1 /*
2 * Copyright (c) 2019, 2022, 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.
8 *
9 * This code is distributed in the hope that it will be useful, but WITHOUT
10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
11 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
12 * version 2 for more details (a copy is included in the LICENSE file that
13 * accompanied this code).
14 *
15 * You should have received a copy of the GNU General Public License version
16 * 2 along with this work; if not, write to the Free Software Foundation,
17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
18 *
19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
20 * or visit www.oracle.com if you need additional information or have any
21 * questions.
22 */
23
24 package org.openjdk.bench.jdk.incubator.vector.crypto;
25
26 import jdk.incubator.foreign.MemorySegment;
27 import org.openjdk.jmh.annotations.*;
28 import jdk.incubator.vector.*;
29
30 import java.nio.ByteOrder;
31 import java.util.Arrays;
32
33 @State(Scope.Thread)
34 @BenchmarkMode(Mode.Throughput)
35 @Fork(value = 1, jvmArgsPrepend = {"--add-modules=jdk.incubator.vector"})
36 @Warmup(iterations = 3, time = 3)
37 @Measurement(iterations = 8, time = 2)
38 public class Poly1305Bench {
39
40 @Param({"16384", "65536"})
41 private int dataSize;
42
43 private Poly1305Vector poly1305_S128 = makePoly1305(VectorShape.S_128_BIT);
44 private Poly1305Vector poly1305_S256 = makePoly1305(VectorShape.S_256_BIT);
45 private Poly1305Vector poly1305_S512 = makePoly1305(VectorShape.S_512_BIT);
46
47 private byte[] in;
48 private byte[] out = new byte[16];
49 private byte[] key = new byte[32];
50
51 private static Poly1305Vector makePoly1305(VectorShape shape) {
52 Poly1305Vector poly = new Poly1305Vector(shape);
53 runKAT(poly);
54 return poly;
55 }
56
57 @Setup
58 public void setup() {
59 in = new byte[dataSize];
60 }
61
62 @Benchmark
63 public void auth128() {
64 poly1305_S128.computeTag(key, in, out);
65 }
66
67 @Benchmark
68 public void auth256() {
69 poly1305_S256.computeTag(key, in, out);
70 }
71
72 @Benchmark
73 public void auth512() {
74 poly1305_S512.computeTag(key, in, out);
75 }
76
77 private static class Poly1305Vector {
78
79 private static final int BITS_PER_LIMB = 26;
80 private static final int LIMB_MASK = (1 << BITS_PER_LIMB) - 1;
81 private static final int KEY_LENGTH = 32;
82 private static final int RS_LENGTH = KEY_LENGTH / 2;
83
84 private final VectorSpecies<Long> longSpecies;
85 private final VectorSpecies<Integer> intSpecies;
86 private final int vectorWidth;
87 private final int parBlockCount;
88
89 private final VectorShuffle<Long> inShuffle0;
90 private final VectorShuffle<Long> inShuffle1;
91 private final VectorMask<Long> inMask;
92
93 public Poly1305Vector(VectorShape shape) {
94
95 this.longSpecies = VectorSpecies.of(long.class, shape);
96 int intSize = shape.vectorBitSize() / 2;
97 VectorShape intShape = VectorShape.forBitSize(intSize);
98 this.intSpecies = VectorSpecies.of(int.class, intShape);
99 this.vectorWidth = longSpecies.length();
100 this.parBlockCount = vectorWidth * 16;
101
102 this.inShuffle0 = makeInShuffle0();
103 this.inShuffle1 = makeInShuffle1();
104 this.inMask = makeInMask();
105 }
106
107 private VectorShuffle<Long> makeInShuffle0() {
108 int[] indexArr = new int[vectorWidth];
109 for (int i = 0; i < indexArr.length; i++) {
110 indexArr[i] = (2 * i) % vectorWidth;
111 }
112 return VectorShuffle.fromArray(longSpecies, indexArr, 0);
113 }
114 private VectorShuffle<Long> makeInShuffle1() {
115 int[] indexArr = new int[vectorWidth];
116 for (int i = 0; i < indexArr.length; i++) {
117 indexArr[i] = ((2 * i) % vectorWidth) + 1;
118 }
