($type$)(a ^ b)));
3072 #end[BITWISE]
3073 default: return null;
3074 }
3075 }
3076
3077 private
3078 @ForceInline
3079 $abstractvectortype$ reduceIdentityVector(VectorOperators.Associative op) {
3080 int opc = opCode(op);
3081 UnaryOperator<$abstractvectortype$> fn
3082 = REDUCE_ID_IMPL.find(op, opc, (opc_) -> {
3083 switch (opc_) {
3084 case VECTOR_OP_ADD:
3085 #if[BITWISE]
3086 case VECTOR_OP_OR:
3087 case VECTOR_OP_XOR:
3088 #end[BITWISE]
3089 return v -> v.broadcast(0);
3090 case VECTOR_OP_MUL:
3091 return v -> v.broadcast(1);
3092 #if[BITWISE]
3093 case VECTOR_OP_AND:
3094 return v -> v.broadcast(-1);
3095 #end[BITWISE]
3096 case VECTOR_OP_MIN:
3097 return v -> v.broadcast(MAX_OR_INF);
3098 case VECTOR_OP_MAX:
3099 return v -> v.broadcast(MIN_OR_INF);
3100 default: return null;
3101 }
3102 });
3103 return fn.apply(this);
3104 }
3105 private static final
3106 ImplCache<Associative,UnaryOperator<$abstractvectortype$>> REDUCE_ID_IMPL
3107 = new ImplCache<>(Associative.class, $Type$Vector.class);
3108
3109 #if[FP]
3110 private static final $type$ MIN_OR_INF = $Boxtype$.NEGATIVE_INFINITY;
3111 private static final $type$ MAX_OR_INF = $Boxtype$.POSITIVE_INFINITY;
3112 #else[FP]
3113 private static final $type$ MIN_OR_INF = $Boxtype$.MIN_VALUE;
3114 private static final $type$ MAX_OR_INF = $Boxtype$.MAX_VALUE;
3115 #end[FP]
3116
3117 public @Override abstract long reduceLanesToLong(VectorOperators.Associative op);
3118 public @Override abstract long reduceLanesToLong(VectorOperators.Associative op,
3119 VectorMask<$Boxtype$> m);
3120
3121 // Type specific accessors
3122
3123 /**
3124 * Gets the lane element at lane index {@code i}
3125 *
3126 * @param i the lane index
3127 * @return the lane element at lane index {@code i}
3128 * @throws IllegalArgumentException if the index is is out of range
3129 * ({@code < 0 || >= length()})
3130 */
3131 public abstract $type$ lane(int i);
3132
3133 /**
3134 * Replaces the lane element of this vector at lane index {@code i} with
3135 * value {@code e}.
3136 *
3137 * This is a cross-lane operation and behaves as if it returns the result
3138 * of blending this vector with an input vector that is the result of
3139 * broadcasting {@code e} and a mask that has only one lane set at lane
3140 * index {@code i}.
3141 *
3142 * @param i the lane index of the lane element to be replaced
3143 * @param e the value to be placed
3144 * @return the result of replacing the lane element of this vector at lane
3145 * index {@code i} with value {@code e}.
3146 * @throws IllegalArgumentException if the index is is out of range
3147 * ({@code < 0 || >= length()})
3148 */
3149 public abstract $abstractvectortype$ withLane(int i, $type$ e);
3150
3151 // Memory load operations
3152
3153 /**
3154 * Returns an array of type {@code $type$[]}
3155 * containing all the lane values.
3156 * The array length is the same as the vector length.
3157 * The array elements are stored in lane order.
3158 * <p>
3159 * This method behaves as if it stores
3160 * this vector into an allocated array
3161 * (using {@link #intoArray($type$[], int) intoArray})
3162 * and returns the array as follows:
3163 * <pre>{@code
3164 * $type$[] a = new $type$[this.length()];
3165 * this.intoArray(a, 0);
3166 * return a;
3167 * }</pre>
3168 *
3169 * @return an array containing the lane values of this vector
3170 */
3171 @ForceInline
3172 @Override
3173 public final $type$[] toArray() {
3174 $type$[] a = new $type$[vspecies().laneCount()];
3175 intoArray(a, 0);
3176 return a;
3177 }
3178
3179 #if[int]
3180 /**
3181 * {@inheritDoc} <!--workaround-->
3182 * This is an alias for {@link #toArray()}
3183 * When this method is used on used on vectors
3184 * of type {@code $abstractvectortype$},
3185 * there will be no loss of range or precision.
3186 */
3187 @ForceInline
3188 @Override
3189 public final int[] toIntArray() {
3190 return toArray();
3191 }
3192 #else[int]
3193 /** {@inheritDoc} <!--workaround-->
3194 #if[!FP]
3195 #if[!long]
3196 * @implNote
3197 * When this method is used on used on vectors
3198 * of type {@code $abstractvectortype$},
3199 * there will be no loss of precision or range,
3200 * and so no {@code UnsupportedOperationException} will
3201 * be thrown.
3202 #end[!long]
3203 #end[!FP]
3204 */
3205 @ForceInline
3206 @Override
3207 public final int[] toIntArray() {
3208 $type$[] a = toArray();
3209 int[] res = new int[a.length];
3210 for (int i = 0; i < a.length; i++) {
3211 $type$ e = a[i];
3212 res[i] = (int) $Type$Species.toIntegralChecked(e, true);
3213 }
3214 return res;
3215 }
3216 #end[int]
3217
3218 #if[long]
3219 /**
3220 * {@inheritDoc} <!--workaround-->
3221 * This is an alias for {@link #toArray()}
3222 * When this method is used on used on vectors
3223 * of type {@code $abstractvectortype$},
3224 * there will be no loss of range or precision.
3225 */
3226 @ForceInline
3227 @Override
3228 public final long[] toLongArray() {
3229 return toArray();
3230 }
3231 #else[long]
3232 /** {@inheritDoc} <!--workaround-->
3233 #if[!FP]
3234 * @implNote
3235 * When this method is used on used on vectors
3236 * of type {@code $abstractvectortype$},
3237 * there will be no loss of precision or range,
3238 * and so no {@code UnsupportedOperationException} will
3239 * be thrown.
3240 #end[!FP]
3241 */
3242 @ForceInline
3243 @Override
3244 public final long[] toLongArray() {
3245 $type$[] a = toArray();
3246 long[] res = new long[a.length];
3247 for (int i = 0; i < a.length; i++) {
3248 $type$ e = a[i];
3249 res[i] = $Type$Species.toIntegralChecked(e, false);
3250 }
3251 return res;
3252 }
3253 #end[long]
3254
3255 #if[double]
3256 /** {@inheritDoc} <!--workaround-->
3257 * @implNote
3258 * This is an alias for {@link #toArray()}
3259 * When this method is used on used on vectors
3260 * of type {@code $abstractvectortype$},
3261 * there will be no loss of precision.
3262 */
3263 @ForceInline
3264 @Override
3265 public final double[] toDoubleArray() {
3266 return toArray();
3267 }
3268 #else[double]
3269 /** {@inheritDoc} <!--workaround-->
3270 #if[long]
3271 * @implNote
3272 * When this method is used on used on vectors
3273 * of type {@code $abstractvectortype$},
3274 * up to nine bits of precision may be lost
3275 * for lane values of large magnitude.
3276 #else[long]
3277 * @implNote
3278 * When this method is used on used on vectors
3279 * of type {@code $abstractvectortype$},
3280 * there will be no loss of precision.
3281 #end[long]
3282 */
3283 @ForceInline
3284 @Override
3285 public final double[] toDoubleArray() {
3286 $type$[] a = toArray();
3287 double[] res = new double[a.length];
3288 for (int i = 0; i < a.length; i++) {
3289 res[i] = (double) a[i];
3290 }
3291 return res;
3292 }
3293 #end[double]
3294
3295 /**
3296 * Loads a vector from a byte array starting at an offset.
3297 * Bytes are composed into primitive lane elements according
3298 * to the specified byte order.
3299 * The vector is arranged into lanes according to
3300 * <a href="Vector.html#lane-order">memory ordering</a>.
3301 * <p>
3302 * This method behaves as if it returns the result of calling
3303 * {@link #fromByteBuffer(VectorSpecies,ByteBuffer,int,ByteOrder,VectorMask)
3304 * fromByteBuffer()} as follows:
3305 * <pre>{@code
3306 * var bb = ByteBuffer.wrap(a);
3307 * var m = species.maskAll(true);
3308 * return fromByteBuffer(species, bb, offset, bo, m);
3309 * }</pre>
3310 *
3311 * @param species species of desired vector
3312 * @param a the byte array
3313 * @param offset the offset into the array
3314 * @param bo the intended byte order
3315 * @return a vector loaded from a byte array
3316 * @throws IndexOutOfBoundsException
3317 * if {@code offset+N*ESIZE < 0}
3318 * or {@code offset+(N+1)*ESIZE > a.length}
3319 * for any lane {@code N} in the vector
3320 */
3321 @ForceInline
3322 public static
3323 $abstractvectortype$ fromByteArray(VectorSpecies<$Boxtype$> species,
3324 byte[] a, int offset,
3325 ByteOrder bo) {
3326 offset = checkFromIndexSize(offset, species.vectorByteSize(), a.length);
3327 $Type$Species vsp = ($Type$Species) species;
3328 return vsp.dummyVector().fromByteArray0(a, offset).maybeSwap(bo);
3329 }
3330
3331 /**
3332 * Loads a vector from a byte array starting at an offset
3333 * and using a mask.
3334 * Lanes where the mask is unset are filled with the default
3335 * value of {@code $type$} ({#if[FP]?positive }zero).
3336 * Bytes are composed into primitive lane elements according
3337 * to the specified byte order.
3338 * The vector is arranged into lanes according to
3339 * <a href="Vector.html#lane-order">memory ordering</a>.
3340 * <p>
3341 * This method behaves as if it returns the result of calling
3342 * {@link #fromByteBuffer(VectorSpecies,ByteBuffer,int,ByteOrder,VectorMask)
3343 * fromByteBuffer()} as follows:
3344 * <pre>{@code
3345 * var bb = ByteBuffer.wrap(a);
3346 * return fromByteBuffer(species, bb, offset, bo, m);
3347 * }</pre>
3348 *
3349 * @param species species of desired vector
3350 * @param a the byte array
3351 * @param offset the offset into the array
3352 * @param bo the intended byte order
3353 * @param m the mask controlling lane selection
3354 * @return a vector loaded from a byte array
3355 * @throws IndexOutOfBoundsException
3356 * if {@code offset+N*ESIZE < 0}
3357 * or {@code offset+(N+1)*ESIZE > a.length}
3358 * for any lane {@code N} in the vector
3359 * where the mask is set
3360 */
3361 @ForceInline
3362 public static
3363 $abstractvectortype$ fromByteArray(VectorSpecies<$Boxtype$> species,
3364 byte[] a, int offset,
3365 ByteOrder bo,
3366 VectorMask<$Boxtype$> m) {
3367 $Type$Species vsp = ($Type$Species) species;
3368 if (offset >= 0 && offset <= (a.length - species.vectorByteSize())) {
3369 return vsp.dummyVector().fromByteArray0(a, offset, m).maybeSwap(bo);
3370 }
3371
3372 // FIXME: optimize
3373 checkMaskFromIndexSize(offset, vsp, m, $sizeInBytes$, a.length);
3374 ByteBuffer wb = wrapper(a, bo);
3375 return vsp.ldOp(wb, offset, (AbstractMask<$Boxtype$>)m,
3376 (wb_, o, i) -> wb_.get{#if[byte]?(:$Type$(}o + i * $sizeInBytes$));
3377 }
3378
3379 /**
3380 * Loads a vector from an array of type {@code $type$[]}
3381 * starting at an offset.
3382 * For each vector lane, where {@code N} is the vector lane index, the
3383 * array element at index {@code offset + N} is placed into the
3384 * resulting vector at lane index {@code N}.
3385 *
3386 * @param species species of desired vector
3387 * @param a the array
3388 * @param offset the offset into the array
3389 * @return the vector loaded from an array
3390 * @throws IndexOutOfBoundsException
3391 * if {@code offset+N < 0} or {@code offset+N >= a.length}
3392 * for any lane {@code N} in the vector
3393 */
3394 @ForceInline
3395 public static
3396 $abstractvectortype$ fromArray(VectorSpecies<$Boxtype$> species,
3397 $type$[] a, int offset) {
3398 offset = checkFromIndexSize(offset, species.length(), a.length);
3399 $Type$Species vsp = ($Type$Species) species;
3400 return vsp.dummyVector().fromArray0(a, offset);
3401 }
3402
3403 /**
3404 * Loads a vector from an array of type {@code $type$[]}
3405 * starting at an offset and using a mask.
3406 * Lanes where the mask is unset are filled with the default
3407 * value of {@code $type$} ({#if[FP]?positive }zero).
