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622 lines
20 KiB
622 lines
20 KiB
// Auf Myriadcoin spezialisierte Version von Groestl |
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#include <cuda.h> |
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#include "cuda_runtime.h" |
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#include "device_launch_parameters.h" |
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#include <stdio.h> |
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#include <memory.h> |
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// it's unfortunate that this is a compile time constant. |
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#define MAXWELL_OR_FERMI 1 |
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// aus cpu-miner.c |
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extern int device_map[8]; |
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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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// Folgende Definitionen später durch header ersetzen |
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typedef unsigned char uint8_t; |
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typedef unsigned short uint16_t; |
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typedef unsigned int uint32_t; |
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// diese Struktur wird in der Init Funktion angefordert |
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static cudaDeviceProp props; |
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// globaler Speicher für alle HeftyHashes aller Threads |
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__constant__ uint32_t pTarget[8]; // Single GPU |
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extern uint32_t *d_resultNonce[8]; |
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__constant__ uint32_t myriadgroestl_gpu_msg[32]; |
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// muss expandiert werden |
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__constant__ uint32_t myr_sha256_gpu_constantTable[64]; |
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__constant__ uint32_t myr_sha256_gpu_hashTable[8]; |
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uint32_t myr_sha256_cpu_hashTable[] = { |
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0x6a09e667, 0xbb67ae85, 0x3c6ef372, 0xa54ff53a, 0x510e527f, 0x9b05688c, 0x1f83d9ab, 0x5be0cd19 }; |
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uint32_t myr_sha256_cpu_constantTable[] = { |
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0x428a2f98, 0x71374491, 0xb5c0fbcf, 0xe9b5dba5, 0x3956c25b, 0x59f111f1, 0x923f82a4, 0xab1c5ed5, |
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0xd807aa98, 0x12835b01, 0x243185be, 0x550c7dc3, 0x72be5d74, 0x80deb1fe, 0x9bdc06a7, 0xc19bf174, |
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0xe49b69c1, 0xefbe4786, 0x0fc19dc6, 0x240ca1cc, 0x2de92c6f, 0x4a7484aa, 0x5cb0a9dc, 0x76f988da, |
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0x983e5152, 0xa831c66d, 0xb00327c8, 0xbf597fc7, 0xc6e00bf3, 0xd5a79147, 0x06ca6351, 0x14292967, |
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0x27b70a85, 0x2e1b2138, 0x4d2c6dfc, 0x53380d13, 0x650a7354, 0x766a0abb, 0x81c2c92e, 0x92722c85, |
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0xa2bfe8a1, 0xa81a664b, 0xc24b8b70, 0xc76c51a3, 0xd192e819, 0xd6990624, 0xf40e3585, 0x106aa070, |
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0x19a4c116, 0x1e376c08, 0x2748774c, 0x34b0bcb5, 0x391c0cb3, 0x4ed8aa4a, 0x5b9cca4f, 0x682e6ff3, |
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0x748f82ee, 0x78a5636f, 0x84c87814, 0x8cc70208, 0x90befffa, 0xa4506ceb, 0xbef9a3f7, 0xc67178f2, |
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}; |
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#if __CUDA_ARCH__ < 350 |
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// Kepler (Compute 3.0) |
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#define ROTR32(x, n) (((x) >> (n)) | ((x) << (32 - (n)))) |
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#else |
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// Kepler (Compute 3.5) |
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#define ROTR32(x, n) __funnelshift_r( (x), (x), (n) ) |
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#endif |
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#define R(x, n) ((x) >> (n)) |
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#define Ch(x, y, z) ((x & (y ^ z)) ^ z) |
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#define Maj(x, y, z) ((x & (y | z)) | (y & z)) |
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#define S0(x) (ROTR32(x, 2) ^ ROTR32(x, 13) ^ ROTR32(x, 22)) |
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#define S1(x) (ROTR32(x, 6) ^ ROTR32(x, 11) ^ ROTR32(x, 25)) |