119 return VectorShuffle.fromArray(longSpecies, indexArr, 0);
120 }
121 private VectorMask<Long> makeInMask() {
122 boolean[] maskArr = new boolean[vectorWidth];
123 for (int i = vectorWidth / 2; i < vectorWidth; i++) {
124 maskArr[i] = true;
125 }
126 return VectorMask.fromArray(longSpecies, maskArr, 0);
127 }
128
129 private static int[] fromByteArray(byte[] buf) {
130 int[] result = new int[5];
131
132 result[0]
133 = (buf[0] & 0xFF)
134 + ((buf[1] & 0xFF) << 8)
135 + ((buf[2] & 0xFF) << 16)
136 + ((buf[3] & 0x03) << 24);
137 result[1]
138 = ((buf[3] & 0xFF) >> 2)
139 + ((buf[4] & 0xFF) << 6)
140 + ((buf[5] & 0xFF) << 14)
141 + ((buf[6] & 0x0F) << 22);
142 result[2]
143 = ((buf[6] & 0xFF) >> 4)
144 + ((buf[7] & 0xFF) << 4)
145 + ((buf[8] & 0xFF) << 12)
146 + ((buf[9] & 0x3F) << 20);
147 result[3]
148 = ((buf[9] & 0xFF) >> 6)
149 + ((buf[10] & 0xFF) << 2)
150 + ((buf[11] & 0xFF) << 10)
151 + ((buf[12] & 0xFF) << 18);
152 result[4]
153 = (buf[13] & 0xFF)
154 + ((buf[14] & 0xFF) << 8)
155 + ((buf[15] & 0xFF) << 16);
156
157 return result;
158 }
159
160 private static void toByteArray(long v0, long v1, long v2, long v3,
161 long v4, byte[] dst) {
162
163 dst[0] = (byte) v0;
164 v0 >>= 8;
165 dst[1] = (byte) v0;
166 v0 >>= 8;
167 dst[2] = (byte) v0;
168 v0 >>= 8;
169 dst[3] = (byte) v0;
170
171 dst[3] += (v1 & 0x3F) << 2;
172 v1 >>= 6;
173 dst[4] = (byte) v1;
174 v1 >>= 8;
175 dst[5] = (byte) v1;
176 v1 >>= 8;
177 dst[6] = (byte) v1;
178
179 dst[6] += (v2 & 0xF) << 4;
180 v2 >>= 4;
181 dst[7] = (byte) v2;
182 v2 >>= 8;
183 dst[8] = (byte) v2;
184 v2 >>= 8;
185 dst[9] = (byte) v2;
186
187 dst[9] += (v3 & 0x3) << 6;
188 v3 >>= 2;
189 dst[10] = (byte) v3;
190 v3 >>= 8;
191 dst[11] = (byte) v3;
192 v3 >>= 8;
193 dst[12] = (byte) v3;
194
195 dst[13] = (byte) v4;
196 v4 >>= 8;
197 dst[14] = (byte) v4;
198 v4 >>= 8;
199 dst[15] = (byte) v4;
200 }
201
202 protected static long carryValue(long x) {
203 return x >> BITS_PER_LIMB;
204 }
205
206 public static void carryReduce(int[] r, long c0, long c1, long c2,
207 long c3, long c4) {
208
209 long c;
210
211 c = carryValue(c3); c3 &= LIMB_MASK; c4 += c;
212 c = carryValue(c4); c4 &= LIMB_MASK; c0 += c * 5;
213 c = carryValue(c0); c0 &= LIMB_MASK; c1 += c;
214 c = carryValue(c1); c1 &= LIMB_MASK; c2 += c;
215 c = carryValue(c2); c2 &= LIMB_MASK; c3 += c;
216 c = carryValue(c3); c3 &= LIMB_MASK; c4 += c;
217
218 r[0] = (int) c0;
219 r[1] = (int) c1;
220 r[2] = (int) c2;
221 r[3] = (int) c3;
222 r[4] = (int) c4;
223 }
224
225 private int[] multiply(int[] a, int[] b) {
226 int[] result = new int[5];
227
228 long a0 = a[0];
229 long a1 = a[1];
230 long a2 = a[2];
231 long a3 = a[3];
232 long a4 = a[4];
233
234 long c0 = (a0 * b[0]) + 5 * (a1 * b[4]) + 5 * (a2 * b[3]) +
235 5 * (a3 * b[2]) + 5 * (a4 * b[1]);
236 long c1 = (a0 * b[1]) + (a1 * b[0]) + 5 * (a2 * b[4]) +
237 5 * (a3 * b[3]) + 5 * (a4 * b[2]);
238 long c2 = (a0 * b[2]) + (a1 * b[1]) + (a2 * b[0]) +
239 5 * (a3 * b[4]) + 5 * (a4 * b[3]);
240 long c3 = (a0 * b[3]) + (a1 * b[2]) + (a2 * b[1]) + (a3 * b[0]) +
241 5 * (a4 * b[4]);
242 long c4 = (a0 * b[4]) + (a1 * b[3]) + (a2 * b[2]) + (a3 * b[1]) +
243 (a4 * b[0]);
244
245 carryReduce(result, c0, c1, c2, c3, c4);
246
247 return result;
248 }
249
250 private LongVector rPowerVec(int[][] r, long[] temp, int maxIndex,
251 int secondIndex) {
252
253 for (int i = 0; i < temp.length; i++) {
254 temp[i] = r[maxIndex - i][secondIndex];
255 }
256 return LongVector.fromArray(longSpecies, temp, 0);
257 }
258
259 public void computeTag(byte[] key, byte[] msg, byte[] out) {
260
261 byte[] keyBytes = key.clone();
262
263 // setup key values
264 // Clamp the bytes in the "r" half of the key.
