// aus heavy.cu extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id); typedef unsigned int uint32_t; typedef unsigned long long uint64_t; #define C32(x) ((uint32_t)(x ## U)) #define T32(x) ((x) & C32(0xFFFFFFFF)) #if __CUDA_ARCH__ < 350 // Kepler (Compute 3.0) #define ROTL32(x, n) T32(((x) << (n)) | ((x) >> (32 - (n)))) #else // Kepler (Compute 3.5) #define ROTL32(x, n) __funnelshift_l( (x), (x), (n) ) #endif __constant__ uint32_t c_IV_512[32]; const uint32_t h_IV_512[32] = { 0x0ba16b95, 0x72f999ad, 0x9fecc2ae, 0xba3264fc, 0x5e894929, 0x8e9f30e5, 0x2f1daa37, 0xf0f2c558, 0xac506643, 0xa90635a5, 0xe25b878b, 0xaab7878f, 0x88817f7a, 0x0a02892b, 0x559a7550, 0x598f657e, 0x7eef60a1, 0x6b70e3e8, 0x9c1714d1, 0xb958e2a8, 0xab02675e, 0xed1c014f, 0xcd8d65bb, 0xfdb7a257, 0x09254899, 0xd699c7bc, 0x9019b6dc, 0x2b9022e4, 0x8fa14956, 0x21bf9bd3, 0xb94d0943, 0x6ffddc22 }; __constant__ int c_FFT[256]; const int h_FFT[256] = { // this is the FFT result in revbin permuted order 4, -4, 32, -32, -60, 60, 60, -60, 101, -101, 58, -58, 112, -112, -11, 11, -92, 92, -119, 119, 42, -42, -82, 82, 32, -32, 32, -32, 121, -121, 17, -17, -47, 47, 63, -63, 107, -107, -76, 76, -119, 119, -83, 83, 126, -126, 94, -94, -23, 23, -76, 76, -47, 47, 92, -92, -117, 117, 73, -73, -53, 53, 88, -88, -80, 80, -47, 47, 5, -5, 67, -67, 34, -34, 4, -4, 87, -87, -28, 28, -70, 70, -110, 110, -18, 18, 93, -93, 51, -51, 36, -36, 118, -118, -106, 106, 45, -45, -108, 108, -44, 44, 117, -117, -121, 121, -37, 37, 65, -65, 37, -37, 40, -40, -42, 42, 91, -91, -128, 128, -21, 21, 94, -94, -98, 98, -47, 47, 28, -28, 115, -115, 16, -16, -20, 20, 122, -122, 115, -115, 46, -46, 84, -84, -127, 127, 57, -57, 127, -127, -80, 80, 24, -24, 15, -15, 29, -29, -78, 78, -126, 126, 16, -16, 52, -52, 55, -55, 110, -110, -51, 51, -120, 120, -124, 124, -24, 24, -76, 76, 26, -26, -21, 21, -64, 64, -99, 99, 85, -85, -15, 15, -120, 120, -116, 116, 85, -85, 12, -12, -24, 24, 4, -4, 79, -79, 76, -76, 23, -23, 4, -4, -108, 108, -20, 20, 73, -73, -42, 42, -7, 7, -29, 29, -123, 123, 49, -49, -96, 96, -68, 68, -112, 112, 116, -116, -24, 24, 93, -93, -125, 125, -86, 86, 117, -117, -91, 91, 42, -42, 87, -87, -117, 117, 102, -102 }; __constant__ int c_P8[32][8]; static const int h_P8[32][8] = { { 2, 66, 34, 98, 18, 82, 50, 114 }, { 6, 70, 38, 102, 22, 86, 54, 118 }, { 0, 64, 32, 96, 16, 80, 48, 112 }, { 4, 68, 36, 100, 20, 84, 52, 116 }, { 14, 78, 46, 110, 30, 94, 62, 126 }, { 10, 74, 42, 106, 26, 90, 58, 122 }, { 12, 76, 44, 108, 28, 92, 60, 124 }, { 8, 72, 40, 104, 24, 88, 56, 120 }, { 15, 79, 47, 111, 31, 95, 63, 127 }, { 13, 77, 