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#define s0(x) (ROTR32(x, 7) ^ ROTR32(x, 18) ^ R(x, 3)) |
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#define s1(x) (ROTR32(x, 17) ^ ROTR32(x, 19) ^ R(x, 10)) |
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#define SWAB32(x) ( ((x & 0x000000FF) << 24) | ((x & 0x0000FF00) << 8) | ((x & 0x00FF0000) >> 8) | ((x & 0xFF000000) >> 24) ) |
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__device__ void myriadgroestl_gpu_sha256(uint32_t *message) |
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{ |
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uint32_t W1[16]; |
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uint32_t W2[16]; |
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// Initialisiere die register a bis h mit der Hash-Tabelle |
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uint32_t regs[8]; |
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uint32_t hash[8]; |
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// pre |
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#pragma unroll 8 |
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for (int k=0; k < 8; k++) |
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{ |
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regs[k] = myr_sha256_gpu_hashTable[k]; |
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hash[k] = regs[k]; |
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} |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) |
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W1[k] = SWAB32(message[k]); |
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// Progress W1 |
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#pragma unroll 16 |
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for(int j=0;j<16;j++) |
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{ |
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uint32_t T1, T2; |
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T1 = regs[7] + S1(regs[4]) + Ch(regs[4], regs[5], regs[6]) + myr_sha256_gpu_constantTable[j] + W1[j]; |
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T2 = S0(regs[0]) + Maj(regs[0], regs[1], regs[2]); |
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#pragma unroll 7 |
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for (int k=6; k >= 0; k--) regs[k+1] = regs[k]; |
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regs[0] = T1 + T2; |
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regs[4] += T1; |
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} |
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// Progress W2...W3 |
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#pragma unroll 3 |
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for(int k=0;k<3;k++) |
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{ |
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#pragma unroll 2 |
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for(int j=0;j<2;j++) |
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W2[j] = s1(W1[14+j]) + W1[9+j] + s0(W1[1+j]) + W1[j]; |
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#pragma unroll 5 |
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for(int j=2;j<7;j++) |
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W2[j] = s1(W2[j-2]) + W1[9+j] + s0(W1[1+j]) + W1[j]; |
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#pragma unroll 8 |
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for(int j=7;j<15;j++) |
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W2[j] = s1(W2[j-2]) + W2[j-7] + s0(W1[1+j]) + W1[j]; |
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W2[15] = s1(W2[13]) + W2[8] + s0(W2[0]) + W1[15]; |
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// Rundenfunktion |
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#pragma unroll 16 |
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for(int j=0;j<16;j++) |
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{ |
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uint32_t T1, T2; |
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T1 = regs[7] + S1(regs[4]) + Ch(regs[4], regs[5], regs[6]) + myr_sha256_gpu_constantTable[j + 16 * (k+1)] + W2[j]; |
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T2 = S0(regs[0]) + Maj(regs[0], regs[1], regs[2]); |
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#pragma unroll 7 |
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for (int l=6; l >= 0; l--) regs[l+1] = regs[l]; |
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regs[0] = T1 + T2; |
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regs[4] += T1; |
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} |
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#pragma unroll 16 |
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for(int j=0;j<16;j++) |
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W1[j] = W2[j]; |
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} |