265 keyBytes[3] &= 15;
266 keyBytes[7] &= 15;
267 keyBytes[11] &= 15;
268 keyBytes[15] &= 15;
269 keyBytes[4] &= 252;
270 keyBytes[8] &= 252;
271 keyBytes[12] &= 252;
272
273 // Create IntegerModuloP elements from the r and s values
274 int[][] r = new int[vectorWidth][];
275 r[0] = fromByteArray(keyBytes);
276 for (int i = 1; i < vectorWidth; i++) {
277 r[i] = multiply(r[i - 1], r[0]);
278 }
279
280 int rUpIndex = vectorWidth - 1;
281 IntVector rUp0_int = IntVector.broadcast(intSpecies, r[rUpIndex][0]);
282 IntVector rUp1_int = IntVector.broadcast(intSpecies, r[rUpIndex][1]);
283 IntVector rUp2_int = IntVector.broadcast(intSpecies, r[rUpIndex][2]);
284 IntVector rUp3_int = IntVector.broadcast(intSpecies, r[rUpIndex][3]);
285 IntVector rUp4_int = IntVector.broadcast(intSpecies, r[rUpIndex][4]);
286
287 IntVector r5Up1_int = rUp1_int.mul(5);
288 IntVector r5Up2_int = rUp2_int.mul(5);
289 IntVector r5Up3_int = rUp3_int.mul(5);
290 IntVector r5Up4_int = rUp4_int.mul(5);
291
292 MemorySegment msMsg = MemorySegment.ofArray(msg);
293 LongVector longMsg0 = LongVector.fromMemorySegment(longSpecies, msMsg, 0, ByteOrder.LITTLE_ENDIAN);
294 LongVector longMsg1 =
295 LongVector.fromMemorySegment(longSpecies, msMsg, vectorWidth * 8L, ByteOrder.LITTLE_ENDIAN);
296
297 LongVector inAlign0 =
298 longMsg0.rearrange(inShuffle0).blend(longMsg1.rearrange(inShuffle0), inMask);
299 LongVector inAlign1 =
300 longMsg0.rearrange(inShuffle1).blend(longMsg1.rearrange(inShuffle1), inMask);
301
302 IntVector a0 = (IntVector)
303 inAlign0.and(LIMB_MASK).castShape(intSpecies, 0);
304 IntVector a1 = (IntVector)
305 inAlign0.lanewise(VectorOperators.LSHR,26).and(LIMB_MASK).castShape(intSpecies, 0);
306 IntVector a2 = (IntVector)
307 inAlign0.lanewise(VectorOperators.LSHR,52).and(0xFFF).castShape(intSpecies, 0);
308 a2 = a2.or(inAlign1.and(0x3FFF).lanewise(VectorOperators.LSHL,12).castShape(intSpecies, 0));
309 IntVector a3 = (IntVector)
310 inAlign1.lanewise(VectorOperators.LSHR,14).and(LIMB_MASK).castShape(intSpecies, 0);
311 IntVector a4 = (IntVector)
312 inAlign1.lanewise(VectorOperators.LSHR,40).and(0xFFFFFF).castShape(intSpecies, 0);
313 a4 = a4.or(1 << 24);
314
315 int numParBlocks = msg.length / parBlockCount - 1;
316 for (int i = 0; i < numParBlocks; i++) {
317
318 // multiply and reduce
319 LongVector c0 = (LongVector)
320 a0.castShape(longSpecies, 0).mul(rUp0_int.castShape(longSpecies, 0))
321 .add(a1.castShape(longSpecies, 0).mul(r5Up4_int.castShape(longSpecies, 0)))
322 .add(a2.castShape(longSpecies, 0).mul(r5Up3_int.castShape(longSpecies, 0)))
323 .add(a3.castShape(longSpecies, 0).mul(r5Up2_int.castShape(longSpecies, 0)))
324 .add(a4.castShape(longSpecies, 0).mul(r5Up1_int.castShape(longSpecies, 0)));
325
326 LongVector c1 = (LongVector)
327 a0.castShape(longSpecies, 0).mul(rUp1_int.castShape(longSpecies, 0))
328 .add(a1.castShape(longSpecies, 0).mul(rUp0_int.castShape(longSpecies, 0)))
329 .add(a2.castShape(longSpecies, 0).mul(r5Up4_int.castShape(longSpecies, 0)))
330 .add(a3.castShape(longSpecies, 0).mul(r5Up3_int.castShape(longSpecies, 0)))
331 .add(a4.castShape(longSpecies, 0).mul(r5Up2_int.castShape(longSpecies, 0)));
332
333 LongVector c2 = (LongVector)
334 a0.castShape(longSpecies, 0).mul(rUp2_int.castShape(longSpecies, 0))