3408 * For each vector lane, where {@code N} is the vector lane index,
3409 * if the mask lane at index {@code N} is set then the array element at
3410 * index {@code offset + N} is placed into the resulting vector at lane index
3411 * {@code N}, otherwise the default element value is placed into the
3412 * resulting vector at lane index {@code N}.
3413 *
3414 * @param species species of desired vector
3415 * @param a the array
3416 * @param offset the offset into the array
3417 * @param m the mask controlling lane selection
3418 * @return the vector loaded from an array
3419 * @throws IndexOutOfBoundsException
3420 * if {@code offset+N < 0} or {@code offset+N >= a.length}
3421 * for any lane {@code N} in the vector
3422 * where the mask is set
3423 */
3424 @ForceInline
3425 public static
3426 $abstractvectortype$ fromArray(VectorSpecies<$Boxtype$> species,
3427 $type$[] a, int offset,
3428 VectorMask<$Boxtype$> m) {
3429 $Type$Species vsp = ($Type$Species) species;
3430 if (offset >= 0 && offset <= (a.length - species.length())) {
3431 return vsp.dummyVector().fromArray0(a, offset, m);
3432 }
3433
3434 // FIXME: optimize
3435 checkMaskFromIndexSize(offset, vsp, m, 1, a.length);
3436 return vsp.vOp(m, i -> a[offset + i]);
3437 }
3438
3439 /**
3440 * Gathers a new vector composed of elements from an array of type
3441 * {@code $type$[]},
3442 * using indexes obtained by adding a fixed {@code offset} to a
3443 * series of secondary offsets from an <em>index map</em>.
3444 * The index map is a contiguous sequence of {@code VLENGTH}
3445 * elements in a second array of {@code int}s, starting at a given
3446 * {@code mapOffset}.
3447 * <p>
3448 * For each vector lane, where {@code N} is the vector lane index,
3449 * the lane is loaded from the array
3450 * element {@code a[f(N)]}, where {@code f(N)} is the
3451 * index mapping expression
3452 * {@code offset + indexMap[mapOffset + N]]}.
3453 *
3454 * @param species species of desired vector
3455 * @param a the array
3456 * @param offset the offset into the array, may be negative if relative
3457 * indexes in the index map compensate to produce a value within the
3458 * array bounds
3459 * @param indexMap the index map
3460 * @param mapOffset the offset into the index map
3461 * @return the vector loaded from the indexed elements of the array
3462 * @throws IndexOutOfBoundsException
3463 * if {@code mapOffset+N < 0}
3464 * or if {@code mapOffset+N >= indexMap.length},
3465 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
3466 * is an invalid index into {@code a},
3467 * for any lane {@code N} in the vector
3468 * @see $abstractvectortype$#toIntArray()
3469 */
3470 #if[byteOrShort]
3471 @ForceInline
3472 public static
3473 $abstractvectortype$ fromArray(VectorSpecies<$Boxtype$> species,
3474 $type$[] a, int offset,
3475 int[] indexMap, int mapOffset) {
3476 $Type$Species vsp = ($Type$Species) species;
3477 return vsp.vOp(n -> a[offset + indexMap[mapOffset + n]]);
3478 }
3479 #else[byteOrShort]
3480 @ForceInline
3481 public static
3482 $abstractvectortype$ fromArray(VectorSpecies<$Boxtype$> species,
3483 $type$[] a, int offset,
3484 int[] indexMap, int mapOffset) {
3485 $Type$Species vsp = ($Type$Species) species;
3486 IntVector.IntSpecies isp = IntVector.species(vsp.indexShape());
3487 Objects.requireNonNull(a);
3488 Objects.requireNonNull(indexMap);
3489 Class<? extends $abstractvectortype$> vectorType = vsp.vectorType();
3490
3491 #if[longOrDouble]
3492 if (vsp.laneCount() == 1) {
3493 return $abstractvectortype$.fromArray(vsp, a, offset + indexMap[mapOffset]);
3494 }
3495
3496 // Index vector: vix[0:n] = k -> offset + indexMap[mapOffset + k]
3497 IntVector vix;
3498 if (isp.laneCount() != vsp.laneCount()) {
3499 // For $Type$MaxVector, if vector length is non-power-of-two or
3500 // 2048 bits, indexShape of $Type$ species is S_MAX_BIT.
3501 // Assume that vector length is 2048, then the lane count of $Type$
3502 // vector is 32. When converting $Type$ species to int species,
3503 // indexShape is still S_MAX_BIT, but the lane count of int vector
3504 // is 64. So when loading index vector (IntVector), only lower half
3505 // of index data is needed.
3506 vix = IntVector
3507 .fromArray(isp, indexMap, mapOffset, IntMaxVector.IntMaxMask.LOWER_HALF_TRUE_MASK)
3508 .add(offset);
3509 } else {
3510 vix = IntVector
3511 .fromArray(isp, indexMap, mapOffset)
3512 .add(offset);
3513 }
3514 #else[longOrDouble]
3515 // Index vector: vix[0:n] = k -> offset + indexMap[mapOffset + k]
3516 IntVector vix = IntVector
3517 .fromArray(isp, indexMap, mapOffset)
3518 .add(offset);
3519 #end[longOrDouble]
3520
3521 vix = VectorIntrinsics.checkIndex(vix, a.length);
3522
3523 return VectorSupport.loadWithMap(
3524 vectorType, null, $type$.class, vsp.laneCount(),
3525 isp.vectorType(),
3526 a, ARRAY_BASE, vix, null,
3527 a, offset, indexMap, mapOffset, vsp,
3528 (c, idx, iMap, idy, s, vm) ->
3529 s.vOp(n -> c[idx + iMap[idy+n]]));
3530 }
3531 #end[byteOrShort]
3532
3533 /**
3534 * Gathers a new vector composed of elements from an array of type
3535 * {@code $type$[]},
3536 * under the control of a mask, and
3537 * using indexes obtained by adding a fixed {@code offset} to a
3538 * series of secondary offsets from an <em>index map</em>.
3539 * The index map is a contiguous sequence of {@code VLENGTH}
3540 * elements in a second array of {@code int}s, starting at a given
3541 * {@code mapOffset}.
3542 * <p>
3543 * For each vector lane, where {@code N} is the vector lane index,
3544 * if the lane is set in the mask,
3545 * the lane is loaded from the array
3546 * element {@code a[f(N)]}, where {@code f(N)} is the
3547 * index mapping expression
3548 * {@code offset + indexMap[mapOffset + N]]}.
3549 * Unset lanes in the resulting vector are set to zero.
3550 *
3551 * @param species species of desired vector
3552 * @param a the array
3553 * @param offset the offset into the array, may be negative if relative
3554 * indexes in the index map compensate to produce a value within the
3555 * array bounds
3556 * @param indexMap the index map
3557 * @param mapOffset the offset into the index map
3558 * @param m the mask controlling lane selection
3559 * @return the vector loaded from the indexed elements of the array
3560 * @throws IndexOutOfBoundsException
3561 * if {@code mapOffset+N < 0}
3562 * or if {@code mapOffset+N >= indexMap.length},
3563 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
3564 * is an invalid index into {@code a},
3565 * for any lane {@code N} in the vector
3566 * where the mask is set
3567 * @see $abstractvectortype$#toIntArray()
3568 */
3569 #if[byteOrShort]
3570 @ForceInline
3571 public static
3572 $abstractvectortype$ fromArray(VectorSpecies<$Boxtype$> species,
3573 $type$[] a, int offset,
3574 int[] indexMap, int mapOffset,
3575 VectorMask<$Boxtype$> m) {
3576 $Type$Species vsp = ($Type$Species) species;
3577 return vsp.vOp(m, n -> a[offset + indexMap[mapOffset + n]]);
3578 }
3579 #else[byteOrShort]
3580 @ForceInline
3581 public static
3582 $abstractvectortype$ fromArray(VectorSpecies<$Boxtype$> species,
3583 $type$[] a, int offset,
3584 int[] indexMap, int mapOffset,
3585 VectorMask<$Boxtype$> m) {
3586 if (m.allTrue()) {
3587 return fromArray(species, a, offset, indexMap, mapOffset);
3588 }
3589 else {
3590 $Type$Species vsp = ($Type$Species) species;
3591 return vsp.dummyVector().fromArray0(a, offset, indexMap, mapOffset, m);
3592 }
3593 }
3594 #end[byteOrShort]
3595
3596 #if[short]
3597 /**
3598 * Loads a vector from an array of type {@code char[]}
3599 * starting at an offset.
3600 * For each vector lane, where {@code N} is the vector lane index, the
3601 * array element at index {@code offset + N}
3602 * is first cast to a {@code short} value and then
3603 * placed into the resulting vector at lane index {@code N}.
3604 *
3605 * @param species species of desired vector
3606 * @param a the array
3607 * @param offset the offset into the array
3608 * @return the vector loaded from an array
3609 * @throws IndexOutOfBoundsException
3610 * if {@code offset+N < 0} or {@code offset+N >= a.length}
3611 * for any lane {@code N} in the vector
3612 */
3613 @ForceInline
3614 public static
3615 $abstractvectortype$ fromCharArray(VectorSpecies<$Boxtype$> species,
3616 char[] a, int offset) {
3617 offset = checkFromIndexSize(offset, species.length(), a.length);
3618 $Type$Species vsp = ($Type$Species) species;
3619 return vsp.dummyVector().fromCharArray0(a, offset);
3620 }
3621
3622 /**
3623 * Loads a vector from an array of type {@code char[]}
3624 * starting at an offset and using a mask.
3625 * Lanes where the mask is unset are filled with the default
3626 * value of {@code $type$} ({#if[FP]?positive }zero).
3627 * For each vector lane, where {@code N} is the vector lane index,
3628 * if the mask lane at index {@code N} is set then the array element at
3629 * index {@code offset + N}
3630 * is first cast to a {@code short} value and then
3631 * placed into the resulting vector at lane index
3632 * {@code N}, otherwise the default element value is placed into the
3633 * resulting vector at lane index {@code N}.
3634 *
3635 * @param species species of desired vector
3636 * @param a the array
3637 * @param offset the offset into the array
3638 * @param m the mask controlling lane selection
3639 * @return the vector loaded from an array
3640 * @throws IndexOutOfBoundsException
3641 * if {@code offset+N < 0} or {@code offset+N >= a.length}
3642 * for any lane {@code N} in the vector
3643 * where the mask is set
3644 */
3645 @ForceInline
3646 public static
3647 $abstractvectortype$ fromCharArray(VectorSpecies<$Boxtype$> species,
3648 char[] a, int offset,
3649 VectorMask<$Boxtype$> m) {
3650 $Type$Species vsp = ($Type$Species) species;
3651 if (offset >= 0 && offset <= (a.length - species.length())) {
3652 return vsp.dummyVector().fromCharArray0(a, offset, m);
3653 }
3654
3655 // FIXME: optimize
3656 checkMaskFromIndexSize(offset, vsp, m, 1, a.length);
3657 return vsp.vOp(m, i -> (short) a[offset + i]);
3658 }
3659
3660 /**
3661 * Gathers a new vector composed of elements from an array of type
3662 * {@code char[]},
3663 * using indexes obtained by adding a fixed {@code offset} to a
3664 * series of secondary offsets from an <em>index map</em>.
3665 * The index map is a contiguous sequence of {@code VLENGTH}
3666 * elements in a second array of {@code int}s, starting at a given
3667 * {@code mapOffset}.
3668 * <p>
3669 * For each vector lane, where {@code N} is the vector lane index,
3670 * the lane is loaded from the expression
3671 * {@code (short) a[f(N)]}, where {@code f(N)} is the
3672 * index mapping expression
3673 * {@code offset + indexMap[mapOffset + N]]}.
3674 *
3675 * @param species species of desired vector
3676 * @param a the array
3677 * @param offset the offset into the array, may be negative if relative
3678 * indexes in the index map compensate to produce a value within the
3679 * array bounds
3680 * @param indexMap the index map
3681 * @param mapOffset the offset into the index map
3682 * @return the vector loaded from the indexed elements of the array
3683 * @throws IndexOutOfBoundsException
3684 * if {@code mapOffset+N < 0}
3685 * or if {@code mapOffset+N >= indexMap.length},
3686 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
3687 * is an invalid index into {@code a},
3688 * for any lane {@code N} in the vector
3689 * @see $abstractvectortype$#toIntArray()
3690 */
3691 @ForceInline
3692 public static
3693 $abstractvectortype$ fromCharArray(VectorSpecies<$Boxtype$> species,
3694 char[] a, int offset,
3695 int[] indexMap, int mapOffset) {
3696 // FIXME: optimize
3697 $Type$Species vsp = ($Type$Species) species;
3698 return vsp.vOp(n -> (short) a[offset + indexMap[mapOffset + n]]);
3699 }
3700
3701 /**
3702 * Gathers a new vector composed of elements from an array of type
3703 * {@code char[]},
3704 * under the control of a mask, and
3705 * using indexes obtained by adding a fixed {@code offset} to a
3706 * series of secondary offsets from an <em>index map</em>.