45, 109, 29, 93, 61, 125 }, { 3, 67, 35, 99, 19, 83, 51, 115 }, { 1, 65, 33, 97, 17, 81, 49, 113 }, { 9, 73, 41, 105, 25, 89, 57, 121 }, { 11, 75, 43, 107, 27, 91, 59, 123 }, { 5, 69, 37, 101, 21, 85, 53, 117 }, { 7, 71, 39, 103, 23, 87, 55, 119 }, { 8, 72, 40, 104, 24, 88, 56, 120 }, { 4, 68, 36, 100, 20, 84, 52, 116 }, { 14, 78, 46, 110, 30, 94, 62, 126 }, { 2, 66, 34, 98, 18, 82, 50, 114 }, { 6, 70, 38, 102, 22, 86, 54, 118 }, { 10, 74, 42, 106, 26, 90, 58, 122 }, { 0, 64, 32, 96, 16, 80, 48, 112 }, { 12, 76, 44, 108, 28, 92, 60, 124 }, { 134, 198, 166, 230, 150, 214, 182, 246 }, { 128, 192, 160, 224, 144, 208, 176, 240 }, { 136, 200, 168, 232, 152, 216, 184, 248 }, { 142, 206, 174, 238, 158, 222, 190, 254 }, { 140, 204, 172, 236, 156, 220, 188, 252 }, { 138, 202, 170, 234, 154, 218, 186, 250 }, { 130, 194, 162, 226, 146, 210, 178, 242 }, { 132, 196, 164, 228, 148, 212, 180, 244 }, }; __constant__ int c_Q8[32][8]; static const int h_Q8[32][8] = { { 130, 194, 162, 226, 146, 210, 178, 242 }, { 134, 198, 166, 230, 150, 214, 182, 246 }, { 128, 192, 160, 224, 144, 208, 176, 240 }, { 132, 196, 164, 228, 148, 212, 180, 244 }, { 142, 206, 174, 238, 158, 222, 190, 254 }, { 138, 202, 170, 234, 154, 218, 186, 250 }, { 140, 204, 172, 236, 156, 220, 188, 252 }, { 136, 200, 168, 232, 152, 216, 184, 248 }, { 143, 207, 175, 239, 159, 223, 191, 255 }, { 141, 205, 173, 237, 157, 221, 189, 253 }, { 131, 195, 163, 227, 147, 211, 179, 243 }, { 129, 193, 161, 225, 145, 209, 177, 241 }, { 137, 201, 169, 233, 153, 217, 185, 249 }, { 139, 203, 171, 235, 155, 219, 187, 251 }, { 133, 197, 165, 229, 149, 213, 181, 245 }, { 135, 199, 167, 231, 151, 215, 183, 247 }, { 9, 73, 41, 105, 25, 89, 57, 121 }, { 5, 69, 37, 101, 21, 85, 53, 117 }, { 15, 79, 47, 111, 31, 95, 63, 127 }, { 3, 67, 35, 99, 19, 83, 51, 115 }, { 7, 71, 39, 103, 23, 87, 55, 119 }, { 11, 75, 43, 107, 27, 91, 59, 123 }, { 1, 65, 33, 97, 17, 81, 49, 113 }, { 13, 77, 45, 109, 29, 93, 61, 125 }, { 135, 199, 167, 231, 151, 215, 183, 247 }, { 129, 193, 161, 225, 145, 209, 177, 241 }, { 137, 201, 169, 233, 153, 217, 185, 249 }, { 143, 207, 175, 239, 159, 223, 191, 255 }, { 141, 205, 173, 237, 157, 221, 189, 253 }, { 139, 203, 171, 235, 155, 219, 187, 251 }, { 131, 195, 163, 227, 147, 211, 179, 243 }, { 133, 197, 165, 229, 149, 213, 181, 245 }, }; __constant__ int c_FFT128_8_16_Twiddle[128]; static const int h_FFT128_8_16_Twiddle[128] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 60, 2, 120, 4, -17, 8, -34, 16, -68, 32, 121, 64, -15, 128, -30, 1, 46, 60, -67, 2, 92, 120, 123, 4, -73, -17, -11, 8, 111, -34, -22, 