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#pragma unroll 8 |
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for(int k=0;k<8;k++) |
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hash[k] += regs[k]; |
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///// |
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///// Zweite Runde (wegen Msg-Padding) |
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///// |
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#pragma unroll 8 |
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for(int k=0;k<8;k++) |
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regs[k] = hash[k]; |
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W1[0] = SWAB32(0x80); |
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#pragma unroll 14 |
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for(int k=1;k<15;k++) |
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W1[k] = 0; |
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W1[15] = 512; |
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// Progress W1 |
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#pragma unroll 16 |
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for(int j=0;j<16;j++) |
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{ |
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uint32_t T1, T2; |
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T1 = regs[7] + S1(regs[4]) + Ch(regs[4], regs[5], regs[6]) + myr_sha256_gpu_constantTable[j] + W1[j]; |
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T2 = S0(regs[0]) + Maj(regs[0], regs[1], regs[2]); |
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#pragma unroll 7 |
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for (int k=6; k >= 0; k--) regs[k+1] = regs[k]; |
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regs[0] = T1 + T2; |
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regs[4] += T1; |
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} |
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// Progress W2...W3 |
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#pragma unroll 3 |
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for(int k=0;k<3;k++) |
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{ |
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#pragma unroll 2 |
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for(int j=0;j<2;j++) |
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W2[j] = s1(W1[14+j]) + W1[9+j] + s0(W1[1+j]) + W1[j]; |
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#pragma unroll 5 |
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for(int j=2;j<7;j++) |
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W2[j] = s1(W2[j-2]) + W1[9+j] + s0(W1[1+j]) + W1[j]; |
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#pragma unroll 8 |
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for(int j=7;j<15;j++) |
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W2[j] = s1(W2[j-2]) + W2[j-7] + s0(W1[1+j]) + W1[j]; |
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W2[15] = s1(W2[13]) + W2[8] + s0(W2[0]) + W1[15]; |
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// Rundenfunktion |
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#pragma unroll 16 |
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for(int j=0;j<16;j++) |
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{ |
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uint32_t T1, T2; |
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T1 = regs[7] + S1(regs[4]) + Ch(regs[4], regs[5], regs[6]) + myr_sha256_gpu_constantTable[j + 16 * (k+1)] + W2[j]; |
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T2 = S0(regs[0]) + Maj(regs[0], regs[1], regs[2]); |
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#pragma unroll 7 |
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for (int l=6; l >= 0; l--) regs[l+1] = regs[l]; |
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regs[0] = T1 + T2; |
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regs[4] += T1; |
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} |
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#pragma unroll 16 |
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for(int j=0;j<16;j++) |
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W1[j] = W2[j]; |
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} |
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#pragma unroll 8 |
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for(int k=0;k<8;k++) |
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hash[k] += regs[k]; |
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//// FERTIG |
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#pragma unroll 8 |
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for(int k=0;k<8;k++) |
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message[k] = SWAB32(hash[k]); |