3707 * The index map is a contiguous sequence of {@code VLENGTH}
3708 * elements in a second array of {@code int}s, starting at a given
3709 * {@code mapOffset}.
3710 * <p>
3711 * For each vector lane, where {@code N} is the vector lane index,
3712 * if the lane is set in the mask,
3713 * the lane is loaded from the expression
3714 * {@code (short) a[f(N)]}, where {@code f(N)} is the
3715 * index mapping expression
3716 * {@code offset + indexMap[mapOffset + N]]}.
3717 * Unset lanes in the resulting vector are set to zero.
3718 *
3719 * @param species species of desired vector
3720 * @param a the array
3721 * @param offset the offset into the array, may be negative if relative
3722 * indexes in the index map compensate to produce a value within the
3723 * array bounds
3724 * @param indexMap the index map
3725 * @param mapOffset the offset into the index map
3726 * @param m the mask controlling lane selection
3727 * @return the vector loaded from the indexed elements of the array
3728 * @throws IndexOutOfBoundsException
3729 * if {@code mapOffset+N < 0}
3730 * or if {@code mapOffset+N >= indexMap.length},
3731 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
3732 * is an invalid index into {@code a},
3733 * for any lane {@code N} in the vector
3734 * where the mask is set
3735 * @see $abstractvectortype$#toIntArray()
3736 */
3737 @ForceInline
3738 public static
3739 $abstractvectortype$ fromCharArray(VectorSpecies<$Boxtype$> species,
3740 char[] a, int offset,
3741 int[] indexMap, int mapOffset,
3742 VectorMask<$Boxtype$> m) {
3743 // FIXME: optimize
3744 $Type$Species vsp = ($Type$Species) species;
3745 return vsp.vOp(m, n -> (short) a[offset + indexMap[mapOffset + n]]);
3746 }
3747 #end[short]
3748
3749 #if[byte]
3750 /**
3751 * Loads a vector from an array of type {@code boolean[]}
3752 * starting at an offset.
3753 * For each vector lane, where {@code N} is the vector lane index, the
3754 * array element at index {@code offset + N}
3755 * is first converted to a {@code byte} value and then
3756 * placed into the resulting vector at lane index {@code N}.
3757 * <p>
3758 * A {@code boolean} value is converted to a {@code byte} value by applying the
3759 * expression {@code (byte) (b ? 1 : 0)}, where {@code b} is the {@code boolean} value.
3760 *
3761 * @param species species of desired vector
3762 * @param a the array
3763 * @param offset the offset into the array
3764 * @return the vector loaded from an array
3765 * @throws IndexOutOfBoundsException
3766 * if {@code offset+N < 0} or {@code offset+N >= a.length}
3767 * for any lane {@code N} in the vector
3768 */
3769 @ForceInline
3770 public static
3771 $abstractvectortype$ fromBooleanArray(VectorSpecies<$Boxtype$> species,
3772 boolean[] a, int offset) {
3773 offset = checkFromIndexSize(offset, species.length(), a.length);
3774 $Type$Species vsp = ($Type$Species) species;
3775 return vsp.dummyVector().fromBooleanArray0(a, offset);
3776 }
3777
3778 /**
3779 * Loads a vector from an array of type {@code boolean[]}
3780 * starting at an offset and using a mask.
3781 * Lanes where the mask is unset are filled with the default
3782 * value of {@code $type$} ({#if[FP]?positive }zero).
3783 * For each vector lane, where {@code N} is the vector lane index,
3784 * if the mask lane at index {@code N} is set then the array element at
3785 * index {@code offset + N}
3786 * is first converted to a {@code byte} value and then
3787 * placed into the resulting vector at lane index
3788 * {@code N}, otherwise the default element value is placed into the
3789 * resulting vector at lane index {@code N}.
3790 * <p>
3791 * A {@code boolean} value is converted to a {@code byte} value by applying the
3792 * expression {@code (byte) (b ? 1 : 0)}, where {@code b} is the {@code boolean} value.
3793 *
3794 * @param species species of desired vector
3795 * @param a the array
3796 * @param offset the offset into the array
3797 * @param m the mask controlling lane selection
3798 * @return the vector loaded from an array
3799 * @throws IndexOutOfBoundsException
3800 * if {@code offset+N < 0} or {@code offset+N >= a.length}
3801 * for any lane {@code N} in the vector
3802 * where the mask is set
3803 */
3804 @ForceInline
3805 public static
3806 $abstractvectortype$ fromBooleanArray(VectorSpecies<$Boxtype$> species,
3807 boolean[] a, int offset,
3808 VectorMask<$Boxtype$> m) {
3809 $Type$Species vsp = ($Type$Species) species;
3810 if (offset >= 0 && offset <= (a.length - species.length())) {
3811 $abstractvectortype$ zero = vsp.zero();
3812 return vsp.dummyVector().fromBooleanArray0(a, offset, m);
3813 }
3814
3815 // FIXME: optimize
3816 checkMaskFromIndexSize(offset, vsp, m, 1, a.length);
3817 return vsp.vOp(m, i -> (byte) (a[offset + i] ? 1 : 0));
3818 }
3819
3820 /**
3821 * Gathers a new vector composed of elements from an array of type
3822 * {@code boolean[]},
3823 * using indexes obtained by adding a fixed {@code offset} to a
3824 * series of secondary offsets from an <em>index map</em>.
3825 * The index map is a contiguous sequence of {@code VLENGTH}
3826 * elements in a second array of {@code int}s, starting at a given
3827 * {@code mapOffset}.
3828 * <p>
3829 * For each vector lane, where {@code N} is the vector lane index,
3830 * the lane is loaded from the expression
3831 * {@code (byte) (a[f(N)] ? 1 : 0)}, where {@code f(N)} is the
3832 * index mapping expression
3833 * {@code offset + indexMap[mapOffset + N]]}.
3834 *
3835 * @param species species of desired vector
3836 * @param a the array
3837 * @param offset the offset into the array, may be negative if relative
3838 * indexes in the index map compensate to produce a value within the
3839 * array bounds
3840 * @param indexMap the index map
3841 * @param mapOffset the offset into the index map
3842 * @return the vector loaded from the indexed elements of the array
3843 * @throws IndexOutOfBoundsException
3844 * if {@code mapOffset+N < 0}
3845 * or if {@code mapOffset+N >= indexMap.length},
3846 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
3847 * is an invalid index into {@code a},
3848 * for any lane {@code N} in the vector
3849 * @see $abstractvectortype$#toIntArray()
3850 */
3851 @ForceInline
3852 public static
3853 $abstractvectortype$ fromBooleanArray(VectorSpecies<$Boxtype$> species,
3854 boolean[] a, int offset,
3855 int[] indexMap, int mapOffset) {
3856 // FIXME: optimize
3857 $Type$Species vsp = ($Type$Species) species;
3858 return vsp.vOp(n -> (byte) (a[offset + indexMap[mapOffset + n]] ? 1 : 0));
3859 }
3860
3861 /**
3862 * Gathers a new vector composed of elements from an array of type
3863 * {@code boolean[]},
3864 * under the control of a mask, and
3865 * using indexes obtained by adding a fixed {@code offset} to a
3866 * series of secondary offsets from an <em>index map</em>.
3867 * The index map is a contiguous sequence of {@code VLENGTH}
3868 * elements in a second array of {@code int}s, starting at a given
3869 * {@code mapOffset}.
3870 * <p>
3871 * For each vector lane, where {@code N} is the vector lane index,
3872 * if the lane is set in the mask,
3873 * the lane is loaded from the expression
3874 * {@code (byte) (a[f(N)] ? 1 : 0)}, where {@code f(N)} is the
3875 * index mapping expression
3876 * {@code offset + indexMap[mapOffset + N]]}.
3877 * Unset lanes in the resulting vector are set to zero.
3878 *
3879 * @param species species of desired vector
3880 * @param a the array
3881 * @param offset the offset into the array, may be negative if relative
3882 * indexes in the index map compensate to produce a value within the
3883 * array bounds
3884 * @param indexMap the index map
3885 * @param mapOffset the offset into the index map
3886 * @param m the mask controlling lane selection
3887 * @return the vector loaded from the indexed elements of the array
3888 * @throws IndexOutOfBoundsException
3889 * if {@code mapOffset+N < 0}
3890 * or if {@code mapOffset+N >= indexMap.length},
3891 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
3892 * is an invalid index into {@code a},
3893 * for any lane {@code N} in the vector
3894 * where the mask is set
3895 * @see $abstractvectortype$#toIntArray()
3896 */
3897 @ForceInline
3898 public static
3899 $abstractvectortype$ fromBooleanArray(VectorSpecies<$Boxtype$> species,
3900 boolean[] a, int offset,
3901 int[] indexMap, int mapOffset,
3902 VectorMask<$Boxtype$> m) {
3903 // FIXME: optimize
3904 $Type$Species vsp = ($Type$Species) species;
3905 return vsp.vOp(m, n -> (byte) (a[offset + indexMap[mapOffset + n]] ? 1 : 0));
3906 }
3907 #end[byte]
3908
3909 /**
3910 * Loads a vector from a {@linkplain ByteBuffer byte buffer}
3911 * starting at an offset into the byte buffer.
3912 * Bytes are composed into primitive lane elements according
3913 * to the specified byte order.
3914 * The vector is arranged into lanes according to
3915 * <a href="Vector.html#lane-order">memory ordering</a>.
3916 * <p>
3917 * This method behaves as if it returns the result of calling
3918 * {@link #fromByteBuffer(VectorSpecies,ByteBuffer,int,ByteOrder,VectorMask)
3919 * fromByteBuffer()} as follows:
3920 * <pre>{@code
3921 * var m = species.maskAll(true);
3922 * return fromByteBuffer(species, bb, offset, bo, m);
3923 * }</pre>
3924 *
3925 * @param species species of desired vector
3926 * @param bb the byte buffer
3927 * @param offset the offset into the byte buffer
3928 * @param bo the intended byte order
3929 * @return a vector loaded from a byte buffer
3930 * @throws IndexOutOfBoundsException
3931 * if {@code offset+N*$sizeInBytes$ < 0}
3932 * or {@code offset+N*$sizeInBytes$ >= bb.limit()}
3933 * for any lane {@code N} in the vector
3934 */
3935 @ForceInline
3936 public static
3937 $abstractvectortype$ fromByteBuffer(VectorSpecies<$Boxtype$> species,
3938 ByteBuffer bb, int offset,
3939 ByteOrder bo) {
3940 offset = checkFromIndexSize(offset, species.vectorByteSize(), bb.limit());
3941 $Type$Species vsp = ($Type$Species) species;
3942 return vsp.dummyVector().fromByteBuffer0(bb, offset).maybeSwap(bo);
3943 }
3944
3945 /**
3946 * Loads a vector from a {@linkplain ByteBuffer byte buffer}
3947 * starting at an offset into the byte buffer
3948 * and using a mask.
3949 * Lanes where the mask is unset are filled with the default
3950 * value of {@code $type$} ({#if[FP]?positive }zero).
3951 * Bytes are composed into primitive lane elements according
3952 * to the specified byte order.
3953 * The vector is arranged into lanes according to
3954 * <a href="Vector.html#lane-order">memory ordering</a>.
3955 * <p>
3956 * The following pseudocode illustrates the behavior:
3957 * <pre>{@code
3958 * $Type$Buffer eb = bb.duplicate()
3959 * .position(offset){#if[byte]?;}
3960 #if[!byte]
3961 * .order(bo).as$Type$Buffer();
3962 #end[!byte]
3963 * $type$[] ar = new $type$[species.length()];
3964 * for (int n = 0; n < ar.length; n++) {
3965 * if (m.laneIsSet(n)) {
3966 * ar[n] = eb.get(n);
3967 * }
3968 * }
3969 * $abstractvectortype$ r = $abstractvectortype$.fromArray(species, ar, 0);
3970 * }</pre>
3971 * @implNote
3972 #if[!byte]
3973 * This operation is likely to be more efficient if
3974 * the specified byte order is the same as
3975 * {@linkplain ByteOrder#nativeOrder()
3976 * the platform native order},
3977 * since this method will not need to reorder
3978 * the bytes of lane values.
3979 #else[!byte]
3980 * The byte order argument is ignored.