1, -67, 120, -73, 8, -22, -68, -70, 64, 81, -30, -46, -2, -123, 17, -111, 1, -118, 46, -31, 60, 116, -67, -61, 2, 21, 92, -62, 120, -25, 123, -122, 1, 116, 92, -122, -17, 84, -22, 18, 32, 114, 117, -49, -30, 118, 67, 62, 1, -31, -67, 21, 120, -122, -73, -50, 8, 9, -22, -89, -68, 52, -70, 114, 1, -61, 123, -50, -34, 18, -70, -99, 128, -98, 67, 25, 17, -9, 35, -79}; __constant__ int c_FFT256_2_128_Twiddle[128]; static const int h_FFT256_2_128_Twiddle[128] = { 1, 41, -118, 45, 46, 87, -31, 14, 60, -110, 116, -127, -67, 80, -61, 69, 2, 82, 21, 90, 92, -83, -62, 28, 120, 37, -25, 3, 123, -97, -122, -119, 4, -93, 42, -77, -73, 91, -124, 56, -17, 74, -50, 6, -11, 63, 13, 19, 8, 71, 84, 103, 111, -75, 9, 112, -34, -109, -100, 12, -22, 126, 26, 38, 16, -115, -89, -51, -35, 107, 18, -33, -68, 39, 57, 24, -44, -5, 52, 76, 32, 27, 79, -102, -70, -43, 36, -66, 121, 78, 114, 48, -88, -10, 104, -105, 64, 54, -99, 53, 117, -86, 72, 125, -15, -101, -29, 96, 81, -20, -49, 47, 128, 108, 59, 106, -23, 85, -113, -7, -30, 55, -58, -65, -95, -40, -98, 94}; #define p8_xor(x) ( ((x)%7) == 0 ? 1 : \ ((x)%7) == 1 ? 6 : \ ((x)%7) == 2 ? 2 : \ ((x)%7) == 3 ? 3 : \ ((x)%7) == 4 ? 5 : \ ((x)%7) == 5 ? 7 : \ 4 ) /************* the round function ****************/ #define IF(x, y, z) ((((y) ^ (z)) & (x)) ^ (z)) #define MAJ(x, y, z) (((z) & (y)) | (((z) | (y)) & (x))) __device__ __forceinline__ void STEP8_IF(const uint32_t *w, const int i, const int r, const int s, uint32_t *A, const uint32_t *B, const uint32_t *C, uint32_t *D) { int j; uint32_t R[8]; #pragma unroll 8 for(j=0; j<8; j++) { R[j] = ROTL32(A[j], r); } #pragma unroll 8 for(j=0; j<8; j++) { D[j] = D[j] + w[j] + IF(A[j], B[j], C[j]); D[j] = T32(ROTL32(T32(D[j]), s) + R[j^p8_xor(i)]); A[j] = R[j]; } } __device__ __forceinline__ void STEP8_MAJ(const uint32_t *w, const int i, const int r, const int s, uint32_t *A, const uint32_t *B, const uint32_t *C, uint32_t *D) { int j; uint32_t R[8]; #pragma unroll 8 for(j=0; j<8; j++) { R[j] = ROTL32(A[j], r); } #pragma unroll 8 for(j=0; j<8; j++) { D[j] = D[j] + w[j] + MAJ(A[j], B[j], C[j]); D[j] = T32(ROTL32(T32(D[j]), s) + R[j^p8_xor(i)]); A[j] = R[j]; } } __device__ __forceinline__ void Round8(uint32_t A[32], const int y[256], int i, int r, int s, int t, int u) { int code = i<2? 