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} |
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#define SPH_C32(x) ((uint32_t)(x ## U)) |
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#define SPH_T32(x) ((x) & SPH_C32(0xFFFFFFFF)) |
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#define PC32up(j, r) ((uint32_t)((j) + (r))) |
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#define PC32dn(j, r) 0 |
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#define QC32up(j, r) 0xFFFFFFFF |
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#define QC32dn(j, r) (((uint32_t)(r) << 24) ^ SPH_T32(~((uint32_t)(j) << 24))) |
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#define B32_0(x) __byte_perm(x, 0, 0x4440) |
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//((x) & 0xFF) |
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#define B32_1(x) __byte_perm(x, 0, 0x4441) |
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//(((x) >> 8) & 0xFF) |
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#define B32_2(x) __byte_perm(x, 0, 0x4442) |
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//(((x) >> 16) & 0xFF) |
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#define B32_3(x) __byte_perm(x, 0, 0x4443) |
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//((x) >> 24) |
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#if MAXWELL_OR_FERMI |
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#define USE_SHARED 1 |
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// Maxwell and Fermi cards get the best speed with SHARED access it seems. |
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#if USE_SHARED |
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#define T0up(x) (*((uint32_t*)mixtabs + ( (x)))) |
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#define T0dn(x) (*((uint32_t*)mixtabs + (256+(x)))) |
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#define T1up(x) (*((uint32_t*)mixtabs + (512+(x)))) |
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#define T1dn(x) (*((uint32_t*)mixtabs + (768+(x)))) |
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#define T2up(x) (*((uint32_t*)mixtabs + (1024+(x)))) |
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#define T2dn(x) (*((uint32_t*)mixtabs + (1280+(x)))) |
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#define T3up(x) (*((uint32_t*)mixtabs + (1536+(x)))) |
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#define T3dn(x) (*((uint32_t*)mixtabs + (1792+(x)))) |
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#else |
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#define T0up(x) tex1Dfetch(t0up1, x) |
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#define T0dn(x) tex1Dfetch(t0dn1, x) |
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#define T1up(x) tex1Dfetch(t1up1, x) |
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#define T1dn(x) tex1Dfetch(t1dn1, x) |
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#define T2up(x) tex1Dfetch(t2up1, x) |
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#define T2dn(x) tex1Dfetch(t2dn1, x) |
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#define T3up(x) tex1Dfetch(t3up1, x) |
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#define T3dn(x) tex1Dfetch(t3dn1, x) |
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#endif |
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#else |
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#define USE_SHARED 1 |
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// a healthy mix between shared and textured access provides the highest speed on Compute 3.0 and 3.5! |
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#define T0up(x) (*((uint32_t*)mixtabs + ( (x)))) |
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#define T0dn(x) tex1Dfetch(t0dn1, x) |
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#define T1up(x) tex1Dfetch(t1up1, x) |
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#define T1dn(x) (*((uint32_t*)mixtabs + (768+(x)))) |
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#define T2up(x) tex1Dfetch(t2up1, x) |
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#define T2dn(x) (*((uint32_t*)mixtabs + (1280+(x)))) |
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#define T3up(x) (*((uint32_t*)mixtabs + (1536+(x)))) |
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#define T3dn(x) tex1Dfetch(t3dn1, x) |
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#endif |
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texture<unsigned int, 1, cudaReadModeElementType> t0up1; |
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texture<unsigned int, 1, cudaReadModeElementType> t0dn1; |
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texture<unsigned int, 1, cudaReadModeElementType> t1up1; |
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texture<unsigned int, 1, cudaReadModeElementType> t1dn1; |