335 .add(a1.castShape(longSpecies, 0).mul(rUp1_int.castShape(longSpecies, 0)))
336 .add(a2.castShape(longSpecies, 0).mul(rUp0_int.castShape(longSpecies, 0)))
337 .add(a3.castShape(longSpecies, 0).mul(r5Up4_int.castShape(longSpecies, 0)))
338 .add(a4.castShape(longSpecies, 0).mul(r5Up3_int.castShape(longSpecies, 0)));
339
340 LongVector c3 = (LongVector)
341 a0.castShape(longSpecies, 0).mul(rUp3_int.castShape(longSpecies, 0))
342 .add(a1.castShape(longSpecies, 0).mul(rUp2_int.castShape(longSpecies, 0)))
343 .add(a2.castShape(longSpecies, 0).mul(rUp1_int.castShape(longSpecies, 0)))
344 .add(a3.castShape(longSpecies, 0).mul(rUp0_int.castShape(longSpecies, 0)))
345 .add(a4.castShape(longSpecies, 0).mul(r5Up4_int.castShape(longSpecies, 0)));
346
347 LongVector c4 = (LongVector)
348 a0.castShape(longSpecies, 0).mul(rUp4_int.castShape(longSpecies, 0))
349 .add(a1.castShape(longSpecies, 0).mul(rUp3_int.castShape(longSpecies, 0)))
350 .add(a2.castShape(longSpecies, 0).mul(rUp2_int.castShape(longSpecies, 0)))
351 .add(a3.castShape(longSpecies, 0).mul(rUp1_int.castShape(longSpecies, 0)))
352 .add(a4.castShape(longSpecies, 0).mul(rUp0_int.castShape(longSpecies, 0)));
353
354 // carry/reduce
355 // Note: this carry/reduce sequence might not be correct
356 c4 = c4.add(c3.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
357 c3 = c3.and(LIMB_MASK);
358 c0 = c0.add(c4.lanewise(VectorOperators.LSHR, BITS_PER_LIMB).mul(5));
359 c4 = c4.and(LIMB_MASK);
360 c1 = c1.add(c0.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
361 c0 = c0.and(LIMB_MASK);
362 c2 = c2.add(c1.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
363 c1 = c1.and(LIMB_MASK);
364 c3 = c3.add(c2.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
365 c2 = c2.and(LIMB_MASK);
366 c4 = c4.add(c3.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
367 c3 = c3.and(LIMB_MASK);
368
369 a0 = (IntVector) c0.castShape(intSpecies, 0);
370 a1 = (IntVector) c1.castShape(intSpecies, 0);
371 a2 = (IntVector) c2.castShape(intSpecies, 0);
372 a3 = (IntVector) c3.castShape(intSpecies, 0);
373 a4 = (IntVector) c4.castShape(intSpecies, 0);
374
375 // fromByteArray and add next part of message
376 int start = parBlockCount * (i + 1);
377
378 longMsg0 = LongVector.fromMemorySegment(longSpecies, msMsg, start, ByteOrder.LITTLE_ENDIAN);
379 longMsg1 = LongVector.fromMemorySegment(longSpecies, msMsg,
380 start + vectorWidth * 8L, ByteOrder.LITTLE_ENDIAN);
381
382 inAlign0 =
383 longMsg0.rearrange(inShuffle0).blend(longMsg1.rearrange(inShuffle0), inMask);
384 inAlign1 =
385 longMsg0.rearrange(inShuffle1).blend(longMsg1.rearrange(inShuffle1), inMask);
386
387 IntVector in0 = (IntVector)
388 inAlign0.and(LIMB_MASK).castShape(intSpecies, 0);
389 IntVector in1 = (IntVector)
390 inAlign0.lanewise(VectorOperators.LSHR, 26).and(LIMB_MASK).castShape(intSpecies, 0);
391 IntVector in2 = (IntVector)
392 inAlign0.lanewise(VectorOperators.LSHR, 52).and(0xFFF).castShape(intSpecies, 0);
393 in2 = in2.or(inAlign1.and(0x3FFF).lanewise(VectorOperators.LSHL, 12).castShape(intSpecies, 0));
394 IntVector in3 = (IntVector)
395 inAlign1.lanewise(VectorOperators.LSHR, 14).and(LIMB_MASK).castShape(intSpecies, 0);
396 IntVector in4 = (IntVector)