185: 233; uint32_t w[8][8]; int a, b; /* * The FFT output y is in revbin permuted order, * but this is included in the tables P and Q */ #pragma unroll 8 for(a=0; a<8; a++) #pragma unroll 8 for(b=0; b<8; b++) w[a][b] = __byte_perm( (y[c_P8[8*i+a][b]] * code), (y[c_Q8[8*i+a][b]] * code), 0x5410); STEP8_IF(w[0], 8*i+0, r, s, A, &A[8], &A[16], &A[24]); STEP8_IF(w[1], 8*i+1, s, t, &A[24], A, &A[8], &A[16]); STEP8_IF(w[2], 8*i+2, t, u, &A[16], &A[24], A, &A[8]); STEP8_IF(w[3], 8*i+3, u, r, &A[8], &A[16], &A[24], A); STEP8_MAJ(w[4], 8*i+4, r, s, A, &A[8], &A[16], &A[24]); STEP8_MAJ(w[5], 8*i+5, s, t, &A[24], A, &A[8], &A[16]); STEP8_MAJ(w[6], 8*i+6, t, u, &A[16], &A[24], A, &A[8]); STEP8_MAJ(w[7], 8*i+7, u, r, &A[8], &A[16], &A[24], A); } /********************* Message expansion ************************/ /* * Reduce modulo 257; result is in [-127; 383] * REDUCE(x) := (x&255) - (x>>8) */ #define REDUCE(x) (((x)&255) - ((x)>>8)) /* * Reduce from [-127; 383] to [-128; 128] * EXTRA_REDUCE_S(x) := x<=128 ? x : x-257 */ #define EXTRA_REDUCE_S(x) \ ((x)<=128 ? (x) : (x)-257) /* * Reduce modulo 257; result is in [-128; 128] */ #define REDUCE_FULL_S(x) \ EXTRA_REDUCE_S(REDUCE(x)) __device__ __forceinline__ void FFT_8(int *y, int stripe) { /* * FFT_8 using w=4 as 8th root of unity * Unrolled decimation in frequency (DIF) radix-2 NTT. * Output data is in revbin_permuted order. */ #define X(i) y[stripe*i] #define DO_REDUCE(i) \ X(i) = REDUCE(X(i)) #define DO_REDUCE_FULL_S(i) \ do { \ X(i) = REDUCE(X(i)); \ X(i) = EXTRA_REDUCE_S(X(i)); \ } while(0) #define BUTTERFLY(i,j,n) \ do { \ int u= X(i); \ int v= X(j); \ X(i) = u+v; \ X(j) = (u-v) << (2*n); \ } while(0) BUTTERFLY(0, 4, 0); BUTTERFLY(1, 5, 1); BUTTERFLY(2, 6, 2); BUTTERFLY(3, 7, 3); DO_REDUCE(6); DO_REDUCE(7); BUTTERFLY(0, 2, 0); BUTTERFLY(4, 6, 0); BUTTERFLY(1, 3, 2); BUTTERFLY(5, 7, 2); DO_REDUCE(7); BUTTERFLY(0, 1, 0); BUTTERFLY(2, 3, 0); BUTTERFLY(4, 5, 0); BUTTERFLY(6, 7, 0); DO_REDUCE_FULL_S(0); DO_REDUCE_FULL_S(1); DO_REDUCE_FULL_S(2); DO_REDUCE_FULL_S(3); DO_REDUCE_FULL_S(4); DO_REDUCE_FULL_S(5); DO_REDUCE_FULL_S(6); DO_REDUCE_FULL_S(7); #undef X #undef DO_REDUCE #undef DO_REDUCE_FULL_S #undef BUTTERFLY } __device__ __forceinline__ void FFT_16(int *y, int stripe) { /* * FFT_16 using w=2 as 16th root of unity * Unrolled decimation in frequency (DIF) radix-2 NTT. * Output data is in revbin_permuted order. */ #define X(i) y[stripe*i] #define DO_REDUCE(i) \ X(i) = REDUCE(X(i)) #define DO_REDUCE_FULL_S(i) \ do { \ X(i) = REDUCE(X(i)); \ X(i) = EXTRA_REDUCE_S(X(i)); \ } while(0) #define BUTTERFLY(i,j,n) \ do { \ int u= X(i); \ int v= X(j); \ X(i) = u+v; \ X(j) = (u-v) << n; \ } while(0) BUTTERFLY(0, 8, 0); BUTTERFLY(1, 9, 1); BUTTERFLY(2, 10, 2); BUTTERFLY(3, 11, 3); BUTTERFLY(4, 12, 4); BUTTERFLY(5, 13, 5); BUTTERFLY(6, 14, 6); BUTTERFLY(7, 15, 7); DO_REDUCE(11); DO_REDUCE(12); DO_REDUCE(13); DO_REDUCE(14); DO_REDUCE(15); BUTTERFLY( 