3981 #end[!byte]
3982 *
3983 * @param species species of desired vector
3984 * @param bb the byte buffer
3985 * @param offset the offset into the byte buffer
3986 * @param bo the intended byte order
3987 * @param m the mask controlling lane selection
3988 * @return a vector loaded from a byte buffer
3989 * @throws IndexOutOfBoundsException
3990 * if {@code offset+N*$sizeInBytes$ < 0}
3991 * or {@code offset+N*$sizeInBytes$ >= bb.limit()}
3992 * for any lane {@code N} in the vector
3993 * where the mask is set
3994 */
3995 @ForceInline
3996 public static
3997 $abstractvectortype$ fromByteBuffer(VectorSpecies<$Boxtype$> species,
3998 ByteBuffer bb, int offset,
3999 ByteOrder bo,
4000 VectorMask<$Boxtype$> m) {
4001 $Type$Species vsp = ($Type$Species) species;
4002 if (offset >= 0 && offset <= (bb.limit() - species.vectorByteSize())) {
4003 return vsp.dummyVector().fromByteBuffer0(bb, offset, m).maybeSwap(bo);
4004 }
4005
4006 // FIXME: optimize
4007 checkMaskFromIndexSize(offset, vsp, m, $sizeInBytes$, bb.limit());
4008 ByteBuffer wb = wrapper(bb, bo);
4009 return vsp.ldOp(wb, offset, (AbstractMask<$Boxtype$>)m,
4010 (wb_, o, i) -> wb_.get{#if[byte]?(:$Type$(}o + i * $sizeInBytes$));
4011 }
4012
4013 // Memory store operations
4014
4015 /**
4016 * Stores this vector into an array of type {@code $type$[]}
4017 * starting at an offset.
4018 * <p>
4019 * For each vector lane, where {@code N} is the vector lane index,
4020 * the lane element at index {@code N} is stored into the array
4021 * element {@code a[offset+N]}.
4022 *
4023 * @param a the array, of type {@code $type$[]}
4024 * @param offset the offset into the array
4025 * @throws IndexOutOfBoundsException
4026 * if {@code offset+N < 0} or {@code offset+N >= a.length}
4027 * for any lane {@code N} in the vector
4028 */
4029 @ForceInline
4030 public final
4031 void intoArray($type$[] a, int offset) {
4032 offset = checkFromIndexSize(offset, length(), a.length);
4033 $Type$Species vsp = vspecies();
4034 VectorSupport.store(
4035 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4036 a, arrayAddress(a, offset),
4037 this,
4038 a, offset,
4039 (arr, off, v)
4040 -> v.stOp(arr, off,
4041 (arr_, off_, i, e) -> arr_[off_ + i] = e));
4042 }
4043
4044 /**
4045 * Stores this vector into an array of type {@code $type$[]}
4046 * starting at offset and using a mask.
4047 * <p>
4048 * For each vector lane, where {@code N} is the vector lane index,
4049 * the lane element at index {@code N} is stored into the array
4050 * element {@code a[offset+N]}.
4051 * If the mask lane at {@code N} is unset then the corresponding
4052 * array element {@code a[offset+N]} is left unchanged.
4053 * <p>
4054 * Array range checking is done for lanes where the mask is set.
4055 * Lanes where the mask is unset are not stored and do not need
4056 * to correspond to legitimate elements of {@code a}.
4057 * That is, unset lanes may correspond to array indexes less than
4058 * zero or beyond the end of the array.
4059 *
4060 * @param a the array, of type {@code $type$[]}
4061 * @param offset the offset into the array
4062 * @param m the mask controlling lane storage
4063 * @throws IndexOutOfBoundsException
4064 * if {@code offset+N < 0} or {@code offset+N >= a.length}
4065 * for any lane {@code N} in the vector
4066 * where the mask is set
4067 */
4068 @ForceInline
4069 public final
4070 void intoArray($type$[] a, int offset,
4071 VectorMask<$Boxtype$> m) {
4072 if (m.allTrue()) {
4073 intoArray(a, offset);
4074 } else {
4075 $Type$Species vsp = vspecies();
4076 checkMaskFromIndexSize(offset, vsp, m, 1, a.length);
4077 intoArray0(a, offset, m);
4078 }
4079 }
4080
4081 /**
4082 * Scatters this vector into an array of type {@code $type$[]}
4083 * using indexes obtained by adding a fixed {@code offset} to a
4084 * series of secondary offsets from an <em>index map</em>.
4085 * The index map is a contiguous sequence of {@code VLENGTH}
4086 * elements in a second array of {@code int}s, starting at a given
4087 * {@code mapOffset}.
4088 * <p>
4089 * For each vector lane, where {@code N} is the vector lane index,
4090 * the lane element at index {@code N} is stored into the array
4091 * element {@code a[f(N)]}, where {@code f(N)} is the
4092 * index mapping expression
4093 * {@code offset + indexMap[mapOffset + N]]}.
4094 *
4095 * @param a the array
4096 * @param offset an offset to combine with the index map offsets
4097 * @param indexMap the index map
4098 * @param mapOffset the offset into the index map
4099 * @throws IndexOutOfBoundsException
4100 * if {@code mapOffset+N < 0}
4101 * or if {@code mapOffset+N >= indexMap.length},
4102 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
4103 * is an invalid index into {@code a},
4104 * for any lane {@code N} in the vector
4105 * @see $abstractvectortype$#toIntArray()
4106 */
4107 #if[byteOrShort]
4108 @ForceInline
4109 public final
4110 void intoArray($type$[] a, int offset,
4111 int[] indexMap, int mapOffset) {
4112 stOp(a, offset,
4113 (arr, off, i, e) -> {
4114 int j = indexMap[mapOffset + i];
4115 arr[off + j] = e;
4116 });
4117 }
4118 #else[byteOrShort]
4119 @ForceInline
4120 public final
4121 void intoArray($type$[] a, int offset,
4122 int[] indexMap, int mapOffset) {
4123 $Type$Species vsp = vspecies();
4124 IntVector.IntSpecies isp = IntVector.species(vsp.indexShape());
4125 #if[longOrDouble]
4126 if (vsp.laneCount() == 1) {
4127 intoArray(a, offset + indexMap[mapOffset]);
4128 return;
4129 }
4130
4131 // Index vector: vix[0:n] = i -> offset + indexMap[mo + i]
4132 IntVector vix;
4133 if (isp.laneCount() != vsp.laneCount()) {
4134 // For $Type$MaxVector, if vector length is 2048 bits, indexShape
4135 // of $Type$ species is S_MAX_BIT. and the lane count of $Type$
4136 // vector is 32. When converting $Type$ species to int species,
4137 // indexShape is still S_MAX_BIT, but the lane count of int vector
4138 // is 64. So when loading index vector (IntVector), only lower half
4139 // of index data is needed.
4140 vix = IntVector
4141 .fromArray(isp, indexMap, mapOffset, IntMaxVector.IntMaxMask.LOWER_HALF_TRUE_MASK)
4142 .add(offset);
4143 } else {
4144 vix = IntVector
4145 .fromArray(isp, indexMap, mapOffset)
4146 .add(offset);
4147 }
4148
4149 #else[longOrDouble]
4150 // Index vector: vix[0:n] = i -> offset + indexMap[mo + i]
4151 IntVector vix = IntVector
4152 .fromArray(isp, indexMap, mapOffset)
4153 .add(offset);
4154 #end[longOrDouble]
4155
4156 vix = VectorIntrinsics.checkIndex(vix, a.length);
4157
4158 VectorSupport.storeWithMap(
4159 vsp.vectorType(), null, vsp.elementType(), vsp.laneCount(),
4160 isp.vectorType(),
4161 a, arrayAddress(a, 0), vix,
4162 this, null,
4163 a, offset, indexMap, mapOffset,
4164 (arr, off, v, map, mo, vm)
4165 -> v.stOp(arr, off,
4166 (arr_, off_, i, e) -> {
4167 int j = map[mo + i];
4168 arr[off + j] = e;
4169 }));
4170 }
4171 #end[byteOrShort]
4172
4173 /**
4174 * Scatters this vector into an array of type {@code $type$[]},
4175 * under the control of a mask, and
4176 * using indexes obtained by adding a fixed {@code offset} to a
4177 * series of secondary offsets from an <em>index map</em>.
4178 * The index map is a contiguous sequence of {@code VLENGTH}
4179 * elements in a second array of {@code int}s, starting at a given
4180 * {@code mapOffset}.
4181 * <p>
4182 * For each vector lane, where {@code N} is the vector lane index,
4183 * if the mask lane at index {@code N} is set then
4184 * the lane element at index {@code N} is stored into the array
4185 * element {@code a[f(N)]}, where {@code f(N)} is the
4186 * index mapping expression
4187 * {@code offset + indexMap[mapOffset + N]]}.
4188 *
4189 * @param a the array
4190 * @param offset an offset to combine with the index map offsets
4191 * @param indexMap the index map
4192 * @param mapOffset the offset into the index map
4193 * @param m the mask
4194 * @throws IndexOutOfBoundsException
4195 * if {@code mapOffset+N < 0}
4196 * or if {@code mapOffset+N >= indexMap.length},
4197 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
4198 * is an invalid index into {@code a},
4199 * for any lane {@code N} in the vector
4200 * where the mask is set
4201 * @see $abstractvectortype$#toIntArray()
4202 */
4203 #if[byteOrShort]
4204 @ForceInline
4205 public final
4206 void intoArray($type$[] a, int offset,
4207 int[] indexMap, int mapOffset,
4208 VectorMask<$Boxtype$> m) {
4209 stOp(a, offset, m,
4210 (arr, off, i, e) -> {
4211 int j = indexMap[mapOffset + i];
4212 arr[off + j] = e;
4213 });
4214 }
4215 #else[byteOrShort]
4216 @ForceInline
4217 public final
4218 void intoArray($type$[] a, int offset,
4219 int[] indexMap, int mapOffset,
4220 VectorMask<$Boxtype$> m) {
4221 if (m.allTrue()) {
4222 intoArray(a, offset, indexMap, mapOffset);
4223 }
4224 else {
4225 intoArray0(a, offset, indexMap, mapOffset, m);
4226 }
4227 }
4228 #end[byteOrShort]
4229
4230 #if[short]
4231 /**
4232 * Stores this vector into an array of type {@code char[]}
4233 * starting at an offset.
4234 * <p>
4235 * For each vector lane, where {@code N} is the vector lane index,
4236 * the lane element at index {@code N}
4237 * is first cast to a {@code char} value and then
4238 * stored into the array element {@code a[offset+N]}.
4239 *
4240 * @param a the array, of type {@code char[]}
4241 * @param offset the offset into the array
4242 * @throws IndexOutOfBoundsException
4243 * if {@code offset+N < 0} or {@code offset+N >= a.length}
4244 * for any lane {@code N} in the vector
4245 */
4246 @ForceInline
4247 public final
4248 void intoCharArray(char[] a, int offset) {
4249 offset = checkFromIndexSize(offset, length(), a.length);
4250 $Type$Species vsp = vspecies();
4251 VectorSupport.store(
4252 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4253 a, charArrayAddress(a, offset),
4254 this,
4255 a, offset,
4256 (arr, off, v)
4257 -> v.stOp(arr, off,
4258 (arr_, off_, i, e) -> arr_[off_ + i] = (char) e));
4259 }
4260
4261 /**
4262 * Stores this vector into an array of type {@code char[]}
4263 * starting at offset and using a mask.
4264 * <p>
4265 * For each vector lane, where {@code N} is the vector lane index,
4266 * the lane element at index {@code N}
4267 * is first cast to a {@code char} value and then
4268 * stored into the array element {@code a[offset+N]}.
4269 * If the mask lane at {@code N} is unset then the corresponding
4270 * array element {@code a[offset+N]} is left unchanged.
4271 * <p>
4272 * Array range checking is done for lanes where the mask is set.
4273 * Lanes where the mask is unset are not stored and do not need
4274 * to correspond to legitimate elements of {@code a}.
4275 * That is, unset lanes may correspond to array indexes less than
4276 * zero or beyond the end of the array.
4277 *
4278 * @param a the array, of type {@code char[]}
4279 * @param offset the offset into the array
4280 * @param m the mask controlling lane storage
4281 * @throws IndexOutOfBoundsException
4282 * if {@code offset+N < 0} or {@code offset+N >= a.length}
4283 * for any lane {@code N} in the vector
4284 * where the mask is set
4285 */
4286 @ForceInline
4287 public final
4288 void intoCharArray(char[] a, int offset,
4289 VectorMask<$Boxtype$> m) {
4290 if (m.allTrue()) {
4291 intoCharArray(a, offset);
4292 } else {
4293 $Type$Species vsp = vspecies();
4294 checkMaskFromIndexSize(offset, vsp, m, 1, a.length);
4295 intoCharArray0(a, offset, m);
4296 }
4297 }
4298
4299 /**
4300 * Scatters this vector into an array of type {@code char[]}
4301 * using indexes obtained by adding a fixed {@code offset} to a
4302 * series of secondary offsets from an <em>index map</em>.