397 inAlign1.lanewise(VectorOperators.LSHR, 40).and(0xFFFFFF).castShape(intSpecies, 0);
398 in4 = in4.or(1 << 24);
399
400 a0 = a0.add(in0);
401 a1 = a1.add(in1);
402 a2 = a2.add(in2);
403 a3 = a3.add(in3);
404 a4 = a4.add(in4);
405 }
406
407 // multiply by powers of r
408 long[] rTemp = new long[vectorWidth];
409 LongVector rFin0 = rPowerVec(r, rTemp, rUpIndex, 0);
410 LongVector rFin1 = rPowerVec(r, rTemp, rUpIndex, 1);
411 LongVector rFin2 = rPowerVec(r, rTemp, rUpIndex, 2);
412 LongVector rFin3 = rPowerVec(r, rTemp, rUpIndex, 3);
413 LongVector rFin4 = rPowerVec(r, rTemp, rUpIndex, 4);
414
415 LongVector r5Fin_1 = rFin1.mul(5);
416 LongVector r5Fin_2 = rFin2.mul(5);
417 LongVector r5Fin_3 = rFin3.mul(5);
418 LongVector r5Fin_4 = rFin4.mul(5);
419
420 LongVector c0 = (LongVector) a0.castShape(longSpecies, 0).mul(rFin0)
421 .add(a1.castShape(longSpecies, 0).mul(r5Fin_4))
422 .add(a2.castShape(longSpecies, 0).mul(r5Fin_3))
423 .add(a3.castShape(longSpecies, 0).mul(r5Fin_2))
424 .add(a4.castShape(longSpecies, 0).mul(r5Fin_1));
425 LongVector c1 = (LongVector) a0.castShape(longSpecies, 0).mul(rFin1)
426 .add(a1.castShape(longSpecies, 0).mul(rFin0))
427 .add(a2.castShape(longSpecies, 0).mul(r5Fin_4))
428 .add(a3.castShape(longSpecies, 0).mul(r5Fin_3))
429 .add(a4.castShape(longSpecies, 0).mul(r5Fin_2));
430 LongVector c2 = (LongVector) a0.castShape(longSpecies, 0).mul(rFin2)
431 .add(a1.castShape(longSpecies, 0).mul(rFin1))
432 .add(a2.castShape(longSpecies, 0).mul(rFin0))
433 .add(a3.castShape(longSpecies, 0).mul(r5Fin_4))
434 .add(a4.castShape(longSpecies, 0).mul(r5Fin_3));
435 LongVector c3 = (LongVector) a0.castShape(longSpecies, 0).mul(rFin3)
436 .add(a1.castShape(longSpecies, 0).mul(rFin2))
437 .add(a2.castShape(longSpecies, 0).mul(rFin1))
438 .add(a3.castShape(longSpecies, 0).mul(rFin0))
439 .add(a4.castShape(longSpecies, 0).mul(r5Fin_4));
440 LongVector c4 = (LongVector) a0.castShape(longSpecies, 0).mul(rFin4)
441 .add(a1.castShape(longSpecies, 0).mul(rFin3))
442 .add(a2.castShape(longSpecies, 0).mul(rFin2))
443 .add(a3.castShape(longSpecies, 0).mul(rFin1))
444 .add(a4.castShape(longSpecies, 0).mul(rFin0));
445
446 c4 = c4.add(c3.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
447 c3 = c3.and(LIMB_MASK);
448 c0 = c0.add(c4.lanewise(VectorOperators.LSHR, BITS_PER_LIMB).mul(5));
449 c4 = c4.and(LIMB_MASK);
450 c1 = c1.add(c0.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
451 c0 = c0.and(LIMB_MASK);
452 c2 = c2.add(c1.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
453 c1 = c1.and(LIMB_MASK);
454 c3 = c3.add(c2.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
455 c2 = c2.and(LIMB_MASK);
456 c4 = c4.add(c3.lanewise(VectorOperators.LSHR, BITS_PER_LIMB));
457 c3 = c3.and(LIMB_MASK);
458
459 a0 = (IntVector) c0.castShape(intSpecies, 0);
460 a1 = (IntVector) c1.castShape(intSpecies, 0);
461 a2 = (IntVector) c2.castShape(intSpecies, 0);
462 a3 = (IntVector) c3.castShape(intSpecies, 0);
463 a4 = (IntVector) c4.castShape(intSpecies, 0);
464
465 // collect lanes and calculate tag
466 long a0Fin = a0.reduceLanes(VectorOperators.ADD);
467 long a1Fin = a1.reduceLanes(VectorOperators.ADD);
468 long a2Fin = a2.reduceLanes(VectorOperators.ADD);
469 long a3Fin = a3.reduceLanes(VectorOperators.ADD);