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texture<unsigned int, 1, cudaReadModeElementType> t2up1; |
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texture<unsigned int, 1, cudaReadModeElementType> t2dn1; |
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texture<unsigned int, 1, cudaReadModeElementType> t3up1; |
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texture<unsigned int, 1, cudaReadModeElementType> t3dn1; |
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extern uint32_t T0up_cpu[]; |
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extern uint32_t T0dn_cpu[]; |
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extern uint32_t T1up_cpu[]; |
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extern uint32_t T1dn_cpu[]; |
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extern uint32_t T2up_cpu[]; |
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extern uint32_t T2dn_cpu[]; |
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extern uint32_t T3up_cpu[]; |
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extern uint32_t T3dn_cpu[]; |
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#define SWAB32(x) ( ((x & 0x000000FF) << 24) | ((x & 0x0000FF00) << 8) | ((x & 0x00FF0000) >> 8) | ((x & 0xFF000000) >> 24) ) |
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__device__ __forceinline__ void myriadgroestl_perm_P(uint32_t *a, char *mixtabs) |
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{ |
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uint32_t t[32]; |
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//#pragma unroll 14 |
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for(int r=0;r<14;r++) |
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{ |
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switch(r) |
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{ |
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case 0: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 0); break; |
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case 1: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 1); break; |
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case 2: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 2); break; |
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case 3: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 3); break; |
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case 4: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 4); break; |
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case 5: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 5); break; |
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case 6: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 6); break; |
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case 7: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 7); break; |
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case 8: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 8); break; |
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case 9: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 9); break; |
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case 10: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 10); break; |
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case 11: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 11); break; |
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case 12: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 12); break; |
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case 13: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) a[(k*2)+0] ^= PC32up(k * 0x10, 13); break; |
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} |
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// RBTT |
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#pragma unroll 16 |
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for(int k=0;k<32;k+=2) |
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{ |
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uint32_t t0_0 = B32_0(a[(k ) & 0x1f]), t9_0 = B32_0(a[(k + 9) & 0x1f]); |
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uint32_t t2_1 = B32_1(a[(k + 2) & 0x1f]), t11_1 = B32_1(a[(k + 11) & 0x1f]); |
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uint32_t t4_2 = B32_2(a[(k + 4) & 0x1f]), t13_2 = B32_2(a[(k + 13) & 0x1f]); |
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uint32_t t6_3 = B32_3(a[(k + 6) & 0x1f]), t23_3 = B32_3(a[(k + 23) & 0x1f]); |
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t[k + 0] = T0up( t0_0 ) ^ T1up( t2_1 ) ^ T2up( t4_2 ) ^ T3up( t6_3 ) ^ |
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T0dn( t9_0 ) ^ T1dn( t11_1 ) ^ T2dn( t13_2 ) ^ T3dn( t23_3 ); |
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t[k + 1] = T0dn( t0_0 ) ^ T1dn( t2_1 ) ^ T2dn( t4_2 ) ^ T3dn( t6_3 ) ^ |
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T0up( t9_0 ) ^ T1up( t11_1 ) ^ T2up( t13_2 ) ^ T3up( t23_3 ); |