4303 * The index map is a contiguous sequence of {@code VLENGTH}
4304 * elements in a second array of {@code int}s, starting at a given
4305 * {@code mapOffset}.
4306 * <p>
4307 * For each vector lane, where {@code N} is the vector lane index,
4308 * the lane element at index {@code N}
4309 * is first cast to a {@code char} value and then
4310 * stored into the array
4311 * element {@code a[f(N)]}, where {@code f(N)} is the
4312 * index mapping expression
4313 * {@code offset + indexMap[mapOffset + N]]}.
4314 *
4315 * @param a the array
4316 * @param offset an offset to combine with the index map offsets
4317 * @param indexMap the index map
4318 * @param mapOffset the offset into the index map
4319 * @throws IndexOutOfBoundsException
4320 * if {@code mapOffset+N < 0}
4321 * or if {@code mapOffset+N >= indexMap.length},
4322 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
4323 * is an invalid index into {@code a},
4324 * for any lane {@code N} in the vector
4325 * @see $abstractvectortype$#toIntArray()
4326 */
4327 @ForceInline
4328 public final
4329 void intoCharArray(char[] a, int offset,
4330 int[] indexMap, int mapOffset) {
4331 // FIXME: optimize
4332 stOp(a, offset,
4333 (arr, off, i, e) -> {
4334 int j = indexMap[mapOffset + i];
4335 arr[off + j] = (char) e;
4336 });
4337 }
4338
4339 /**
4340 * Scatters this vector into an array of type {@code char[]},
4341 * under the control of a mask, and
4342 * using indexes obtained by adding a fixed {@code offset} to a
4343 * series of secondary offsets from an <em>index map</em>.
4344 * The index map is a contiguous sequence of {@code VLENGTH}
4345 * elements in a second array of {@code int}s, starting at a given
4346 * {@code mapOffset}.
4347 * <p>
4348 * For each vector lane, where {@code N} is the vector lane index,
4349 * if the mask lane at index {@code N} is set then
4350 * the lane element at index {@code N}
4351 * is first cast to a {@code char} value and then
4352 * stored into the array
4353 * element {@code a[f(N)]}, where {@code f(N)} is the
4354 * index mapping expression
4355 * {@code offset + indexMap[mapOffset + N]]}.
4356 *
4357 * @param a the array
4358 * @param offset an offset to combine with the index map offsets
4359 * @param indexMap the index map
4360 * @param mapOffset the offset into the index map
4361 * @param m the mask
4362 * @throws IndexOutOfBoundsException
4363 * if {@code mapOffset+N < 0}
4364 * or if {@code mapOffset+N >= indexMap.length},
4365 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
4366 * is an invalid index into {@code a},
4367 * for any lane {@code N} in the vector
4368 * where the mask is set
4369 * @see $abstractvectortype$#toIntArray()
4370 */
4371 @ForceInline
4372 public final
4373 void intoCharArray(char[] a, int offset,
4374 int[] indexMap, int mapOffset,
4375 VectorMask<$Boxtype$> m) {
4376 // FIXME: optimize
4377 stOp(a, offset, m,
4378 (arr, off, i, e) -> {
4379 int j = indexMap[mapOffset + i];
4380 arr[off + j] = (char) e;
4381 });
4382 }
4383 #end[short]
4384
4385 #if[byte]
4386 /**
4387 * Stores this vector into an array of type {@code boolean[]}
4388 * starting at an offset.
4389 * <p>
4390 * For each vector lane, where {@code N} is the vector lane index,
4391 * the lane element at index {@code N}
4392 * is first converted to a {@code boolean} value and then
4393 * stored into the array element {@code a[offset+N]}.
4394 * <p>
4395 * A {@code byte} value is converted to a {@code boolean} value by applying the
4396 * expression {@code (b & 1) != 0} where {@code b} is the byte value.
4397 *
4398 * @param a the array
4399 * @param offset the offset into the array
4400 * @throws IndexOutOfBoundsException
4401 * if {@code offset+N < 0} or {@code offset+N >= a.length}
4402 * for any lane {@code N} in the vector
4403 */
4404 @ForceInline
4405 public final
4406 void intoBooleanArray(boolean[] a, int offset) {
4407 offset = checkFromIndexSize(offset, length(), a.length);
4408 $Type$Species vsp = vspecies();
4409 ByteVector normalized = this.and((byte) 1);
4410 VectorSupport.store(
4411 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4412 a, booleanArrayAddress(a, offset),
4413 normalized,
4414 a, offset,
4415 (arr, off, v)
4416 -> v.stOp(arr, off,
4417 (arr_, off_, i, e) -> arr_[off_ + i] = (e & 1) != 0));
4418 }
4419
4420 /**
4421 * Stores this vector into an array of type {@code boolean[]}
4422 * starting at offset and using a mask.
4423 * <p>
4424 * For each vector lane, where {@code N} is the vector lane index,
4425 * the lane element at index {@code N}
4426 * is first converted to a {@code boolean} value and then
4427 * stored into the array element {@code a[offset+N]}.
4428 * If the mask lane at {@code N} is unset then the corresponding
4429 * array element {@code a[offset+N]} is left unchanged.
4430 * <p>
4431 * A {@code byte} value is converted to a {@code boolean} value by applying the
4432 * expression {@code (b & 1) != 0} where {@code b} is the byte value.
4433 * <p>
4434 * Array range checking is done for lanes where the mask is set.
4435 * Lanes where the mask is unset are not stored and do not need
4436 * to correspond to legitimate elements of {@code a}.
4437 * That is, unset lanes may correspond to array indexes less than
4438 * zero or beyond the end of the array.
4439 *
4440 * @param a the array
4441 * @param offset the offset into the array
4442 * @param m the mask controlling lane storage
4443 * @throws IndexOutOfBoundsException
4444 * if {@code offset+N < 0} or {@code offset+N >= a.length}
4445 * for any lane {@code N} in the vector
4446 * where the mask is set
4447 */
4448 @ForceInline
4449 public final
4450 void intoBooleanArray(boolean[] a, int offset,
4451 VectorMask<$Boxtype$> m) {
4452 if (m.allTrue()) {
4453 intoBooleanArray(a, offset);
4454 } else {
4455 $Type$Species vsp = vspecies();
4456 checkMaskFromIndexSize(offset, vsp, m, 1, a.length);
4457 intoBooleanArray0(a, offset, m);
4458 }
4459 }
4460
4461 /**
4462 * Scatters this vector into an array of type {@code boolean[]}
4463 * using indexes obtained by adding a fixed {@code offset} to a
4464 * series of secondary offsets from an <em>index map</em>.
4465 * The index map is a contiguous sequence of {@code VLENGTH}
4466 * elements in a second array of {@code int}s, starting at a given
4467 * {@code mapOffset}.
4468 * <p>
4469 * For each vector lane, where {@code N} is the vector lane index,
4470 * the lane element at index {@code N}
4471 * is first converted to a {@code boolean} value and then
4472 * stored into the array
4473 * element {@code a[f(N)]}, where {@code f(N)} is the
4474 * index mapping expression
4475 * {@code offset + indexMap[mapOffset + N]]}.
4476 * <p>
4477 * A {@code byte} value is converted to a {@code boolean} value by applying the
4478 * expression {@code (b & 1) != 0} where {@code b} is the byte value.
4479 *
4480 * @param a the array
4481 * @param offset an offset to combine with the index map offsets
4482 * @param indexMap the index map
4483 * @param mapOffset the offset into the index map
4484 * @throws IndexOutOfBoundsException
4485 * if {@code mapOffset+N < 0}
4486 * or if {@code mapOffset+N >= indexMap.length},
4487 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
4488 * is an invalid index into {@code a},
4489 * for any lane {@code N} in the vector
4490 * @see $abstractvectortype$#toIntArray()
4491 */
4492 @ForceInline
4493 public final
4494 void intoBooleanArray(boolean[] a, int offset,
4495 int[] indexMap, int mapOffset) {
4496 // FIXME: optimize
4497 stOp(a, offset,
4498 (arr, off, i, e) -> {
4499 int j = indexMap[mapOffset + i];
4500 arr[off + j] = (e & 1) != 0;
4501 });
4502 }
4503
4504 /**
4505 * Scatters this vector into an array of type {@code boolean[]},
4506 * under the control of a mask, and
4507 * using indexes obtained by adding a fixed {@code offset} to a
4508 * series of secondary offsets from an <em>index map</em>.
4509 * The index map is a contiguous sequence of {@code VLENGTH}
4510 * elements in a second array of {@code int}s, starting at a given
4511 * {@code mapOffset}.
4512 * <p>
4513 * For each vector lane, where {@code N} is the vector lane index,
4514 * if the mask lane at index {@code N} is set then
4515 * the lane element at index {@code N}
4516 * is first converted to a {@code boolean} value and then
4517 * stored into the array
4518 * element {@code a[f(N)]}, where {@code f(N)} is the
4519 * index mapping expression
4520 * {@code offset + indexMap[mapOffset + N]]}.
4521 * <p>
4522 * A {@code byte} value is converted to a {@code boolean} value by applying the
4523 * expression {@code (b & 1) != 0} where {@code b} is the byte value.
4524 *
4525 * @param a the array
4526 * @param offset an offset to combine with the index map offsets
4527 * @param indexMap the index map
4528 * @param mapOffset the offset into the index map
4529 * @param m the mask
4530 * @throws IndexOutOfBoundsException
4531 * if {@code mapOffset+N < 0}
4532 * or if {@code mapOffset+N >= indexMap.length},
4533 * or if {@code f(N)=offset+indexMap[mapOffset+N]}
4534 * is an invalid index into {@code a},
4535 * for any lane {@code N} in the vector
4536 * where the mask is set
4537 * @see $abstractvectortype$#toIntArray()
4538 */
4539 @ForceInline
4540 public final
4541 void intoBooleanArray(boolean[] a, int offset,
4542 int[] indexMap, int mapOffset,
4543 VectorMask<$Boxtype$> m) {
4544 // FIXME: optimize
4545 stOp(a, offset, m,
4546 (arr, off, i, e) -> {
4547 int j = indexMap[mapOffset + i];
4548 arr[off + j] = (e & 1) != 0;
4549 });
4550 }
4551 #end[byte]
4552
4553 /**
4554 * {@inheritDoc} <!--workaround-->
4555 */
4556 @Override
4557 @ForceInline
4558 public final
4559 void intoByteArray(byte[] a, int offset,
4560 ByteOrder bo) {
4561 offset = checkFromIndexSize(offset, byteSize(), a.length);
4562 maybeSwap(bo).intoByteArray0(a, offset);
4563 }
4564
4565 /**
4566 * {@inheritDoc} <!--workaround-->
4567 */
4568 @Override
4569 @ForceInline
4570 public final
4571 void intoByteArray(byte[] a, int offset,
4572 ByteOrder bo,
4573 VectorMask<$Boxtype$> m) {
4574 if (m.allTrue()) {
4575 intoByteArray(a, offset, bo);
4576 } else {
4577 $Type$Species vsp = vspecies();
4578 checkMaskFromIndexSize(offset, vsp, m, $sizeInBytes$, a.length);
4579 maybeSwap(bo).intoByteArray0(a, offset, m);
4580 }
4581 }
4582
4583 /**
4584 * {@inheritDoc} <!--workaround-->
4585 */
4586 @Override
4587 @ForceInline
4588 public final
4589 void intoByteBuffer(ByteBuffer bb, int offset,
4590 ByteOrder bo) {
4591 if (ScopedMemoryAccess.isReadOnly(bb)) {
4592 throw new ReadOnlyBufferException();
4593 }
4594 offset = checkFromIndexSize(offset, byteSize(), bb.limit());
4595 maybeSwap(bo).intoByteBuffer0(bb, offset);
4596 }
4597
4598 /**
4599 * {@inheritDoc} <!--workaround-->
4600 */
4601 @Override
4602 @ForceInline
4603 public final
4604 void intoByteBuffer(ByteBuffer bb, int offset,
4605 ByteOrder bo,
4606 VectorMask<$Boxtype$> m) {
4607 if (m.allTrue()) {
4608 intoByteBuffer(bb, offset, bo);
4609 } else {
4610 if (bb.isReadOnly()) {
4611 throw new ReadOnlyBufferException();
4612 }
4613 $Type$Species vsp = vspecies();
4614 checkMaskFromIndexSize(offset, vsp, m, $sizeInBytes$, bb.limit());
4615 maybeSwap(bo).intoByteBuffer0(bb, offset, m);
4616 }
4617 }
4618
4619 // ================================================
4620
4621 // Low-level memory operations.
4622 //
4623 // Note that all of these operations *must* inline into a context
4624 // where the exact species of the involved vector is a
4625 // compile-time constant. Otherwise, the intrinsic generation
4626 // will fail and performance will suffer.