470 long a4Fin = a4.reduceLanes(VectorOperators.ADD);
471
472 // carry/reduce the result
473 a4Fin = a4Fin + (a3Fin >>> BITS_PER_LIMB);
474 a3Fin = a3Fin & LIMB_MASK;
475 a0Fin = a0Fin + ((a4Fin >>> BITS_PER_LIMB) * 5);
476 a4Fin = a4Fin & LIMB_MASK;
477 a1Fin = a1Fin + (a0Fin >>> BITS_PER_LIMB);
478 a0Fin = a0Fin & LIMB_MASK;
479 a2Fin = a2Fin + (a1Fin >>> BITS_PER_LIMB);
480 a1Fin = a1Fin & LIMB_MASK;
481 a3Fin = a3Fin + (a2Fin >>> BITS_PER_LIMB);
482 a2Fin = a2Fin & LIMB_MASK;
483 a4Fin = a4Fin + (a3Fin >>> BITS_PER_LIMB);
484 a3Fin = a3Fin & LIMB_MASK;
485
486 byte[] s_arr =
487 Arrays.copyOfRange(keyBytes, RS_LENGTH, 2 * RS_LENGTH);
488 int[] s = fromByteArray(s_arr);
489
490 // Add in the s-half of the key to the accumulator
491 a0Fin += s[0];
492 a1Fin += s[1];
493 a2Fin += s[2];
494 a3Fin += s[3];
495 a4Fin += s[4];
496
497 // final carry mod 2^130
498 a1Fin = a1Fin + (a0Fin >> BITS_PER_LIMB);
499 a0Fin = a0Fin & LIMB_MASK;
500 a2Fin = a2Fin + (a1Fin >> BITS_PER_LIMB);
501 a1Fin = a1Fin & LIMB_MASK;
502 a3Fin = a3Fin + (a2Fin >> BITS_PER_LIMB);
503 a2Fin = a2Fin & LIMB_MASK;
504 a4Fin = a4Fin + (a3Fin >> BITS_PER_LIMB);
505 a3Fin = a3Fin & LIMB_MASK;
506 a4Fin = a4Fin & LIMB_MASK;
507
508 // put result in buffer
509 toByteArray(a0Fin, a1Fin, a2Fin, a3Fin, a4Fin, out);
510 }
511 }
512
513
514 private static byte[] hexStringToByteArray(String str) {
515 byte[] result = new byte[str.length() / 2];
516 for (int i = 0; i < result.length; i++) {
517 result[i] = (byte) Character.digit(str.charAt(2 * i), 16);
518 result[i] <<= 4;
519 result[i] += Character.digit(str.charAt(2 * i + 1), 16);
520 }
521 return result;
522 }
523
524 public static String byteArrayToHexString(byte[] arr) {
525 StringBuilder result = new StringBuilder();
526 for (int i = 0; i < arr.length; ++i) {
527 byte curVal = arr[i];
528 result.append(Character.forDigit(curVal >> 4 & 0xF, 16));
529 result.append(Character.forDigit(curVal & 0xF, 16));
530 }
531 return result.toString();
532 }
533
534 private static void kat(Poly1305Vector poly1305, String key, String msg,
535 String expectedTag) {
536
537 kat(poly1305, hexStringToByteArray(key), hexStringToByteArray(msg),
538 hexStringToByteArray(expectedTag));
539 }
540
541 private static void kat(Poly1305Vector poly1305, byte[] key, byte[] msg,
542 byte[] expectedTag) {
543
544 byte[] tag = new byte[expectedTag.length];
545 poly1305.computeTag(key, msg, tag);
546 if (!Arrays.equals(tag, expectedTag)) {
547 throw new RuntimeException(
548 "bad tag: " + byteArrayToHexString(tag) +
549 " expected: " + byteArrayToHexString(expectedTag));
550 }
551 }
552
553 /*
554 * Poly1305 Known Answer Tests to ensure that the implementation is correct.
555 */
556 private static void runKAT(Poly1305Vector poly1305) {
557 kat(poly1305,
558 "d212b886dd4682a41f1759e6c5aef84760e5a63d4423ca7d1fb5c7ecfc5dac27",
559 "5d2ad39e2a7b0bc5f375488643acf391188d01ad936971457427bc053c4262a1" +
560 "598532850def8573213c5f79fa736703c57c03ec49b55617210998c8af408698" +
561 "866632a7ecf7e9a688605cbca919e17e2badd090a7a6d83ad90be0617fa44642" +
562 "cc9a1ca38514a026cbea51c287ec0b56719fc61183c88e9450ba85aa8ab7d390",
563 "7ccdfa8e82df540276e8172f705adce2");
564
565 kat(poly1305,
