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256 lines
8.1 KiB
256 lines
8.1 KiB
#include <stdio.h> |
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#include <memory.h> |
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#include "cuda_helper.h" |
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// globaler Speicher für alle HeftyHashes aller Threads |
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extern uint32_t *heavy_heftyHashes[MAX_GPUS]; |
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extern uint32_t *heavy_nonceVector[MAX_GPUS]; |
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// globaler Speicher für unsere Ergebnisse |
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uint32_t *d_hash5output[MAX_GPUS]; |
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// die Message (112 bzw. 116 Bytes) mit Padding zur Berechnung auf der GPU |
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__constant__ uint64_t c_PaddedMessage[16]; // padded message (80/84+32 bytes + padding) |
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// ---------------------------- BEGIN CUDA blake512 functions ------------------------------------ |
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__constant__ uint8_t c_sigma[16][16]; |
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const uint8_t host_sigma[16][16] = |
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{ |
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{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 }, |
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{14, 10, 4, 8, 9, 15, 13, 6, 1, 12, 0, 2, 11, 7, 5, 3 }, |
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{11, 8, 12, 0, 5, 2, 15, 13, 10, 14, 3, 6, 7, 1, 9, 4 }, |
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{ 7, 9, 3, 1, 13, 12, 11, 14, 2, 6, 5, 10, 4, 0, 15, 8 }, |
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{ 9, 0, 5, 7, 2, 4, 10, 15, 14, 1, 11, 12, 6, 8, 3, 13 }, |
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{ 2, 12, 6, 10, 0, 11, 8, 3, 4, 13, 7, 5, 15, 14, 1, 9 }, |
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{12, 5, 1, 15, 14, 13, 4, 10, 0, 7, 6, 3, 9, 2, 8, 11 }, |
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{13, 11, 7, 14, 12, 1, 3, 9, 5, 0, 15, 4, 8, 6, 2, 10 }, |
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{ 6, 15, 14, 9, 11, 3, 0, 8, 12, 2, 13, 7, 1, 4, 10, 5 }, |
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{10, 2, 8, 4, 7, 6, 1, 5, 15, 11, 9, 14, 3, 12, 13 , 0 }, |
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{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 }, |
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{14, 10, 4, 8, 9, 15, 13, 6, 1, 12, 0, 2, 11, 7, 5, 3 }, |
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{11, 8, 12, 0, 5, 2, 15, 13, 10, 14, 3, 6, 7, 1, 9, 4 }, |
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{ 7, 9, 3, 1, 13, 12, 11, 14, 2, 6, 5, 10, 4, 0, 15, 8 }, |
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{ 9, 0, 5, 7, 2, 4, 10, 15, 14, 1, 11, 12, 6, 8, 3, 13 }, |
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{ 2, 12, 6, 10, 0, 11, 8, 3, 4, 13, 7, 5, 15, 14, 1, 9 } |
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}; |
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/* in cuda_helper */ |
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#define SWAP32(x) cuda_swab32(x) |
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#define SWAP64(x) cuda_swab64(x) |
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__constant__ uint64_t c_SecondRound[15]; |
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const uint64_t host_SecondRound[15] = |
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{ |
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0,0,0,0,0,0,0,0,0,0,0,0,0,SWAP64(1),0 |
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}; |
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__constant__ uint64_t c_u512[16]; |
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const uint64_t host_u512[16] = |
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{ |
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0x243f6a8885a308d3ULL, 0x13198a2e03707344ULL, |
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0xa4093822299f31d0ULL, 0x082efa98ec4e6c89ULL, |
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0x452821e638d01377ULL, 0xbe5466cf34e90c6cULL, |
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0xc0ac29b7c97c50ddULL, 0x3f84d5b5b5470917ULL, |
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0x9216d5d98979fb1bULL, 0xd1310ba698dfb5acULL, |
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0x2ffd72dbd01adfb7ULL, 0xb8e1afed6a267e96ULL, |
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0xba7c9045f12c7f99ULL, 0x24a19947b3916cf7ULL, |
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0x0801f2e2858efc16ULL, 0x636920d871574e69ULL |
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}; |
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#define G(a,b,c,d,e) \ |
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v[a] += (m[sigma[i][e]] ^ u512[sigma[i][e+1]]) + v[b];\ |
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v[d] = SWAPDWORDS( v[d] ^ v[a]); \ |
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v[c] += v[d]; \ |
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v[b] = ROTR64( v[b] ^ v[c],25); \ |
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v[a] += (m[sigma[i][e+1]] ^ u512[sigma[i][e]])+v[b]; \ |
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v[d] = ROTR64( v[d] ^ v[a],16); \ |
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v[c] += v[d]; \ |
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v[b] = ROTR64( v[b] ^ v[c],11); |
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template <int BLOCKSIZE> __device__ void blake512_compress( uint64_t *h, const uint64_t *block, int nullt, const uint8_t ((*sigma)[16]), const uint64_t *u512 ) |
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{ |
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uint64_t v[16], m[16], i; |
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#pragma unroll 16 |
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for( i = 0; i < 16; ++i ) m[i] = cuda_swab64(block[i]); |
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#pragma unroll 8 |
