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#include <stdio.h> |
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#include <memory.h> |
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#include "cuda_helper.h" |
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#define ROTR(x,n) ROTR64(x,n) |
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#define USE_SHUFFLE 0 |
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// aus heavy.cu |
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extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id); |
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// die Message it Padding zur Berechnung auf der GPU |
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__constant__ uint64_t c_PaddedMessage80[16]; // padded message (80 bytes + padding) |
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// ---------------------------- BEGIN CUDA quark_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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__device__ __constant__ |
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const uint64_t c_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] = ROTR( v[d] ^ v[a],32); \ |
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v[c] += v[d]; \ |
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v[b] = ROTR( 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] = ROTR( v[d] ^ v[a],16); \ |
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v[c] += v[d]; \ |
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v[b] = ROTR( v[b] ^ v[c],11); |
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__device__ static |
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void quark_blake512_compress( uint64_t *h, const uint64_t *block, const uint8_t ((*sigma)[16]), const uint64_t *u512, const int bits ) |
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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 ) { |
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m[i] = cuda_swab64(block[i]); |
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} |
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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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v[12] ^= bits; |
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v[13] ^= bits; |
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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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__device__ __constant__ |
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static const uint64_t d_constMem[8] = { |
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0x6a09e667f3bcc908ULL, |
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0xbb67ae8584caa73bULL, |
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0x3c6ef372fe94f82bULL, |
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0xa54ff53a5f1d36f1ULL, |
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0x510e527fade682d1ULL, |
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0x9b05688c2b3e6c1fULL, |
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0x1f83d9abfb41bd6bULL, |
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0x5be0cd19137e2179ULL }; |
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// Hash-Padding |
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__device__ __constant__ |
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static const uint64_t d_constHashPadding[8] = { |
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0x0000000000000080ull, |
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0, |
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0, |
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0, |
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0, |
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0x0100000000000000ull, |
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0, |
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0x0002000000000000ull }; |
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__global__ __launch_bounds__(256, 4) |
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void quark_blake512_gpu_hash_64(int threads, uint32_t startNounce, uint32_t *g_nonceVector, uint64_t *g_hash) |
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{ |
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int thread = (blockDim.x * blockIdx.x + threadIdx.x); |
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#if USE_SHUFFLE |
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const int warpID = threadIdx.x & 0x0F; // 16 warps |
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const int warpBlockID = (thread + 15)>>4; // aufrunden auf volle Warp-Bl<EFBFBD>cke |
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const int maxHashPosition = thread<<3; |
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#endif |
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#if USE_SHUFFLE |
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if (warpBlockID < ( (threads+15)>>4 )) |
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#else |
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if (thread < threads) |
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#endif |
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{ |
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uint8_t i; |
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// bestimme den aktuellen Z<EFBFBD>hler |
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uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread); |
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int hashPosition = nounce - startNounce; |
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uint64_t *inpHash = &g_hash[hashPosition<<3]; // hashPosition * 8 |
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// 128 Byte f<EFBFBD>r die Message |
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uint64_t buf[16]; |
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// State vorbereiten |
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uint64_t h[8]; |
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#pragma unroll 8 |
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for (i=0;i<8;i++) |
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h[i] = d_constMem[i]; |
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// Message f<EFBFBD>r die erste Runde in Register holen |
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#pragma unroll 8 |
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for (i=0; i < 8; ++i) |
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buf[i] = inpHash[i]; |
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#pragma unroll 8 |
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for (i=0; i < 8; i++) |
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buf[i+8] = d_constHashPadding[i]; |
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// die einzige Hashing-Runde |
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quark_blake512_compress( h, buf, c_sigma, c_u512, 512 ); |
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#if __CUDA_ARCH__ >= 130 |
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// ausschliesslich 32 bit Operationen sofern die SM1.3 double intrinsics verf<EFBFBD>gbar sind |
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uint32_t *outHash = (uint32_t*)&g_hash[8 * hashPosition]; |
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#pragma unroll 8 |
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for (i=0; i < 8; ++i) { |
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outHash[2*i+0] = cuda_swab32( _HIWORD(h[i]) ); |
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outHash[2*i+1] = cuda_swab32( _LOWORD(h[i]) ); |
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} |
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#else |
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// in dieser Version passieren auch ein paar 64 Bit Shifts |