4627 //
4628 // In many cases this is achieved by re-deriving a version of the
4629 // method in each concrete subclass (per species). The re-derived
4630 // method simply calls one of these generic methods, with exact
4631 // parameters for the controlling metadata, which is either a
4632 // typed vector or constant species instance.
4633
4634 // Unchecked loading operations in native byte order.
4635 // Caller is responsible for applying index checks, masking, and
4636 // byte swapping.
4637
4638 /*package-private*/
4639 abstract
4640 $abstractvectortype$ fromArray0($type$[] a, int offset);
4641 @ForceInline
4642 final
4643 $abstractvectortype$ fromArray0Template($type$[] a, int offset) {
4644 $Type$Species vsp = vspecies();
4645 return VectorSupport.load(
4646 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4647 a, arrayAddress(a, offset),
4648 a, offset, vsp,
4649 (arr, off, s) -> s.ldOp(arr, off,
4650 (arr_, off_, i) -> arr_[off_ + i]));
4651 }
4652
4653 /*package-private*/
4654 abstract
4655 $abstractvectortype$ fromArray0($type$[] a, int offset, VectorMask<$Boxtype$> m);
4656 @ForceInline
4657 final
4658 <M extends VectorMask<$Boxtype$>>
4659 $abstractvectortype$ fromArray0Template(Class<M> maskClass, $type$[] a, int offset, M m) {
4660 m.check(species());
4661 $Type$Species vsp = vspecies();
4662 return VectorSupport.loadMasked(
4663 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
4664 a, arrayAddress(a, offset), m,
4665 a, offset, vsp,
4666 (arr, off, s, vm) -> s.ldOp(arr, off, vm,
4667 (arr_, off_, i) -> arr_[off_ + i]));
4668 }
4669
4670 #if[!byteOrShort]
4671 /*package-private*/
4672 abstract
4673 $abstractvectortype$ fromArray0($type$[] a, int offset,
4674 int[] indexMap, int mapOffset,
4675 VectorMask<$Boxtype$> m);
4676 @ForceInline
4677 final
4678 <M extends VectorMask<$Boxtype$>>
4679 $abstractvectortype$ fromArray0Template(Class<M> maskClass, $type$[] a, int offset,
4680 int[] indexMap, int mapOffset, M m) {
4681 $Type$Species vsp = vspecies();
4682 IntVector.IntSpecies isp = IntVector.species(vsp.indexShape());
4683 Objects.requireNonNull(a);
4684 Objects.requireNonNull(indexMap);
4685 m.check(vsp);
4686 Class<? extends $abstractvectortype$> vectorType = vsp.vectorType();
4687
4688 #if[longOrDouble]
4689 if (vsp.laneCount() == 1) {
4690 return $abstractvectortype$.fromArray(vsp, a, offset + indexMap[mapOffset], m);
4691 }
4692
4693 // Index vector: vix[0:n] = k -> offset + indexMap[mapOffset + k]
4694 IntVector vix;
4695 if (isp.laneCount() != vsp.laneCount()) {
4696 // For $Type$MaxVector, if vector length is non-power-of-two or
4697 // 2048 bits, indexShape of $Type$ species is S_MAX_BIT.
4698 // Assume that vector length is 2048, then the lane count of $Type$
4699 // vector is 32. When converting $Type$ species to int species,
4700 // indexShape is still S_MAX_BIT, but the lane count of int vector
4701 // is 64. So when loading index vector (IntVector), only lower half
4702 // of index data is needed.
4703 vix = IntVector
4704 .fromArray(isp, indexMap, mapOffset, IntMaxVector.IntMaxMask.LOWER_HALF_TRUE_MASK)
4705 .add(offset);
4706 } else {
4707 vix = IntVector
4708 .fromArray(isp, indexMap, mapOffset)
4709 .add(offset);
4710 }
4711 #else[longOrDouble]
4712 // Index vector: vix[0:n] = k -> offset + indexMap[mapOffset + k]
4713 IntVector vix = IntVector
4714 .fromArray(isp, indexMap, mapOffset)
4715 .add(offset);
4716 #end[longOrDouble]
4717
4718 // FIXME: Check index under mask controlling.
4719 vix = VectorIntrinsics.checkIndex(vix, a.length);
4720
4721 return VectorSupport.loadWithMap(
4722 vectorType, maskClass, $type$.class, vsp.laneCount(),
4723 isp.vectorType(),
4724 a, ARRAY_BASE, vix, m,
4725 a, offset, indexMap, mapOffset, vsp,
4726 (c, idx, iMap, idy, s, vm) ->
4727 s.vOp(vm, n -> c[idx + iMap[idy+n]]));
4728 }
4729 #end[!byteOrShort]
4730
4731 #if[short]
4732 /*package-private*/
4733 abstract
4734 $abstractvectortype$ fromCharArray0(char[] a, int offset);
4735 @ForceInline
4736 final
4737 $abstractvectortype$ fromCharArray0Template(char[] a, int offset) {
4738 $Type$Species vsp = vspecies();
4739 return VectorSupport.load(
4740 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4741 a, charArrayAddress(a, offset),
4742 a, offset, vsp,
4743 (arr, off, s) -> s.ldOp(arr, off,
4744 (arr_, off_, i) -> (short) arr_[off_ + i]));
4745 }
4746
4747 /*package-private*/
4748 abstract
4749 $abstractvectortype$ fromCharArray0(char[] a, int offset, VectorMask<$Boxtype$> m);
4750 @ForceInline
4751 final
4752 <M extends VectorMask<$Boxtype$>>
4753 $abstractvectortype$ fromCharArray0Template(Class<M> maskClass, char[] a, int offset, M m) {
4754 m.check(species());
4755 $Type$Species vsp = vspecies();
4756 return VectorSupport.loadMasked(
4757 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
4758 a, charArrayAddress(a, offset), m,
4759 a, offset, vsp,
4760 (arr, off, s, vm) -> s.ldOp(arr, off, vm,
4761 (arr_, off_, i) -> (short) arr_[off_ + i]));
4762 }
4763 #end[short]
4764
4765 #if[byte]
4766 /*package-private*/
4767 abstract
4768 $abstractvectortype$ fromBooleanArray0(boolean[] a, int offset);
4769 @ForceInline
4770 final
4771 $abstractvectortype$ fromBooleanArray0Template(boolean[] a, int offset) {
4772 $Type$Species vsp = vspecies();
4773 return VectorSupport.load(
4774 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4775 a, booleanArrayAddress(a, offset),
4776 a, offset, vsp,
4777 (arr, off, s) -> s.ldOp(arr, off,
4778 (arr_, off_, i) -> (byte) (arr_[off_ + i] ? 1 : 0)));
4779 }
4780
4781 /*package-private*/
4782 abstract
4783 $abstractvectortype$ fromBooleanArray0(boolean[] a, int offset, VectorMask<$Boxtype$> m);
4784 @ForceInline
4785 final
4786 <M extends VectorMask<$Boxtype$>>
4787 $abstractvectortype$ fromBooleanArray0Template(Class<M> maskClass, boolean[] a, int offset, M m) {
4788 m.check(species());
4789 $Type$Species vsp = vspecies();
4790 return VectorSupport.loadMasked(
4791 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
4792 a, booleanArrayAddress(a, offset), m,
4793 a, offset, vsp,
4794 (arr, off, s, vm) -> s.ldOp(arr, off, vm,
4795 (arr_, off_, i) -> (byte) (arr_[off_ + i] ? 1 : 0)));
4796 }
4797 #end[byte]
4798
4799 @Override
4800 abstract
4801 $abstractvectortype$ fromByteArray0(byte[] a, int offset);
4802 @ForceInline
4803 final
4804 $abstractvectortype$ fromByteArray0Template(byte[] a, int offset) {
4805 $Type$Species vsp = vspecies();
4806 return VectorSupport.load(
4807 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4808 a, byteArrayAddress(a, offset),
4809 a, offset, vsp,
4810 (arr, off, s) -> {
4811 ByteBuffer wb = wrapper(arr, NATIVE_ENDIAN);
4812 return s.ldOp(wb, off,
4813 (wb_, o, i) -> wb_.get{#if[byte]?(:$Type$(}o + i * $sizeInBytes$));
4814 });
4815 }
4816
4817 abstract
4818 $abstractvectortype$ fromByteArray0(byte[] a, int offset, VectorMask<$Boxtype$> m);
4819 @ForceInline
4820 final
4821 <M extends VectorMask<$Boxtype$>>
4822 $abstractvectortype$ fromByteArray0Template(Class<M> maskClass, byte[] a, int offset, M m) {
4823 $Type$Species vsp = vspecies();
4824 m.check(vsp);
4825 return VectorSupport.loadMasked(
4826 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
4827 a, byteArrayAddress(a, offset), m,
4828 a, offset, vsp,
4829 (arr, off, s, vm) -> {
4830 ByteBuffer wb = wrapper(arr, NATIVE_ENDIAN);
4831 return s.ldOp(wb, off, vm,
4832 (wb_, o, i) -> wb_.get{#if[byte]?(:$Type$(}o + i * $sizeInBytes$));
4833 });
4834 }
4835
4836 abstract
4837 $abstractvectortype$ fromByteBuffer0(ByteBuffer bb, int offset);
4838 @ForceInline
4839 final
4840 $abstractvectortype$ fromByteBuffer0Template(ByteBuffer bb, int offset) {
4841 $Type$Species vsp = vspecies();
4842 return ScopedMemoryAccess.loadFromByteBuffer(
4843 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4844 bb, offset, vsp,
4845 (buf, off, s) -> {
4846 ByteBuffer wb = wrapper(buf, NATIVE_ENDIAN);
4847 return s.ldOp(wb, off,
4848 (wb_, o, i) -> wb_.get{#if[byte]?(:$Type$(}o + i * $sizeInBytes$));
4849 });
4850 }
4851
4852 abstract
4853 $abstractvectortype$ fromByteBuffer0(ByteBuffer bb, int offset, VectorMask<$Boxtype$> m);
4854 @ForceInline
4855 final
4856 <M extends VectorMask<$Boxtype$>>
4857 $abstractvectortype$ fromByteBuffer0Template(Class<M> maskClass, ByteBuffer bb, int offset, M m) {
4858 $Type$Species vsp = vspecies();
4859 m.check(vsp);
4860 return ScopedMemoryAccess.loadFromByteBufferMasked(
4861 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
4862 bb, offset, m, vsp,
4863 (buf, off, s, vm) -> {
4864 ByteBuffer wb = wrapper(buf, NATIVE_ENDIAN);
4865 return s.ldOp(wb, off, vm,
4866 (wb_, o, i) -> wb_.get{#if[byte]?(:$Type$(}o + i * $sizeInBytes$));
4867 });
4868 }
4869
4870 // Unchecked storing operations in native byte order.
4871 // Caller is responsible for applying index checks, masking, and
4872 // byte swapping.
4873
4874 abstract
4875 void intoArray0($type$[] a, int offset);
4876 @ForceInline
4877 final
4878 void intoArray0Template($type$[] a, int offset) {
4879 $Type$Species vsp = vspecies();
4880 VectorSupport.store(
4881 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4882 a, arrayAddress(a, offset),
4883 this, a, offset,
4884 (arr, off, v)
4885 -> v.stOp(arr, off,
4886 (arr_, off_, i, e) -> arr_[off_+i] = e));
4887 }
4888
4889 abstract
4890 void intoArray0($type$[] a, int offset, VectorMask<$Boxtype$> m);
4891 @ForceInline
4892 final
4893 <M extends VectorMask<$Boxtype$>>
4894 void intoArray0Template(Class<M> maskClass, $type$[] a, int offset, M m) {
4895 m.check(species());
4896 $Type$Species vsp = vspecies();
4897 VectorSupport.storeMasked(
4898 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
4899 a, arrayAddress(a, offset),
4900 this, m, a, offset,
4901 (arr, off, v, vm)
4902 -> v.stOp(arr, off, vm,
4903 (arr_, off_, i, e) -> arr_[off_ + i] = e));
4904 }
4905
4906 #if[!byteOrShort]
4907 abstract
4908 void intoArray0($type$[] a, int offset,
4909 int[] indexMap, int mapOffset,
4910 VectorMask<$Boxtype$> m);
4911 @ForceInline
4912 final
4913 <M extends VectorMask<$Boxtype$>>
4914 void intoArray0Template(Class<M> maskClass, $type$[] a, int offset,
4915 int[] indexMap, int mapOffset, M m) {
4916 m.check(species());
4917 $Type$Species vsp = vspecies();
4918 IntVector.IntSpecies isp = IntVector.species(vsp.indexShape());
4919 #if[longOrDouble]
4920 if (vsp.laneCount() == 1) {
4921 intoArray(a, offset + indexMap[mapOffset], m);
4922 return;
4923 }
4924
4925 // Index vector: vix[0:n] = i -> offset + indexMap[mo + i]
4926 IntVector vix;
4927 if (isp.laneCount() != vsp.laneCount()) {
4928 // For $Type$MaxVector, if vector length is 2048 bits, indexShape
4929 // of $Type$ species is S_MAX_BIT. and the lane count of $Type$
4930 // vector is 32. When converting $Type$ species to int species,
4931 // indexShape is still S_MAX_BIT, but the lane count of int vector
4932 // is 64. So when loading index vector (IntVector), only lower half
4933 // of index data is needed.