0, 4, 0); BUTTERFLY( 1, 5, 2); BUTTERFLY( 2, 6, 4); BUTTERFLY( 3, 7, 6); BUTTERFLY( 8, 12, 0); BUTTERFLY( 9, 13, 2); BUTTERFLY(10, 14, 4); BUTTERFLY(11, 15, 6); DO_REDUCE(5); DO_REDUCE(7); DO_REDUCE(13); DO_REDUCE(15); BUTTERFLY( 0, 2, 0); BUTTERFLY( 1, 3, 4); BUTTERFLY( 4, 6, 0); BUTTERFLY( 5, 7, 4); BUTTERFLY( 8, 10, 0); BUTTERFLY(12, 14, 0); BUTTERFLY( 9, 11, 4); BUTTERFLY(13, 15, 4); BUTTERFLY( 0, 1, 0); BUTTERFLY( 2, 3, 0); BUTTERFLY( 4, 5, 0); BUTTERFLY( 6, 7, 0); BUTTERFLY( 8, 9, 0); BUTTERFLY(10, 11, 0); BUTTERFLY(12, 13, 0); BUTTERFLY(14, 15, 0); DO_REDUCE_FULL_S( 0); DO_REDUCE_FULL_S( 1); DO_REDUCE_FULL_S( 2); DO_REDUCE_FULL_S( 3); DO_REDUCE_FULL_S( 4); DO_REDUCE_FULL_S( 5); DO_REDUCE_FULL_S( 6); DO_REDUCE_FULL_S( 7); DO_REDUCE_FULL_S( 8); DO_REDUCE_FULL_S( 9); DO_REDUCE_FULL_S(10); DO_REDUCE_FULL_S(11); DO_REDUCE_FULL_S(12); DO_REDUCE_FULL_S(13); DO_REDUCE_FULL_S(14); DO_REDUCE_FULL_S(15); #undef X #undef DO_REDUCE #undef DO_REDUCE_FULL_S #undef BUTTERFLY } __device__ __forceinline__ void FFT_128_full(int *y) { int i; #pragma unroll 16 for (i=0; i<16; i++) { FFT_8(y+i,16); } #pragma unroll 128 for (i=0; i<128; i++) /*if (i & 7)*/ y[i] = REDUCE(y[i]*c_FFT128_8_16_Twiddle[i]); #pragma unroll 8 for (i=0; i<8; i++) { FFT_16(y+16*i,1); } } __device__ __forceinline__ void FFT_256_halfzero(int y[256]) { int i; /* * FFT_256 using w=41 as 256th root of unity. * Decimation in frequency (DIF) NTT. * Output data is in revbin_permuted order. * In place. */ const int tmp = y[127]; #pragma unroll 127 for (i=0; i<127; i++) y[128+i] = REDUCE(y[i] * c_FFT256_2_128_Twiddle[i]); /* handle X^255 with an additionnal butterfly */ y[127] = REDUCE(tmp + 1); y[255] = REDUCE((tmp - 1) * c_FFT256_2_128_Twiddle[127]); FFT_128_full(y); FFT_128_full(y+128); } __device__ __forceinline__ void SIMD_Compress(uint32_t A[32], const int *expanded, const uint32_t *M) { uint32_t IV[4][8]; int i; /* Save the chaining value for the feed-forward */ #pragma unroll 8 for(i=0; i<8; i++) { IV[0][i] = A[i]; IV[1][i] = (&A[8])[i]; IV[2][i] = (&A[16])[i]; IV[3][i] = (&A[24])[i]; } /* XOR the message to the chaining value */ /* we can XOR word-by-word */ { #pragma unroll 8 for(i=0; i<8; i++) { A[i] ^= M[i]; (&A[8])[i] ^= M[8+i]; } } /* Run the feistel ladders with the expanded message */ { Round8(A, expanded, 0, 3, 23, 17, 27); Round8(A, expanded, 1, 28, 19, 22, 7); Round8(A, expanded, 2, 29, 9, 15, 5); Round8(A, expanded, 3, 4, 13, 10, 25); STEP8_IF(IV[0], 32, 4, 13, A, &A[8], &A[16], &A[24]); STEP8_IF(IV[1], 33, 13, 10, &A[24], A, &A[8], &A[16]); STEP8_IF(IV[2], 34, 10, 