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uint64_t *outHash = &g_hash[8 * hashPosition]; |
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#pragma unroll 8 |
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for (i=0; i < 8; ++i) |
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{ |
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outHash[i] = cuda_swab64(h[i]); |
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} |
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#endif |
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} |
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} |
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__global__ void quark_blake512_gpu_hash_80(int threads, uint32_t startNounce, void *outputHash) |
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{ |
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int thread = (blockDim.x * blockIdx.x + threadIdx.x); |
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if (thread < threads) |
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{ |
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// State vorbereiten |
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uint64_t h[8]; |
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// 128 Byte f<EFBFBD>r die Message |
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uint64_t buf[16]; |
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uint8_t i; |
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// bestimme den aktuellen Z<EFBFBD>hler |
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uint32_t nounce = startNounce + thread; |
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#pragma unroll 8 |
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for(i=0;i<8;i++) |
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h[i] = d_constMem[i]; |
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// Message f<EFBFBD>r die erste Runde in Register holen |
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#pragma unroll 16 |
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for (i=0; i < 16; ++i) buf[i] = c_PaddedMessage80[i]; |
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// die Nounce durch die thread-spezifische ersetzen |
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buf[9] = REPLACE_HIWORD(buf[9], cuda_swab32(nounce)); |
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// die einzige Hashing-Runde |
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quark_blake512_compress( h, buf, c_sigma, c_u512, 640 ); |
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// Hash rauslassen |
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#if __CUDA_ARCH__ >= 130 |
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// ausschliesslich 32 bit Operationen sofern die SM1.3 double intrinsics verf<EFBFBD>gbar sind |
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uint32_t *outHash = (uint32_t *)outputHash + 16 * thread; |
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#pragma unroll 8 |
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for (i=0; i < 8; ++i) { |
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outHash[2*i+0] = cuda_swab32( _HIWORD(h[i]) ); |
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outHash[2*i+1] = cuda_swab32( _LOWORD(h[i]) ); |
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} |
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#else |
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// in dieser Version passieren auch ein paar 64 Bit Shifts |
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uint64_t *outHash = (uint64_t *)outputHash + 8 * thread; |
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#pragma unroll 8 |
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for (i=0; i < 8; ++i) { |
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outHash[i] = cuda_swab64( h[i] ); |
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} |
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#endif |
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} |
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} |
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// ---------------------------- END CUDA quark_blake512 functions ------------------------------------ |
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// Setup-Funktionen |
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__host__ void quark_blake512_cpu_init(int thr_id, int 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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} |
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// Blake512 f<EFBFBD>r 80 Byte grosse Eingangsdaten |
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__host__ void quark_blake512_cpu_setBlock_80(void *pdata) |
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{ |
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// Message mit Padding bereitstellen |
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// lediglich die korrekte Nonce ist noch ab Byte 76 einzusetzen. |
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unsigned char PaddedMessage[128]; |
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memcpy(PaddedMessage, pdata, 80); |
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memset(PaddedMessage+80, 0, 48); |
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PaddedMessage[80] = 0x80; |
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PaddedMessage[111] = 1; |
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PaddedMessage[126] = 0x02; |
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PaddedMessage[127] = 0x80; |
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CUDA_SAFE_CALL( |
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cudaMemcpyToSymbol(c_PaddedMessage80, PaddedMessage, 16*sizeof(uint64_t), 0, cudaMemcpyHostToDevice) |
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); |
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} |
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__host__ void quark_blake512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_outputHash, int order) |
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{ |
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const int 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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// Gr<EFBFBD><EFBFBD>e des dynamischen Shared Memory Bereichs |
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size_t shared_size = 0; |
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quark_blake512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, d_nonceVector, (uint64_t*)d_outputHash); |
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// Strategisches Sleep Kommando zur Senkung der CPU Last |
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MyStreamSynchronize(NULL, order, thr_id); |
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} |
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__host__ void quark_blake512_cpu_hash_80(int thr_id, int threads, uint32_t startNounce, uint32_t *d_outputHash, int order) |
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{ |
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const int 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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// Gr<EFBFBD><EFBFBD>e des dynamischen Shared Memory Bereichs |
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size_t shared_size = 0; |
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quark_blake512_gpu_hash_80<<<grid, block, shared_size>>>(threads, startNounce, d_outputHash); |
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// Strategisches Sleep Kommando zur Senkung der CPU Last |
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MyStreamSynchronize(NULL, order, thr_id); |
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}
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