4934 vix = IntVector
4935 .fromArray(isp, indexMap, mapOffset, IntMaxVector.IntMaxMask.LOWER_HALF_TRUE_MASK)
4936 .add(offset);
4937 } else {
4938 vix = IntVector
4939 .fromArray(isp, indexMap, mapOffset)
4940 .add(offset);
4941 }
4942
4943 #else[longOrDouble]
4944 // Index vector: vix[0:n] = i -> offset + indexMap[mo + i]
4945 IntVector vix = IntVector
4946 .fromArray(isp, indexMap, mapOffset)
4947 .add(offset);
4948 #end[longOrDouble]
4949
4950 // FIXME: Check index under mask controlling.
4951 vix = VectorIntrinsics.checkIndex(vix, a.length);
4952
4953 VectorSupport.storeWithMap(
4954 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
4955 isp.vectorType(),
4956 a, arrayAddress(a, 0), vix,
4957 this, m,
4958 a, offset, indexMap, mapOffset,
4959 (arr, off, v, map, mo, vm)
4960 -> v.stOp(arr, off, vm,
4961 (arr_, off_, i, e) -> {
4962 int j = map[mo + i];
4963 arr[off + j] = e;
4964 }));
4965 }
4966 #end[!byteOrShort]
4967
4968 #if[byte]
4969 abstract
4970 void intoBooleanArray0(boolean[] a, int offset, VectorMask<$Boxtype$> m);
4971 @ForceInline
4972 final
4973 <M extends VectorMask<$Boxtype$>>
4974 void intoBooleanArray0Template(Class<M> maskClass, boolean[] a, int offset, M m) {
4975 m.check(species());
4976 $Type$Species vsp = vspecies();
4977 ByteVector normalized = this.and((byte) 1);
4978 VectorSupport.storeMasked(
4979 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
4980 a, booleanArrayAddress(a, offset),
4981 normalized, m, a, offset,
4982 (arr, off, v, vm)
4983 -> v.stOp(arr, off, vm,
4984 (arr_, off_, i, e) -> arr_[off_ + i] = (e & 1) != 0));
4985 }
4986 #end[byte]
4987
4988 abstract
4989 void intoByteArray0(byte[] a, int offset);
4990 @ForceInline
4991 final
4992 void intoByteArray0Template(byte[] a, int offset) {
4993 $Type$Species vsp = vspecies();
4994 VectorSupport.store(
4995 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
4996 a, byteArrayAddress(a, offset),
4997 this, a, offset,
4998 (arr, off, v) -> {
4999 ByteBuffer wb = wrapper(arr, NATIVE_ENDIAN);
5000 v.stOp(wb, off,
5001 (tb_, o, i, e) -> tb_.put{#if[byte]?(:$Type$(}o + i * $sizeInBytes$, e));
5002 });
5003 }
5004
5005 abstract
5006 void intoByteArray0(byte[] a, int offset, VectorMask<$Boxtype$> m);
5007 @ForceInline
5008 final
5009 <M extends VectorMask<$Boxtype$>>
5010 void intoByteArray0Template(Class<M> maskClass, byte[] a, int offset, M m) {
5011 $Type$Species vsp = vspecies();
5012 m.check(vsp);
5013 VectorSupport.storeMasked(
5014 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
5015 a, byteArrayAddress(a, offset),
5016 this, m, a, offset,
5017 (arr, off, v, vm) -> {
5018 ByteBuffer wb = wrapper(arr, NATIVE_ENDIAN);
5019 v.stOp(wb, off, vm,
5020 (tb_, o, i, e) -> tb_.put{#if[byte]?(:$Type$(}o + i * $sizeInBytes$, e));
5021 });
5022 }
5023
5024 @ForceInline
5025 final
5026 void intoByteBuffer0(ByteBuffer bb, int offset) {
5027 $Type$Species vsp = vspecies();
5028 ScopedMemoryAccess.storeIntoByteBuffer(
5029 vsp.vectorType(), vsp.elementType(), vsp.laneCount(),
5030 this, bb, offset,
5031 (buf, off, v) -> {
5032 ByteBuffer wb = wrapper(buf, NATIVE_ENDIAN);
5033 v.stOp(wb, off,
5034 (wb_, o, i, e) -> wb_.put{#if[byte]?(:$Type$(}o + i * $sizeInBytes$, e));
5035 });
5036 }
5037
5038 abstract
5039 void intoByteBuffer0(ByteBuffer bb, int offset, VectorMask<$Boxtype$> m);
5040 @ForceInline
5041 final
5042 <M extends VectorMask<$Boxtype$>>
5043 void intoByteBuffer0Template(Class<M> maskClass, ByteBuffer bb, int offset, M m) {
5044 $Type$Species vsp = vspecies();
5045 m.check(vsp);
5046 ScopedMemoryAccess.storeIntoByteBufferMasked(
5047 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
5048 this, m, bb, offset,
5049 (buf, off, v, vm) -> {
5050 ByteBuffer wb = wrapper(buf, NATIVE_ENDIAN);
5051 v.stOp(wb, off, vm,
5052 (wb_, o, i, e) -> wb_.put{#if[byte]?(:$Type$(}o + i * $sizeInBytes$, e));
5053 });
5054 }
5055
5056 #if[short]
5057 /*package-private*/
5058 abstract
5059 void intoCharArray0(char[] a, int offset, VectorMask<$Boxtype$> m);
5060 @ForceInline
5061 final
5062 <M extends VectorMask<$Boxtype$>>
5063 void intoCharArray0Template(Class<M> maskClass, char[] a, int offset, M m) {
5064 m.check(species());
5065 $Type$Species vsp = vspecies();
5066 VectorSupport.storeMasked(
5067 vsp.vectorType(), maskClass, vsp.elementType(), vsp.laneCount(),
5068 a, charArrayAddress(a, offset),
5069 this, m, a, offset,
5070 (arr, off, v, vm)
5071 -> v.stOp(arr, off, vm,
5072 (arr_, off_, i, e) -> arr_[off_ + i] = (char) e));
5073 }
5074 #end[short]
5075
5076 // End of low-level memory operations.
5077
5078 private static
5079 void checkMaskFromIndexSize(int offset,
5080 $Type$Species vsp,
5081 VectorMask<$Boxtype$> m,
5082 int scale,
5083 int limit) {
5084 ((AbstractMask<$Boxtype$>)m)
5085 .checkIndexByLane(offset, limit, vsp.iota(), scale);
5086 }
5087
5088 @ForceInline
5089 private void conditionalStoreNYI(int offset,
5090 $Type$Species vsp,
5091 VectorMask<$Boxtype$> m,
5092 int scale,
5093 int limit) {
5094 if (offset < 0 || offset + vsp.laneCount() * scale > limit) {
5095 String msg =
5096 String.format("unimplemented: store @%d in [0..%d), %s in %s",
5097 offset, limit, m, vsp);
5098 throw new AssertionError(msg);
5099 }
5100 }
5101
5102 /*package-private*/
5103 @Override
5104 @ForceInline
5105 final
5106 $abstractvectortype$ maybeSwap(ByteOrder bo) {
5107 #if[!byte]
5108 if (bo != NATIVE_ENDIAN) {
5109 return this.reinterpretAsBytes()
5110 .rearrange(swapBytesShuffle())
5111 .reinterpretAs$Type$s();
5112 }
5113 #end[!byte]
5114 return this;
5115 }
5116
5117 static final int ARRAY_SHIFT =
5118 31 - Integer.numberOfLeadingZeros(Unsafe.ARRAY_$TYPE$_INDEX_SCALE);
5119 static final long ARRAY_BASE =
5120 Unsafe.ARRAY_$TYPE$_BASE_OFFSET;
5121
5122 @ForceInline
5123 static long arrayAddress($type$[] a, int index) {
5124 return ARRAY_BASE + (((long)index) << ARRAY_SHIFT);
5125 }
5126
5127 #if[short]
5128 static final int ARRAY_CHAR_SHIFT =
5129 31 - Integer.numberOfLeadingZeros(Unsafe.ARRAY_CHAR_INDEX_SCALE);
5130 static final long ARRAY_CHAR_BASE =
5131 Unsafe.ARRAY_CHAR_BASE_OFFSET;
5132
5133 @ForceInline
5134 static long charArrayAddress(char[] a, int index) {
5135 return ARRAY_CHAR_BASE + (((long)index) << ARRAY_CHAR_SHIFT);
5136 }
5137 #end[short]
5138
5139 #if[byte]
5140 static final int ARRAY_BOOLEAN_SHIFT =
5141 31 - Integer.numberOfLeadingZeros(Unsafe.ARRAY_BOOLEAN_INDEX_SCALE);
5142 static final long ARRAY_BOOLEAN_BASE =
5143 Unsafe.ARRAY_BOOLEAN_BASE_OFFSET;
5144
5145 @ForceInline
5146 static long booleanArrayAddress(boolean[] a, int index) {
5147 return ARRAY_BOOLEAN_BASE + (((long)index) << ARRAY_BOOLEAN_SHIFT);
5148 }
5149 #end[byte]
5150
5151 @ForceInline
5152 static long byteArrayAddress(byte[] a, int index) {
5153 return Unsafe.ARRAY_BYTE_BASE_OFFSET + index;
5154 }
5155
5156 // ================================================
5157
5158 /// Reinterpreting view methods:
5159 // lanewise reinterpret: viewAsXVector()
5160 // keep shape, redraw lanes: reinterpretAsEs()
5161
5162 /**
5163 * {@inheritDoc} <!--workaround-->
5164 */
5165 @ForceInline
5166 @Override
5167 public final ByteVector reinterpretAsBytes() {
5168 #if[byte]
5169 return this;
5170 #else[byte]
5171 // Going to ByteVector, pay close attention to byte order.
5172 assert(REGISTER_ENDIAN == ByteOrder.LITTLE_ENDIAN);
5173 return asByteVectorRaw();
5174 //return asByteVectorRaw().rearrange(swapBytesShuffle());
5175 #end[byte]
5176 }
5177
5178 /**
5179 * {@inheritDoc} <!--workaround-->
5180 */
5181 @ForceInline
5182 @Override
5183 public final $Bitstype$Vector viewAsIntegralLanes() {
5184 #if[BITWISE]
5185 return this;
5186 #else[BITWISE]
5187 LaneType ilt = LaneType.$TYPE$.asIntegral();
5188 return ($Bitstype$Vector) asVectorRaw(ilt);
5189 #end[BITWISE]
5190 }
5191
5192 /**
5193 * {@inheritDoc} <!--workaround-->
5194 #if[byteOrShort]
5195 *
5196 * @implNote This method always throws
5197 * {@code UnsupportedOperationException}, because there is no floating
5198 * point type of the same size as {@code $type$}. The return type
5199 * of this method is arbitrarily designated as
5200 * {@code Vector<?>}. Future versions of this API may change the return
5201 * type if additional floating point types become available.
5202 #end[byteOrShort]
5203 */
5204 @ForceInline
5205 @Override
5206 public final
5207 {#if[byteOrShort]?Vector<?>:$Fptype$Vector}
5208 viewAsFloatingLanes() {
5209 #if[FP]
5210 return this;
5211 #else[FP]
5212 LaneType flt = LaneType.$TYPE$.asFloating();
5213 #if[!byteOrShort]
5214 return ($Fptype$Vector) asVectorRaw(flt);
5215 #else[!byteOrShort]
5216 // asFloating() will throw UnsupportedOperationException for the unsupported type $type$
5217 throw new AssertionError("Cannot reach here");
5218 #end[!byteOrShort]
5219 #end[FP]
5220 }
5221
5222 // ================================================
5223
5224 /// Object methods: toString, equals, hashCode
5225 //
5226 // Object methods are defined as if via Arrays.toString, etc.,
5227 // is applied to the array of elements. Two equal vectors
5228 // are required to have equal species and equal lane values.
5229
5230 /**
5231 * Returns a string representation of this vector, of the form
5232 * {@code "[0,1,2...]"}, reporting the lane values of this vector,
5233 * in lane order.
5234 *
5235 * The string is produced as if by a call to {@link
5236 * java.util.Arrays#toString($type$[]) Arrays.toString()},
5237 * as appropriate to the {@code $type$} array returned by
5238 * {@link #toArray this.toArray()}.