25, &A[16], &A[24], A, &A[8]); STEP8_IF(IV[3], 35, 25, 4, &A[8], &A[16], &A[24], A); } } /***************************************************/ __device__ __forceinline__ void SIMDHash(const uint32_t *data, uint32_t *hashval) { uint32_t A[32]; int i; uint32_t buffer[16]; #pragma unroll 32 for (i=0; i < 32; i++) A[i] = c_IV_512[i]; #pragma unroll 16 for (i=0; i < 16; i++) buffer[i] = data[i]; /* Message Expansion using Number Theoretical Transform similar to FFT */ int expanded[256]; { #pragma unroll 16 for(i=0; i<64; i+=4) { expanded[i+0] = __byte_perm(buffer[i/4],0,0x4440); expanded[i+1] = __byte_perm(buffer[i/4],0,0x4441); expanded[i+2] = __byte_perm(buffer[i/4],0,0x4442); expanded[i+3] = __byte_perm(buffer[i/4],0,0x4443); } #pragma unroll 16 for(i=64; i<128; i+=4) { expanded[i+0] = 0; expanded[i+1] = 0; expanded[i+2] = 0; expanded[i+3] = 0; } FFT_256_halfzero(expanded); } /* Compression Function */ SIMD_Compress(A, expanded, buffer); /* Padding Round with known input (hence the FFT can be precomputed) */ buffer[0] = 512; #pragma unroll 15 for (i=1; i < 16; i++) buffer[i] = 0; SIMD_Compress(A, c_FFT, buffer); #pragma unroll 16 for (i=0; i < 16; i++) hashval[i] = A[i]; } /***************************************************/ // Die Hash-Funktion __global__ void x11_simd512_gpu_hash_64(int threads, uint32_t startNounce, uint64_t *g_hash, uint32_t *g_nonceVector) { int thread = (blockDim.x * blockIdx.x + threadIdx.x); if (thread < threads) { uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread); int hashPosition = nounce - startNounce; uint32_t *Hash = (uint32_t*)&g_hash[8 * hashPosition]; SIMDHash(Hash, Hash); } } // Setup-Funktionen __host__ void x11_simd512_cpu_init(int thr_id, int threads) { cudaMemcpyToSymbol( c_IV_512, h_IV_512, sizeof(h_IV_512), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol( c_FFT, h_FFT, sizeof(h_FFT), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol( c_P8, h_P8, sizeof(h_P8), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol( c_Q8, h_Q8, sizeof(h_Q8), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol( c_FFT128_8_16_Twiddle, h_FFT128_8_16_Twiddle, sizeof(h_FFT128_8_16_Twiddle), 0, cudaMemcpyHostToDevice); cudaMemcpyToSymbol( c_FFT256_2_128_Twiddle, h_FFT256_2_128_Twiddle, sizeof(h_FFT256_2_128_Twiddle), 0, cudaMemcpyHostToDevice); } __host__ void x11_simd512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order) { 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); x11_simd512_gpu_hash_64<<>>(threads, startNounce, (uint64_t*)d_hash, d_nonceVector); MyStreamSynchronize(NULL, order, thr_id); }