-
Notifications
You must be signed in to change notification settings - Fork 1.7k
/
cuda_blake512.cu
307 lines (253 loc) · 9.7 KB
/
cuda_blake512.cu
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
#include <cuda.h>
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <stdio.h>
#include <memory.h>
// Folgende Definitionen später durch header ersetzen
typedef unsigned char uint8_t;
typedef unsigned int uint32_t;
typedef unsigned long long uint64_t;
// globaler Speicher für alle HeftyHashes aller Threads
extern uint32_t *d_heftyHashes[8];
extern uint32_t *d_nonceVector[8];
// globaler Speicher für unsere Ergebnisse
uint32_t *d_hash5output[8];
// die Message (116 Bytes) mit Padding zur Berechnung auf der GPU
__constant__ uint64_t c_PaddedMessage[16]; // padded message (84+32 bytes + padding)
// ---------------------------- BEGIN CUDA blake512 functions ------------------------------------
__constant__ uint8_t c_sigma[16][16];
const uint8_t host_sigma[16][16] =
{
{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 },
{14, 10, 4, 8, 9, 15, 13, 6, 1, 12, 0, 2, 11, 7, 5, 3 },
{11, 8, 12, 0, 5, 2, 15, 13, 10, 14, 3, 6, 7, 1, 9, 4 },
{ 7, 9, 3, 1, 13, 12, 11, 14, 2, 6, 5, 10, 4, 0, 15, 8 },
{ 9, 0, 5, 7, 2, 4, 10, 15, 14, 1, 11, 12, 6, 8, 3, 13 },
{ 2, 12, 6, 10, 0, 11, 8, 3, 4, 13, 7, 5, 15, 14, 1, 9 },
{12, 5, 1, 15, 14, 13, 4, 10, 0, 7, 6, 3, 9, 2, 8, 11 },
{13, 11, 7, 14, 12, 1, 3, 9, 5, 0, 15, 4, 8, 6, 2, 10 },
{ 6, 15, 14, 9, 11, 3, 0, 8, 12, 2, 13, 7, 1, 4, 10, 5 },
{10, 2, 8, 4, 7, 6, 1, 5, 15, 11, 9, 14, 3, 12, 13 , 0 },
{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 },
{14, 10, 4, 8, 9, 15, 13, 6, 1, 12, 0, 2, 11, 7, 5, 3 },
{11, 8, 12, 0, 5, 2, 15, 13, 10, 14, 3, 6, 7, 1, 9, 4 },
{ 7, 9, 3, 1, 13, 12, 11, 14, 2, 6, 5, 10, 4, 0, 15, 8 },
{ 9, 0, 5, 7, 2, 4, 10, 15, 14, 1, 11, 12, 6, 8, 3, 13 },
{ 2, 12, 6, 10, 0, 11, 8, 3, 4, 13, 7, 5, 15, 14, 1, 9 }
};
#define SWAP32(x) \
((((x) << 24) & 0xff000000u) | (((x) << 8) & 0x00ff0000u) | \
(((x) >> 8) & 0x0000ff00u) | (((x) >> 24) & 0x000000ffu))
#define SWAP64(x) \
((uint64_t)((((uint64_t)(x) & 0xff00000000000000ULL) >> 56) | \
(((uint64_t)(x) & 0x00ff000000000000ULL) >> 40) | \
(((uint64_t)(x) & 0x0000ff0000000000ULL) >> 24) | \
(((uint64_t)(x) & 0x000000ff00000000ULL) >> 8) | \
(((uint64_t)(x) & 0x00000000ff000000ULL) << 8) | \
(((uint64_t)(x) & 0x0000000000ff0000ULL) << 24) | \
(((uint64_t)(x) & 0x000000000000ff00ULL) << 40) | \
(((uint64_t)(x) & 0x00000000000000ffULL) << 56)))
__constant__ uint64_t c_SecondRound[16];
const uint64_t host_SecondRound[16] =
{
0,0,0,0,0,0,0,0,0,0,0,0,0,SWAP64(1),0,SWAP64(0x3A0)
};
__constant__ uint64_t c_u512[16];
const uint64_t host_u512[16] =
{
0x243f6a8885a308d3ULL, 0x13198a2e03707344ULL,
0xa4093822299f31d0ULL, 0x082efa98ec4e6c89ULL,
0x452821e638d01377ULL, 0xbe5466cf34e90c6cULL,
0xc0ac29b7c97c50ddULL, 0x3f84d5b5b5470917ULL,
0x9216d5d98979fb1bULL, 0xd1310ba698dfb5acULL,
0x2ffd72dbd01adfb7ULL, 0xb8e1afed6a267e96ULL,
0xba7c9045f12c7f99ULL, 0x24a19947b3916cf7ULL,
0x0801f2e2858efc16ULL, 0x636920d871574e69ULL
};
#define ROTR(x,n) (((x)<<(64-n))|( (x)>>(n)))