5239 *
5240 * @return a string of the form {@code "[0,1,2...]"}
5241 * reporting the lane values of this vector
5242 */
5243 @Override
5244 @ForceInline
5245 public final
5246 String toString() {
5247 // now that toArray is strongly typed, we can define this
5248 return Arrays.toString(toArray());
5249 }
5250
5251 /**
5252 * {@inheritDoc} <!--workaround-->
5253 */
5254 @Override
5255 @ForceInline
5256 public final
5257 boolean equals(Object obj) {
5258 if (obj instanceof Vector) {
5259 Vector<?> that = (Vector<?>) obj;
5260 if (this.species().equals(that.species())) {
5261 return this.eq(that.check(this.species())).allTrue();
5262 }
5263 }
5264 return false;
5265 }
5266
5267 /**
5268 * {@inheritDoc} <!--workaround-->
5269 */
5270 @Override
5271 @ForceInline
5272 public final
5273 int hashCode() {
5274 // now that toArray is strongly typed, we can define this
5275 return Objects.hash(species(), Arrays.hashCode(toArray()));
5276 }
5277
5278 // ================================================
5279
5280 // Species
5281
5282 /**
5283 * Class representing {@link $abstractvectortype$}'s of the same {@link VectorShape VectorShape}.
5284 */
5285 /*package-private*/
5286 static final class $Type$Species extends AbstractSpecies<$Boxtype$> {
5287 private $Type$Species(VectorShape shape,
5288 Class<? extends $abstractvectortype$> vectorType,
5289 Class<? extends AbstractMask<$Boxtype$>> maskType,
5290 Function<Object, $abstractvectortype$> vectorFactory) {
5291 super(shape, LaneType.of($type$.class),
5292 vectorType, maskType,
5293 vectorFactory);
5294 assert(this.elementSize() == $Boxtype$.SIZE);
5295 }
5296
5297 // Specializing overrides:
5298
5299 @Override
5300 @ForceInline
5301 public final Class<$Boxtype$> elementType() {
5302 return $type$.class;
5303 }
5304
5305 @Override
5306 @ForceInline
5307 final Class<$Boxtype$> genericElementType() {
5308 return $Boxtype$.class;
5309 }
5310
5311 @SuppressWarnings("unchecked")
5312 @Override
5313 @ForceInline
5314 public final Class<? extends $Type$Vector> vectorType() {
5315 return (Class<? extends $Type$Vector>) vectorType;
5316 }
5317
5318 @Override
5319 @ForceInline
5320 public final long checkValue(long e) {
5321 longToElementBits(e); // only for exception
5322 return e;
5323 }
5324
5325 /*package-private*/
5326 @Override
5327 @ForceInline
5328 final $abstractvectortype$ broadcastBits(long bits) {
5329 return ($abstractvectortype$)
5330 VectorSupport.broadcastCoerced(
5331 vectorType, $type$.class, laneCount,
5332 bits, this,
5333 (bits_, s_) -> s_.rvOp(i -> bits_));
5334 }
5335
5336 /*package-private*/
5337 @ForceInline
5338 {#if[long]?public }final $abstractvectortype$ broadcast($type$ e) {
5339 return broadcastBits(toBits(e));
5340 }
5341
5342 #if[!long]
5343 @Override
5344 @ForceInline
5345 public final $abstractvectortype$ broadcast(long e) {
5346 return broadcastBits(longToElementBits(e));
5347 }
5348 #end[!long]
5349
5350 /*package-private*/
5351 final @Override
5352 @ForceInline
5353 long longToElementBits(long value) {
5354 #if[long]
5355 // In this case, the conversion can never fail.
5356 return value;
5357 #else[long]
5358 // Do the conversion, and then test it for failure.
5359 $type$ e = ($type$) value;
5360 if ((long) e != value) {
5361 throw badElementBits(value, e);
5362 }
5363 return toBits(e);
5364 #end[long]
5365 }
5366
5367 /*package-private*/
5368 @ForceInline
5369 static long toIntegralChecked($type$ e, boolean convertToInt) {
5370 long value = convertToInt ? (int) e : (long) e;
5371 if (($type$) value != e) {
5372 throw badArrayBits(e, convertToInt, value);
5373 }
5374 return value;
5375 }
5376
5377 /* this non-public one is for internal conversions */
5378 @Override
5379 @ForceInline
5380 final $abstractvectortype$ fromIntValues(int[] values) {
5381 VectorIntrinsics.requireLength(values.length, laneCount);
5382 $type$[] va = new $type$[laneCount()];
5383 for (int i = 0; i < va.length; i++) {
5384 int lv = values[i];
5385 $type$ v = ($type$) lv;
5386 va[i] = v;
5387 if ((int)v != lv) {
5388 throw badElementBits(lv, v);
5389 }
5390 }
5391 return dummyVector().fromArray0(va, 0);
5392 }
5393
5394 // Virtual constructors
5395
5396 @ForceInline
5397 @Override final
5398 public $abstractvectortype$ fromArray(Object a, int offset) {
5399 // User entry point: Be careful with inputs.
5400 return $abstractvectortype$
5401 .fromArray(this, ($type$[]) a, offset);
5402 }
5403
5404 @ForceInline
5405 @Override final
5406 $abstractvectortype$ dummyVector() {
5407 return ($abstractvectortype$) super.dummyVector();
5408 }
5409
5410 /*package-private*/
5411 final @Override
5412 @ForceInline
5413 $abstractvectortype$ rvOp(RVOp f) {
5414 $type$[] res = new $type$[laneCount()];
5415 for (int i = 0; i < res.length; i++) {
5416 $bitstype$ bits = {#if[!long]?($bitstype$)} f.apply(i);
5417 res[i] = fromBits(bits);
5418 }
5419 return dummyVector().vectorFactory(res);
5420 }
5421
5422 $Type$Vector vOp(FVOp f) {
5423 $type$[] res = new $type$[laneCount()];
5424 for (int i = 0; i < res.length; i++) {
5425 res[i] = f.apply(i);
5426 }
5427 return dummyVector().vectorFactory(res);
5428 }
5429
5430 $Type$Vector vOp(VectorMask<$Boxtype$> m, FVOp f) {
5431 $type$[] res = new $type$[laneCount()];
5432 boolean[] mbits = ((AbstractMask<$Boxtype$>)m).getBits();
5433 for (int i = 0; i < res.length; i++) {
5434 if (mbits[i]) {
5435 res[i] = f.apply(i);
5436 }
5437 }
5438 return dummyVector().vectorFactory(res);
5439 }
5440
5441 /*package-private*/
5442 @ForceInline
5443 <M> $abstractvectortype$ ldOp(M memory, int offset,
5444 FLdOp<M> f) {
5445 return dummyVector().ldOp(memory, offset, f);
5446 }
5447
5448 /*package-private*/
5449 @ForceInline
5450 <M> $abstractvectortype$ ldOp(M memory, int offset,
5451 VectorMask<$Boxtype$> m,
5452 FLdOp<M> f) {
5453 return dummyVector().ldOp(memory, offset, m, f);
5454 }
5455
5456 /*package-private*/
5457 @ForceInline
5458 <M> void stOp(M memory, int offset, FStOp<M> f) {
5459 dummyVector().stOp(memory, offset, f);
5460 }
5461
5462 /*package-private*/
5463 @ForceInline
5464 <M> void stOp(M memory, int offset,
5465 AbstractMask<$Boxtype$> m,
5466 FStOp<M> f) {
5467 dummyVector().stOp(memory, offset, m, f);
5468 }
5469
5470 // N.B. Make sure these constant vectors and
5471 // masks load up correctly into registers.
5472 //
5473 // Also, see if we can avoid all that switching.
5474 // Could we cache both vectors and both masks in
5475 // this species object?
5476
5477 // Zero and iota vector access
5478 @Override
5479 @ForceInline
5480 public final $abstractvectortype$ zero() {
5481 if ((Class<?>) vectorType() == $Type$MaxVector.class)
5482 return $Type$MaxVector.ZERO;
5483 switch (vectorBitSize()) {
5484 case 64: return $Type$64Vector.ZERO;
5485 case 128: return $Type$128Vector.ZERO;
5486 case 256: return $Type$256Vector.ZERO;
5487 case 512: return $Type$512Vector.ZERO;
5488 }
5489 throw new AssertionError();
5490 }
5491
5492 @Override
5493 @ForceInline
5494 public final $abstractvectortype$ iota() {
5495 if ((Class<?>) vectorType() == $Type$MaxVector.class)
5496 return $Type$MaxVector.IOTA;
5497 switch (vectorBitSize()) {
5498 case 64: return $Type$64Vector.IOTA;
5499 case 128: return $Type$128Vector.IOTA;
5500 case 256: return $Type$256Vector.IOTA;
5501 case 512: return $Type$512Vector.IOTA;
5502 }
5503 throw new AssertionError();
5504 }
5505
5506 // Mask access
5507 @Override
5508 @ForceInline
5509 public final VectorMask<$Boxtype$> maskAll(boolean bit) {
5510 if ((Class<?>) vectorType() == $Type$MaxVector.class)
5511 return $Type$MaxVector.$Type$MaxMask.maskAll(bit);
5512 switch (vectorBitSize()) {
5513 case 64: return $Type$64Vector.$Type$64Mask.maskAll(bit);
5514 case 128: return $Type$128Vector.$Type$128Mask.maskAll(bit);
5515 case 256: return $Type$256Vector.$Type$256Mask.maskAll(bit);
5516 case 512: return $Type$512Vector.$Type$512Mask.maskAll(bit);
5517 }
5518 throw new AssertionError();
5519 }
5520 }
5521
5522 /**
5523 * Finds a species for an element type of {@code $type$} and shape.
5524 *
5525 * @param s the shape
5526 * @return a species for an element type of {@code $type$} and shape
5527 * @throws IllegalArgumentException if no such species exists for the shape
5528 */
5529 static $Type$Species species(VectorShape s) {
5530 Objects.requireNonNull(s);
5531 switch (s) {
5532 case S_64_BIT: return ($Type$Species) SPECIES_64;
5533 case S_128_BIT: return ($Type$Species) SPECIES_128;
5534 case S_256_BIT: return ($Type$Species) SPECIES_256;
5535 case S_512_BIT: return ($Type$Species) SPECIES_512;
5536 case S_Max_BIT: return ($Type$Species) SPECIES_MAX;
5537 default: throw new IllegalArgumentException("Bad shape: " + s);
5538 }
5539 }
5540
5541 /** Species representing {@link $Type$Vector}s of {@link VectorShape#S_64_BIT VectorShape.S_64_BIT}. */
5542 public static final VectorSpecies<$Boxtype$> SPECIES_64
5543 = new $Type$Species(VectorShape.S_64_BIT,
5544 $Type$64Vector.class,
5545 $Type$64Vector.$Type$64Mask.class,
5546 $Type$64Vector::new);
5547
5548 /** Species representing {@link $Type$Vector}s of {@link VectorShape#S_128_BIT VectorShape.S_128_BIT}. */
5549 public static final VectorSpecies<$Boxtype$> SPECIES_128
5550 = new $Type$Species(VectorShape.S_128_BIT,
5551 $Type$128Vector.class,
5552 $Type$128Vector.$Type$128Mask.class,
5553 $Type$128Vector::new);
5554
5555 /** Species representing {@link $Type$Vector}s of {@link VectorShape#S_256_BIT VectorShape.S_256_BIT}. */
5556 public static final VectorSpecies<$Boxtype$> SPECIES_256
5557 = new $Type$Species(VectorShape.S_256_BIT,
5558 $Type$256Vector.class,
5559 $Type$256Vector.$Type$256Mask.class,
5560 $Type$256Vector::new);
5561
5562 /** Species representing {@link $Type$Vector}s of {@link VectorShape#S_512_BIT VectorShape.S_512_BIT}. */
5563 public static final VectorSpecies<$Boxtype$> SPECIES_512
5564 = new $Type$Species(VectorShape.S_512_BIT,
5565 $Type$512Vector.class,
5566 $Type$512Vector.$Type$512Mask.class,
5567 $Type$512Vector::new);
5568
5569 /** Species representing {@link $Type$Vector}s of {@link VectorShape#S_Max_BIT VectorShape.S_Max_BIT}. */
5570 public static final VectorSpecies<$Boxtype$> SPECIES_MAX
5571 = new $Type$Species(VectorShape.S_Max_BIT,
5572 $Type$MaxVector.class,
5573 $Type$MaxVector.$Type$MaxMask.class,
5574 $Type$MaxVector::new);
5575
5576 /**
5577 * Preferred species for {@link $Type$Vector}s.
5578 * A preferred species is a species of maximal bit-size for the platform.
5579 */
5580 public static final VectorSpecies<$Boxtype$> SPECIES_PREFERRED
5581 = ($Type$Species) VectorSpecies.ofPreferred($type$.class);
5582 }