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} |
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#pragma unroll 32 |
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for(int k=0;k<32;k++) |
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a[k] = t[k]; |
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} |
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} |
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__device__ __forceinline__ void myriadgroestl_perm_Q(uint32_t *a, char *mixtabs) |
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{ |
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//#pragma unroll 14 |
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for(int r=0;r<14;r++) |
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{ |
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uint32_t t[32]; |
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switch(r) |
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{ |
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case 0: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 0); a[(k*2)+1] ^= QC32dn(k * 0x10, 0);} break; |
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case 1: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 1); a[(k*2)+1] ^= QC32dn(k * 0x10, 1);} break; |
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case 2: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 2); a[(k*2)+1] ^= QC32dn(k * 0x10, 2);} break; |
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case 3: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 3); a[(k*2)+1] ^= QC32dn(k * 0x10, 3);} break; |
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case 4: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 4); a[(k*2)+1] ^= QC32dn(k * 0x10, 4);} break; |
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case 5: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 5); a[(k*2)+1] ^= QC32dn(k * 0x10, 5);} break; |
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case 6: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 6); a[(k*2)+1] ^= QC32dn(k * 0x10, 6);} break; |
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case 7: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 7); a[(k*2)+1] ^= QC32dn(k * 0x10, 7);} break; |
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case 8: |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 8); a[(k*2)+1] ^= QC32dn(k * 0x10, 8);} break; |
|
case 9: |
|
#pragma unroll 16 |
|
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 9); a[(k*2)+1] ^= QC32dn(k * 0x10, 9);} break; |
|
case 10: |
|
#pragma unroll 16 |
|
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 10); a[(k*2)+1] ^= QC32dn(k * 0x10, 10);} break; |
|
case 11: |
|
#pragma unroll 16 |
|
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 11); a[(k*2)+1] ^= QC32dn(k * 0x10, 11);} break; |
|
case 12: |
|
#pragma unroll 16 |
|
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 12); a[(k*2)+1] ^= QC32dn(k * 0x10, 12);} break; |
|
case 13: |
|
#pragma unroll 16 |
|
for(int k=0;k<16;k++) { a[(k*2)+0] ^= QC32up(k * 0x10, 13); a[(k*2)+1] ^= QC32dn(k * 0x10, 13);} break; |
|
} |
|
|
|
// RBTT |
|
#pragma unroll 16 |
|
for(int k=0;k<32;k+=2) |
|
{ |
|
uint32_t t2_0 = B32_0(a[(k + 2) & 0x1f]), t1_0 = B32_0(a[(k + 1) & 0x1f]); |
|
uint32_t t6_1 = B32_1(a[(k + 6) & 0x1f]), t5_1 = B32_1(a[(k + 5) & 0x1f]); |
|
uint32_t t10_2 = B32_2(a[(k + 10) & 0x1f]), t9_2 = B32_2(a[(k + 9) & 0x1f]); |
|
uint32_t t22_3 = B32_3(a[(k + 22) & 0x1f]), t13_3 = B32_3(a[(k + 13) & 0x1f]); |
|
|
|
t[k + 0] = T0up( t2_0 ) ^ T1up( t6_1 ) ^ T2up( t10_2 ) ^ T3up( t22_3 ) ^ |
|
T0dn( t1_0 ) ^ T1dn( t5_1 ) ^ T2dn( t9_2 ) ^ T3dn( t13_3 ); |
|
|
|
t[k + 1] = T0dn( t2_0 ) ^ T1dn( t6_1 ) ^ T2dn( t10_2 ) ^ T3dn( t22_3 ) ^ |
|
T0up( t1_0 ) ^ T1up( t5_1 ) ^ T2up( t9_2 ) ^ T3up( t13_3 ); |
|
} |
|
#pragma unroll 32 |
|
for(int k=0;k<32;k++) |
|
a[k] = t[k]; |
|
} |
|
} |
|
|
|
__global__ void |
|
myriadgroestl_gpu_hash(int threads, uint32_t startNounce, uint32_t *resNounce) |
|
{ |
|
#if USE_SHARED |
|
extern __shared__ char mixtabs[]; |
|
|
|
if (threadIdx.x < 256) |
|
{ |
|
*((uint32_t*)mixtabs + ( threadIdx.x)) = tex1Dfetch(t0up1, threadIdx.x); |
|
*((uint32_t*)mixtabs + (256+threadIdx.x)) = tex1Dfetch(t0dn1, threadIdx.x); |
|
*((uint32_t*)mixtabs + (512+threadIdx.x)) = tex1Dfetch(t1up1, threadIdx.x); |
|
*((uint32_t*)mixtabs + (768+threadIdx.x)) = tex1Dfetch(t1dn1, threadIdx.x); |
|
*((uint32_t*)mixtabs + (1024+threadIdx.x)) = tex1Dfetch(t2up1, threadIdx.x); |
|
*((uint32_t*)mixtabs + (1280+threadIdx.x)) = tex1Dfetch(t2dn1, threadIdx.x); |
|
*((uint32_t*)mixtabs + (1536+threadIdx.x)) = tex1Dfetch(t3up1, threadIdx.x); |
|
*((uint32_t*)mixtabs + (1792+threadIdx.x)) = tex1Dfetch(t3dn1, threadIdx.x); |
|
} |
|
|
|
__syncthreads(); |
|
#endif |
|
|
|
int thread = (blockDim.x * blockIdx.x + threadIdx.x); |
|
if (thread < threads) |
|
{ |
|
// GROESTL |
|