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for( i = 0; i < 8; ++i ) v[i] = h[i]; |
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v[ 8] = u512[0]; |
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v[ 9] = u512[1]; |
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v[10] = u512[2]; |
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v[11] = u512[3]; |
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v[12] = u512[4]; |
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v[13] = u512[5]; |
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v[14] = u512[6]; |
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v[15] = u512[7]; |
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/* don't xor t when the block is only padding */ |
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if ( !nullt ) { |
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v[12] ^= 8*(BLOCKSIZE+32); |
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v[13] ^= 8*(BLOCKSIZE+32); |
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} |
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//#pragma unroll 16 |
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for( i = 0; i < 16; ++i ) |
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{ |
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/* column step */ |
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G( 0, 4, 8, 12, 0 ); |
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G( 1, 5, 9, 13, 2 ); |
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G( 2, 6, 10, 14, 4 ); |
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G( 3, 7, 11, 15, 6 ); |
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/* diagonal step */ |
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G( 0, 5, 10, 15, 8 ); |
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G( 1, 6, 11, 12, 10 ); |
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G( 2, 7, 8, 13, 12 ); |
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G( 3, 4, 9, 14, 14 ); |
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} |
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#pragma unroll 16 |
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for( i = 0; i < 16; ++i ) h[i % 8] ^= v[i]; |
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} |
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template <int BLOCKSIZE> __global__ void blake512_gpu_hash(uint32_t threads, uint32_t startNounce, void *outputHash, uint32_t *heftyHashes, uint32_t *nonceVector) |
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{ |
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uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x); |
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if (thread < threads) |
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{ |
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// bestimme den aktuellen Zähler |
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//uint32_t nounce = startNounce + thread; |
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uint32_t nounce = nonceVector[thread]; |
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// Index-Position des Hashes in den Hash Puffern bestimmen (Hefty1 und outputHash) |
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uint32_t hashPosition = nounce - startNounce; |
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// State vorbereiten |
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uint64_t h[8]; |
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h[0] = 0x6a09e667f3bcc908ULL; |
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h[1] = 0xbb67ae8584caa73bULL; |
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h[2] = 0x3c6ef372fe94f82bULL; |
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h[3] = 0xa54ff53a5f1d36f1ULL; |
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h[4] = 0x510e527fade682d1ULL; |
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h[5] = 0x9b05688c2b3e6c1fULL; |
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h[6] = 0x1f83d9abfb41bd6bULL; |
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h[7] = 0x5be0cd19137e2179ULL; |
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// 128 Byte für die Message |
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uint64_t buf[16]; |
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// Message für die erste Runde in Register holen |
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#pragma unroll 16 |
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for (int i=0; i < 16; ++i) buf[i] = c_PaddedMessage[i]; |
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// die Nounce durch die thread-spezifische ersetzen |
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buf[9] = REPLACE_HIWORD(buf[9], nounce); |
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uint32_t *hefty = heftyHashes + 8 * hashPosition; |
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if (BLOCKSIZE == 84) { |
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// den thread-spezifischen Hefty1 hash einsetzen |
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// aufwändig, weil das nicht mit uint64_t Wörtern aligned ist. |
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buf[10] = REPLACE_HIWORD(buf[10], hefty[0]); |
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buf[11] = REPLACE_LOWORD(buf[11], hefty[1]); |
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buf[11] = REPLACE_HIWORD(buf[11], hefty[2]); |
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buf[12] = REPLACE_LOWORD(buf[12], hefty[3]); |
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buf[12] = REPLACE_HIWORD(buf[12], hefty[4]); |
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buf[13] = REPLACE_LOWORD(buf[13], hefty[5]); |
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buf[13] = REPLACE_HIWORD(buf[13], hefty[6]); |
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buf[14] = REPLACE_LOWORD(buf[14], hefty[7]); |
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} |
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else if (BLOCKSIZE == 80) { |
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buf[10] = MAKE_ULONGLONG(hefty[0], hefty[1]); |
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buf[11] = MAKE_ULONGLONG(hefty[2], hefty[3]); |
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buf[12] = MAKE_ULONGLONG(hefty[4], hefty[5]); |