566 "2b0b684c86910104aee1d261ac4d5a0f5443b4b7746cf7f8ba03921d273f6a9b",
567 "027b359f44a5d60f81073ceb74749207742529dcefa4a26a1817db2c8d50ba2b" +
568 "d9e170cd1930946872d95e4eae41389f362087871a749897e0fbe42494e6f0b3" +
569 "8db01e2059510b6fda4f422ce7d226433ba00940e1761baaff80d9b8f3a61d11" +
570 "a109e6082d231cf85aa718199e6eaaaf07bad562469ef1b8e639c727967bf6da" +
571 "bcd16fcb0fc102095325e2fac92e599e81c26900df1deb7b0a0b5c321a658024" +
572 "26506740509ece646fecf33a517b66e57577372156aae85765c6b473521d1019" +
573 "4f5fbe0e932cfee716e1d41c9154fb8e15b82ab7e807fb54f3d7d3e4c589cc9a" +
574 "492d17ea4fd27894fa9d22a9db6d5df674cd1e97e7e8758a360291f22dfe1cc3",
575 "84ca3a778faf0ab9f840fe5fb38ace27");
576
577 kat(poly1305,
578 "870c6fa7da2eadb845ac8b0eeaed4cf856eca67bf96b64a29a2e6a881821fa8a",
579 "ff1a3b67a4f575be5f05c4054e4c7365838c2cbe786ba78900c8b43f197c3c4d" +
580 "120432a287e434669af579bcd56f3320e54d2f97a306f917f2f41b1c97cc69db" +
581 "4ac2051adccd687fa89f92504d1ab5c3006681d846c8051aabccca0024ef5ec4" +
582 "c43b8701ffc9d14fef8d55e229ed210a2b9bde996f5d7b545d15e1fc32764604" +
583 "b2a0384dd173aa800b7526c8ff397c05130bb6a1f2194968adaef6979b023cd8" +
584 "d9195d2739351c7e4ac6c43508634f813641f669e78cbcf732ccb1321a2cd2c4" +
585 "14c7df5b9ea3408f2e12fbf3a3cbdb98699dd5402725ec25f9fff9bcd0f93cb3" +
586 "cf0dac016fec41a5ef3ae8b8d258a09f530ad14ad2e52186041592eac0ea22ff" +
587 "8c3751009b516c60f7764cccbb816394ef035bd8cb2a38d5c6b9229e528e56cd" +
588 "62600b5219b64212642384e628f01d790eeef4963a7d1a63a9faff79d4acfa09" +
589 "78b58b0b623ae89389661aa408b16814d3baaca20978dce6888c3365f4ffd2fa" +
590 "8f031a44f2e870a06da21d7becf450d335e1386268bc189435e7955a477bc368",
591 "ff4e0ee6feb1c6a57e638a79fafc7c60");
592
593 kat(poly1305,
594 "c27987ae88a833ae2ea90371b2e257c15773da3bc34516b6b075446e1f844a81",
595 "64e5a2e2940b173c7103ae931ced302a8f8c778f4e5c0b3677c51552655005d8" +
596 "504b724107e7262448c94db83fc9c6a2a26fc973360dce15c0553b73bb733d3e" +
597 "f61fcba8977e76c32523b80c3b45b1226b23ee17522f9b677880c69b356917ae" +
598 "3c792a0c5b0c77b90dfa51483626323b7a73fffb1b128c595d553bf62a8f5bb9" +
599 "fa48b4a850a932481bf607e8da84730c9052bba9316ec7eb84007a4eb5cbed5c" +
600 "7c67ef32d4c5cb6cfbccd738d239857c240de6d3d4e5af14d480feb63541e5d8" +
601 "036e088b2e32431e6fe0c4d3505aebe2e14bd02b6b15325f89aef048cd1236db" +
602 "4461a59304b7c61ece2c52ef8ac4cf2326e6aaff013494b1b191be4ae4381f57" +
603 "e72b947ee23d0a528087db9338bc28c68484929fc3436995b2083b06a765ceb7" +
604 "09e9dd41ba896d99832d6851189766e844137d9a83d2890bc2be7afc82f9ebb8" +
605 "bafe08ef5f7ff0cce9a1d08e6b797a17df04731f384a34b16e72e9f2ab070114" +
606 "8008945509fe378658dc51eb752248f48364be327cd1b6bd148c518a976ae95d" +
607 "d391f3b0d447251988c7e77400c9d44395b8f9f10cbc442a6804d0ad83e8c3e3" +
608 "9fa09c2140fac143c90f09a7d907c57e29b528d54c8bd927f39aee2cec671213" +
609 "c50fe657b29682d57a419e3e52dafb348cbe44b6c17e4be18f5c5e411734fcfc" +
610 "99b9ca26f29a21cc93374ef1bfa86ca2bb3be76b94b4ef69ec790c968a51e4d0",
611 "d4c09727f68fa3beb57ce9e74205b652");
612
613 kat(poly1305,
614 "2593adf2efc0e49c7fde0d45de4f7a21ceb76df45c0e5a917ef1f6b7fbf4fb7e",
615 "23665b9a6d4f04c9d58347d32d64d4cbf8d4ca993a8bb73758e6eb2db9f97096" +
616 "d0f00aca8cb16460d2bc15c0136fa92482602f47b3ec78244c4dc619d9b28afa" +