#define G(a,b,c,d,e) \
v[a] += (m[sigma[i][e]] ^ u512[sigma[i][e+1]]) + v[b];\
v[d] = ROTR( v[d] ^ v[a],32); \
v[c] += v[d]; \
v[b] = ROTR( v[b] ^ v[c],25); \
v[a] += (m[sigma[i][e+1]] ^ u512[sigma[i][e]])+v[b]; \
v[d] = ROTR( v[d] ^ v[a],16); \
v[c] += v[d]; \
v[b] = ROTR( v[b] ^ v[c],11);
__device__ void blake512_compress( uint64_t *h, const uint64_t *block, int nullt, const uint8_t ((*sigma)[16]), const uint64_t *u512 )
{
uint64_t v[16], m[16], i;
#pragma unroll 16
for( i = 0; i < 16; ++i ) m[i] = SWAP64(block[i]);
#pragma unroll 8
for( i = 0; i < 8; ++i ) v[i] = h[i];
v[ 8] = u512[0];
v[ 9] = u512[1];
v[10] = u512[2];
v[11] = u512[3];
v[12] = u512[4];
v[13] = u512[5];
v[14] = u512[6];
v[15] = u512[7];
/* don't xor t when the block is only padding */
if ( !nullt ) {
v[12] ^= 928;
v[13] ^= 928;
}
#pragma unroll 16
for( i = 0; i < 16; ++i )
{
/* column step */
G( 0, 4, 8, 12, 0 );
G( 1, 5, 9, 13, 2 );
G( 2, 6, 10, 14, 4 );
G( 3, 7, 11, 15, 6 );
/* diagonal step */
G( 0, 5, 10, 15, 8 );
G( 1, 6, 11, 12, 10 );
G( 2, 7, 8, 13, 12 );
G( 3, 4, 9, 14, 14 );
}
#pragma unroll 16
for( i = 0; i < 16; ++i ) h[i % 8] ^= v[i];
}
// Endian Drehung für 32 Bit Typen
static __device__ uint32_t cuda_swab32(uint32_t x)
{
return (((x << 24) & 0xff000000u) | ((x << 8) & 0x00ff0000u)
| ((x >> 8) & 0x0000ff00u) | ((x >> 24) & 0x000000ffu));
}
// Endian Drehung für 64 Bit Typen
static __device__ uint64_t cuda_swab64(uint64_t x) {
uint32_t h = (x >> 32);
uint32_t l = (x & 0xFFFFFFFFULL);
return (((uint64_t)cuda_swab32(l)) << 32) | ((uint64_t)cuda_swab32(h));
}
// das Hi Word aus einem 64 Bit Typen extrahieren
static __device__ uint32_t HIWORD(const uint64_t &x) {
#if __CUDA_ARCH__ >= 130
return (uint32_t)__double2hiint(__longlong_as_double(x));
#else
return (uint32_t)(x >> 32);
#endif
}
// das Hi Word in einem 64 Bit Typen ersetzen
static __device__ uint64_t REPLACE_HIWORD(const uint64_t &x, const uint32_t &y) {
return (x & 0xFFFFFFFFULL) | (((uint64_t)y) << 32ULL);
}
// das Lo Word aus einem 64 Bit Typen extrahieren
static __device__ uint32_t LOWORD(const uint64_t &x) {
#if __CUDA_ARCH__ >= 130
return (uint32_t)__double2loint(__longlong_as_double(x));
#else
return (uint32_t)(x & 0xFFFFFFFFULL);
#endif
}
// das Lo Word in einem 64 Bit Typen ersetzen
static __device__ uint64_t REPLACE_LOWORD(const uint64_t &x, const uint32_t &y) {
return (x & 0xFFFFFFFF00000000ULL) | ((uint64_t)y);
}
__global__ void blake512_gpu_hash(int threads, uint32_t startNounce, void *outputHash, uint32_t *heftyHashes, uint32_t *nonceVector)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
// bestimme den aktuellen Zähler
//uint32_t nounce = startNounce + thread;
uint32_t nounce = nonceVector[thread];
// Index-Position des Hashes in den Hash Puffern bestimmen (Hefty1 und outputHash)
uint32_t hashPosition = nounce - startNounce;
// State vorbereiten
uint64_t h[8];
h[0] = 0x6a09e667f3bcc908ULL;
h[1] = 0xbb67ae8584caa73bULL;
h[2] = 0x3c6ef372fe94f82bULL;
h[3] = 0xa54ff53a5f1d36f1ULL;
h[4] = 0x510e527fade682d1ULL;
h[5] = 0x9b05688c2b3e6c1fULL;
h[6] = 0x1f83d9abfb41bd6bULL;
h[7] = 0x5be0cd19137e2179ULL;