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buf[13] = MAKE_ULONGLONG(hefty[6], hefty[7]); |
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} |
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// erste Runde |
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blake512_compress<BLOCKSIZE>( h, buf, 0, c_sigma, c_u512 ); |
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// zweite Runde |
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#pragma unroll 15 |
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for (int i=0; i < 15; ++i) buf[i] = c_SecondRound[i]; |
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buf[15] = SWAP64(8*(BLOCKSIZE+32)); // Blocksize in Bits einsetzen |
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blake512_compress<BLOCKSIZE>( h, buf, 1, c_sigma, c_u512 ); |
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// Hash rauslassen |
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uint64_t *outHash = (uint64_t *)outputHash + 8 * hashPosition; |
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#pragma unroll 8 |
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for (int i=0; i < 8; ++i) outHash[i] = cuda_swab64( h[i] ); |
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} |
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} |
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// ---------------------------- END CUDA blake512 functions ------------------------------------ |
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// Setup-Funktionen |
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__host__ void blake512_cpu_init(int thr_id, uint32_t threads) |
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{ |
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// Kopiere die Hash-Tabellen in den GPU-Speicher |
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cudaMemcpyToSymbol( c_sigma, |
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host_sigma, |
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sizeof(host_sigma), |
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0, cudaMemcpyHostToDevice); |
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cudaMemcpyToSymbol( c_u512, |
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host_u512, |
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sizeof(host_u512), |
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0, cudaMemcpyHostToDevice); |
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cudaMemcpyToSymbol( c_SecondRound, |
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host_SecondRound, |
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sizeof(host_SecondRound), |
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0, cudaMemcpyHostToDevice); |
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// Speicher für alle Ergebnisse belegen |
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CUDA_SAFE_CALL(cudaMalloc(&d_hash5output[thr_id], 16 * sizeof(uint32_t) * threads)); |
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} |
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static int BLOCKSIZE = 84; |
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__host__ void blake512_cpu_setBlock(void *pdata, int len) |
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// data muss 84-Byte haben! |
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// heftyHash hat 32-Byte |
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{ |
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unsigned char PaddedMessage[128]; |
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if (len == 84) { |
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// Message mit Padding für erste Runde bereitstellen |
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memcpy(PaddedMessage, pdata, 84); |
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memset(PaddedMessage+84, 0, 32); // leeres Hefty Hash einfüllen |
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memset(PaddedMessage+116, 0, 12); |
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PaddedMessage[116] = 0x80; |
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} else if (len == 80) { |
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memcpy(PaddedMessage, pdata, 80); |
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memset(PaddedMessage+80, 0, 32); // leeres Hefty Hash einfüllen |
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memset(PaddedMessage+112, 0, 16); |
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PaddedMessage[112] = 0x80; |
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} |
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// die Message (116 Bytes) ohne Padding zur Berechnung auf der GPU |
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cudaMemcpyToSymbol( c_PaddedMessage, PaddedMessage, 16*sizeof(uint64_t), 0, cudaMemcpyHostToDevice); |
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BLOCKSIZE = len; |
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} |
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__host__ void blake512_cpu_hash(int thr_id, uint32_t threads, uint32_t startNounce) |
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{ |
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const uint32_t threadsperblock = 256; |
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// berechne wie viele Thread Blocks wir brauchen |
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dim3 grid((threads + threadsperblock-1)/threadsperblock); |
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dim3 block(threadsperblock); |
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// Größe des dynamischen Shared Memory Bereichs |
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size_t shared_size = 0; |
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if (BLOCKSIZE == 80) |
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blake512_gpu_hash<80><<<grid, block, shared_size>>>(threads, startNounce, d_hash5output[thr_id], heavy_heftyHashes[thr_id], heavy_nonceVector[thr_id]); |
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else if (BLOCKSIZE == 84) |
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blake512_gpu_hash<84><<<grid, block, shared_size>>>(threads, startNounce, d_hash5output[thr_id], heavy_heftyHashes[thr_id], heavy_nonceVector[thr_id]); |
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}
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