617 "19b063c196bcff848eff179102cce29dfcc58bf90a2f6311e6d021e2573ccbb4" +
618 "4e06947167c9865127c0b7362196523f97c8157058f7aebff475f77e23393dc1" +
619 "a3031bbaf31270db3eadc00cca6ae073aa53160d095afdce0a202de8a23d9a38" +
620 "b0bed20cbe64e1ec77fc13ba0cfc9be52edb70475bf1aeaaff25e11f2e0ae47f" +
621 "f23cbd4a6219d276fcc6c8f12a739f11434c86d4e24397f96ef6e36d9195fa8a" +
622 "48eb55990d69feacfb754b5019a3ebafa98d5544077b46c136cc11de8ee7f8a6" +
623 "76a6696600088696233f4e8f060ba8a64890fb638469639bfb727ed758c36250" +
624 "a553b7ce1115509f2bb19c13cea87003a8eff45ce9e1cff0a21ba5ae19226d50" +
625 "e108db212a588e5f4c502468859b9b607922c3311b5d912bd9400e696d7debbb" +
626 "9ac5454cc7d0f95fc242c491f095a02f0d3bd7ead0f0b7358c9b1d85e4e9ab75" +
627 "24bb43867c94a21a4e0db6470a210c9dd937e4801396bd687127fa7c83014c85" +
628 "372553c56dfd6cd9b75fa10483aea825f8e3fa53c6bf17467e37c2e7439ed0ea" +
629 "6fb24d13d428965c44f1ac943c7bc77fa84711c91b41f5ee6d9a7d9091648a96" +
630 "cc7c261d7fc5d964446d1e3dcc41d32ecaa8d7791b8462563fcf7f96cd1d11d4" +
631 "34923e0150321356866f5bdafebc96f2661bfd3c1f104e96b6492cafcbe25fc6" +
632 "ec0c92a3bbec7328e1905d5951fae04625a2452f596027a5d9c64eed55165c8a" +
633 "23bc3f944b4fa9c7ad83ebc1777c7153d5de13d04c0a12e774b17906a62f5134" +
634 "685c2de31da08bd04840299fd62d56ffe95248365034e7ba95961cebf0542b24",
635 "b9f68b0996caf5135136b10b37fe5f81");
636
637 kat(poly1305,
638 "e9c8c78bc0ad5751f094fd4657fe5ef2a3c232f6930eef3431cde76659f04210",
639 "914e57a2745fd475d7b8f982483fe11a05d7b55853239112d5ae99616c718b3c" +
640 "4a0c2d05e3ca1df509614c0fe051b414d404149ec422e0998e192e51518518c4" +
641 "b8acd9e3e3ff9f3b4ef931d3052755785d38e75821ceefa7da0bfe3f1fb2dc6d" +
642 "738e2a2332e53ce77d44547621bb7aa724dd8805c7c795088db865d6b13d9b3e" +
643 "8acec846efb072d105ab6e599f8292a7601087e0ba13af9f503dcfd426e26e4d" +
644 "fb22bf5a1ff1a82d67d9bd8871e6adc17aa39d221f2865f81da9ed566192c269" +
645 "3c85f0442924e603b9ae54b88dd0f21e92eedc40c08dd484c552e297894eeee8" +
646 "b5acc91d5ae16f56257bb0836b48e1a8fa72e83a8b10b7026a7f466c8b08eac5" +
647 "4359b70e639117cf688e263b891f004db94d77941380f3ab0559538c9398c859" +
648 "b76d2bbcd6b635e753160583e7adc263097a80520d003514e134a21597c1ec57" +
649 "55da3a70acc6951b4d4d81e98b9eb962d9e3bc37d5e8ebd61e2a3f61cc452a65" +
650 "56571e12c190d4e3d0f8cc61ffcb60324b4a6987e7375a832ff807682e0b4595" +
651 "66ef1f765638f3d2e837ed43ce2c1c7837f271c866908d865c3d9174fd4f8056" +
652 "265abfb88fbc207db7a12c0a0ad035e5a728725e98cb682d41fd0bcf3aef2fd7" +
653 "ab261727f310fc7cf3b34286c9e9ee235995315167191f3b4d77e5642fb57dbd" +
654 "fdb5ccadefc5d03866918ab1a3eff54b405d8946e2b0c2fa444d1b2be4c3d41d" +
655 "990515e7534190d66d10e38c36c5d3df0315db85ba10c924bef97d1faa07a5f8" +
656 "f04998a7d38689237a1912bea3f821357d8383d7c5cfa66ba5965b5a94bb702c" +
657 "e6583e59879021139355c5b90e0f9cd13b34f3357ffde404bbf34c97f9fd55b5" +
658 "53e42d8a6b370eded02c8a5221e15db701da56918412520e12fd1ef9f4748647" +
659 "858488d5e0abd5b9e01457768907e1d24581f9591771304192711292e4025fce" +
660 "bd92adb2297e9496852f80bd78578bbdb292ca209f7584ff76e9eb66ec8a111e" +
661 "add30dc7ef364c4f1339312f226fe0cfa7a5b1602417e469cf2c8e3874c51232" +
662 "00f2d90dbe7f3c3ff5c6c6484052a80eb6229a6ed6176ad600da185da624bea6",
663 "c1de44dd8ea245ca43e5587460feb514");
664 }
665 }