uint32_t message[32]; |
|
uint32_t state[32]; |
|
|
|
#pragma unroll 32 |
|
for(int k=0;k<32;k++) message[k] = myriadgroestl_gpu_msg[k]; |
|
|
|
uint32_t nounce = startNounce + thread; |
|
message[19] = SWAB32(nounce); |
|
|
|
#pragma unroll 32 |
|
for(int u=0;u<32;u++) state[u] = message[u]; |
|
state[31] ^= 0x20000; |
|
|
|
// Perm |
|
#if USE_SHARED |
|
myriadgroestl_perm_P(state, mixtabs); |
|
state[31] ^= 0x20000; |
|
myriadgroestl_perm_Q(message, mixtabs); |
|
#else |
|
myriadgroestl_perm_P(state, NULL); |
|
state[31] ^= 0x20000; |
|
myriadgroestl_perm_Q(message, NULL); |
|
#endif |
|
#pragma unroll 32 |
|
for(int u=0;u<32;u++) state[u] ^= message[u]; |
|
|
|
#pragma unroll 32 |
|
for(int u=0;u<32;u++) message[u] = state[u]; |
|
|
|
#if USE_SHARED |
|
myriadgroestl_perm_P(message, mixtabs); |
|
#else |
|
myriadgroestl_perm_P(message, NULL); |
|
#endif |
|
|
|
#pragma unroll 32 |
|
for(int u=0;u<32;u++) state[u] ^= message[u]; |
|
|
|
uint32_t out_state[16]; |
|
#pragma unroll 16 |
|
for(int u=0;u<16;u++) out_state[u] = state[u+16]; |
|
myriadgroestl_gpu_sha256(out_state); |
|
|
|
int i, position = -1; |
|
bool rc = true; |
|
|
|
#pragma unroll 8 |
|
for (i = 7; i >= 0; i--) { |
|
if (out_state[i] > pTarget[i]) { |
|
if(position < i) { |
|
position = i; |
|
rc = false; |
|
} |
|
} |
|
if (out_state[i] < pTarget[i]) { |
|
if(position < i) { |
|
position = i; |
|
rc = true; |
|
} |
|
} |
|
} |
|
|
|
if(rc == true) |
|
if(resNounce[0] > nounce) |
|
resNounce[0] = nounce; |
|
} |
|
} |
|
|
|
#define texDef(texname, texmem, texsource, texsize) \ |
|
unsigned int *texmem; \ |
|
cudaMalloc(&texmem, texsize); \ |
|
cudaMemcpy(texmem, texsource, texsize, cudaMemcpyHostToDevice); \ |
|
texname.normalized = 0; \ |
|
texname.filterMode = cudaFilterModePoint; \ |
|
texname.addressMode[0] = cudaAddressModeClamp; \ |
|
{ cudaChannelFormatDesc channelDesc = cudaCreateChannelDesc<unsigned int>(); \ |
|
cudaBindTexture(NULL, &texname, texmem, &channelDesc, texsize ); } \ |
|
|
|
// Setup-Funktionen |
|
__host__ void myriadgroestl_cpu_init(int thr_id, int threads) |
|
{ |
|
cudaSetDevice(device_map[thr_id]); |
|
|
|
cudaMemcpyToSymbol( myr_sha256_gpu_hashTable, |
|
myr_sha256_cpu_hashTable, |
|
sizeof(uint32_t) * 8 ); |
|
|
|
cudaMemcpyToSymbol( myr_sha256_gpu_constantTable, |
|
myr_sha256_cpu_constantTable, |
|
sizeof(uint32_t) * 64 ); |
|
|
|
cudaGetDeviceProperties(&props, device_map[thr_id]); |
|
|
|
// Texturen mit obigem Makro initialisieren |
|
texDef(t0up1, d_T0up, T0up_cpu, sizeof(uint32_t)*256); |
|
texDef(t0dn1, d_T0dn, T0dn_cpu, sizeof(uint32_t)*256); |
|
texDef(t1up1, d_T1up, T1up_cpu, sizeof(uint32_t)*256); |
|
texDef(t1dn1, d_T1dn, T1dn_cpu, sizeof(uint32_t)*256); |
|
texDef(t2up1, d_T2up, T2up_cpu, sizeof(uint32_t)*256); |
|
texDef(t2dn1, d_T2dn, T2dn_cpu, sizeof(uint32_t)*256); |
|
texDef(t3up1, d_T3up, T3up_cpu, sizeof(uint32_t)*256); |
|
texDef(t3dn1, d_T3dn, T3dn_cpu, sizeof(uint32_t)*256); |
|
|
|
// Speicher für Gewinner-Nonce belegen |
|
cudaMalloc(&d_resultNonce[thr_id], sizeof(uint32_t)); |
|
} |
|
|
|
__host__ void myriadgroestl_cpu_setBlock(int thr_id, void *data, void *pTargetIn) |
|
{ |
|
// Nachricht expandieren und setzen |
|
uint32_t msgBlock[32]; |
|
|
|
memset(msgBlock, 0, sizeof(uint32_t) * 32); |
|
memcpy(&msgBlock[0], data, 80); |
|
|
|
// Erweitere die Nachricht auf den Nachrichtenblock (padding) |
|
// Unsere Nachricht hat 80 Byte |
|
msgBlock[20] = 0x80; |
|
msgBlock[31] = 0x01000000; |
|
|
|
// groestl512 braucht hierfür keinen CPU-Code (die einzige Runde wird |
|
// auf der GPU ausgeführt) |
|
|
|
// Blockheader setzen (korrekte Nonce und Hefty Hash fehlen da drin noch) |
|
cudaMemcpyToSymbol( myriadgroestl_gpu_msg, |
|
msgBlock, |
|
128); |
|
|
|
cudaMemset(d_resultNonce[thr_id], 0xFF, sizeof(uint32_t)); |
|
cudaMemcpyToSymbol( pTarget, |
|
pTargetIn, |
|
sizeof(uint32_t) * 8 ); |
|
} |
|
|
|
__host__ void myriadgroestl_cpu_hash(int thr_id, int threads, uint32_t startNounce, void *outputHashes, uint32_t *nounce) |
|
{ |
|
// Compute 3.x und 5.x Geräte am besten mit 768 Threads ansteuern, |
|
// alle anderen mit 512 Threads. |
|
int threadsperblock = (props.major >= 3) ? 768 : 512; |
|
|
|
// berechne wie viele Thread Blocks wir brauchen |
|
dim3 grid((threads + threadsperblock-1)/threadsperblock); |
|
dim3 block(threadsperblock); |
|
|
|
// Größe des dynamischen Shared Memory Bereichs |
|
#if USE_SHARED |
|
size_t shared_size = 8 * 256 * sizeof(uint32_t); |
|
#else |
|
size_t shared_size = 0; |
|
#endif |
|
|
|
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size); |
|
//fprintf(stderr, "ThrID: %d\n", thr_id); |
|
cudaMemset(d_resultNonce[thr_id], 0xFF, sizeof(uint32_t)); |
|
myriadgroestl_gpu_hash<<<grid, block, shared_size>>>(threads, startNounce, d_resultNonce[thr_id]); |
|
|
|
// Strategisches Sleep Kommando zur Senkung der CPU Last |
|
MyStreamSynchronize(NULL, 0, thr_id); |
|
|
|
cudaMemcpy(nounce, d_resultNonce[thr_id], sizeof(uint32_t), cudaMemcpyDeviceToHost); |
|
}
|
|
|