// 128 Byte für die Message
uint64_t buf[16];
// Message für die erste Runde in Register holen
#pragma unroll 16
for (int i=0; i < 16; ++i) buf[i] = c_PaddedMessage[i];
// die Nounce durch die thread-spezifische ersetzen
buf[9] = REPLACE_HIWORD(buf[9], nounce);
// den thread-spezifischen Hefty1 hash einsetzen
uint32_t *hefty = heftyHashes + 8 * hashPosition;
buf[10] = REPLACE_HIWORD(buf[10], hefty[0]);
buf[11] = REPLACE_LOWORD(buf[11], hefty[1]);
buf[11] = REPLACE_HIWORD(buf[11], hefty[2]);
buf[12] = REPLACE_LOWORD(buf[12], hefty[3]);
buf[12] = REPLACE_HIWORD(buf[12], hefty[4]);
buf[13] = REPLACE_LOWORD(buf[13], hefty[5]);
buf[13] = REPLACE_HIWORD(buf[13], hefty[6]);
buf[14] = REPLACE_LOWORD(buf[14], hefty[7]);
// erste Runde
blake512_compress( h, buf, 0, c_sigma, c_u512 );
// zweite Runde
#pragma unroll 16
for (int i=0; i < 16; ++i) buf[i] = c_SecondRound[i];
blake512_compress( h, buf, 1, c_sigma, c_u512 );
// Hash rauslassen
#if 0
// ausschliesslich 32 bit Operationen sofern die SM1.3 double intrinsics verfügbar sind
uint32_t *outHash = (uint32_t *)outputHash + 16 * hashPosition;
#pragma unroll 8
for (int i=0; i < 8; ++i) {
outHash[2*i+0] = cuda_swab32( HIWORD(h[i]) );
outHash[2*i+1] = cuda_swab32( LOWORD(h[i]) );
}
#else
// in dieser Version passieren auch ein paar 64 Bit Shifts
uint64_t *outHash = (uint64_t *)outputHash + 8 * hashPosition;
#pragma unroll 8
for (int i=0; i < 8; ++i) outHash[i] = cuda_swab64( h[i] );
#endif
}
}
// ---------------------------- END CUDA blake512 functions ------------------------------------
// Setup-Funktionen
__host__ void blake512_cpu_init(int thr_id, int threads)
{
// Kopiere die Hash-Tabellen in den GPU-Speicher
cudaMemcpyToSymbol( c_sigma,
host_sigma,
sizeof(host_sigma),
0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol( c_u512,
host_u512,
sizeof(host_u512),
0, cudaMemcpyHostToDevice);
cudaMemcpyToSymbol( c_SecondRound,
host_SecondRound,
sizeof(host_SecondRound),
0, cudaMemcpyHostToDevice);
// Speicher für alle Ergebnisse belegen
cudaMalloc(&d_hash5output[thr_id], 16 * sizeof(uint32_t) * threads);
}
__host__ void blake512_cpu_setBlock(void *pdata)
// data muss 84-Byte haben!
// heftyHash hat 32-Byte
{
// Message mit Padding für erste Runde bereitstellen
unsigned char PaddedMessage[128];
memcpy(PaddedMessage, pdata, 84);
memset(PaddedMessage+84, 0, 32); // leeres Hefty Hash einfüllen
memset(PaddedMessage+116, 0, 12);
PaddedMessage[116] = 0x80;
// die Message (116 Bytes) ohne Padding zur Berechnung auf der GPU
cudaMemcpyToSymbol( c_PaddedMessage, PaddedMessage, 16*sizeof(uint64_t), 0, cudaMemcpyHostToDevice);
}
__host__ void blake512_cpu_hash(int thr_id, int threads, uint32_t startNounce)
{
const int threadsperblock = 256;
// berechne wie viele Thread Blocks wir brauchen
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
// Größe des dynamischen Shared Memory Bereichs
size_t shared_size = 0;
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
blake512_gpu_hash<<<grid, block, shared_size>>>(threads, startNounce, d_hash5output[thr_id], d_heftyHashes[thr_id], d_nonceVector[thr_id]);
}