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397 lines
15 KiB
397 lines
15 KiB
// Auf QuarkCoin 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 int uint32_t; |
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typedef unsigned long long uint64_t; |
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// diese Struktur wird in der Init Funktion angefordert |
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static cudaDeviceProp props[8]; |
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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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__device__ __forceinline__ void quark_groestl512_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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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<< 4, 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 quark_groestl512_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<< 4, 0); a[(k*2)+1] ^= QC32dn(k<< 4, 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<< 4, 1); a[(k*2)+1] ^= QC32dn(k<< 4, 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<< 4, 2); a[(k*2)+1] ^= QC32dn(k<< 4, 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<< 4, 3); a[(k*2)+1] ^= QC32dn(k<< 4, 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<< 4, 4); a[(k*2)+1] ^= QC32dn(k<< 4, 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<< 4, 5); a[(k*2)+1] ^= QC32dn(k<< 4, 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<< 4, 6); a[(k*2)+1] ^= QC32dn(k<< 4, 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<< 4, 7); a[(k*2)+1] ^= QC32dn(k<< 4, 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<< 4, 8); a[(k*2)+1] ^= QC32dn(k<< 4, 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] ^= QC32up(k<< 4, 9); a[(k*2)+1] ^= QC32dn(k<< 4, 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] ^= QC32up(k<< 4, 10); a[(k*2)+1] ^= QC32dn(k<< 4, 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] ^= QC32up(k<< 4, 11); a[(k*2)+1] ^= QC32dn(k<< 4, 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] ^= QC32up(k<< 4, 12); a[(k*2)+1] ^= QC32dn(k<< 4, 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] ^= QC32up(k<< 4, 13); a[(k*2)+1] ^= QC32dn(k<< 4, 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 t2_0 = B32_0(a[(k + 2) & 0x1f]), t1_0 = B32_0(a[(k + 1) & 0x1f]); |
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uint32_t t6_1 = B32_1(a[(k + 6) & 0x1f]), t5_1 = B32_1(a[(k + 5) & 0x1f]); |
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uint32_t t10_2 = B32_2(a[(k + 10) & 0x1f]), t9_2 = B32_2(a[(k + 9) & 0x1f]); |
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uint32_t t22_3 = B32_3(a[(k + 22) & 0x1f]), t13_3 = B32_3(a[(k + 13) & 0x1f]); |
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t[k + 0] = T0up( t2_0 ) ^ T1up( t6_1 ) ^ T2up( t10_2 ) ^ T3up( t22_3 ) ^ |
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T0dn( t1_0 ) ^ T1dn( t5_1 ) ^ T2dn( t9_2 ) ^ T3dn( t13_3 ); |
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t[k + 1] = T0dn( t2_0 ) ^ T1dn( t6_1 ) ^ T2dn( t10_2 ) ^ T3dn( t22_3 ) ^ |
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T0up( t1_0 ) ^ T1up( t5_1 ) ^ T2up( t9_2 ) ^ T3up( t13_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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__global__ void quark_groestl512_gpu_hash_64(int threads, uint32_t startNounce, uint32_t *g_hash, uint32_t *g_nonceVector) |
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{ |
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#if USE_SHARED |
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extern __shared__ char mixtabs[]; |
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if (threadIdx.x < 256) |
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{ |
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*((uint32_t*)mixtabs + ( threadIdx.x)) = tex1Dfetch(t0up1, threadIdx.x); |
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*((uint32_t*)mixtabs + (256+threadIdx.x)) = tex1Dfetch(t0dn1, threadIdx.x); |
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*((uint32_t*)mixtabs + (512+threadIdx.x)) = tex1Dfetch(t1up1, threadIdx.x); |
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*((uint32_t*)mixtabs + (768+threadIdx.x)) = tex1Dfetch(t1dn1, threadIdx.x); |
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*((uint32_t*)mixtabs + (1024+threadIdx.x)) = tex1Dfetch(t2up1, threadIdx.x); |
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*((uint32_t*)mixtabs + (1280+threadIdx.x)) = tex1Dfetch(t2dn1, threadIdx.x); |
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*((uint32_t*)mixtabs + (1536+threadIdx.x)) = tex1Dfetch(t3up1, threadIdx.x); |
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*((uint32_t*)mixtabs + (1792+threadIdx.x)) = tex1Dfetch(t3dn1, threadIdx.x); |
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} |
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__syncthreads(); |
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#endif |
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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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// GROESTL |
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uint32_t message[32]; |
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uint32_t state[32]; |
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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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uint32_t *inpHash = &g_hash[16 * hashPosition]; |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) message[k] = inpHash[k]; |
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#pragma unroll 14 |
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for(int k=1;k<15;k++) |
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message[k+16] = 0; |
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message[16] = 0x80; |
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message[31] = 0x01000000; |
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#pragma unroll 32 |
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for(int u=0;u<32;u++) state[u] = message[u]; |
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state[31] ^= 0x20000; |
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// Perm |
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#if USE_SHARED |
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quark_groestl512_perm_P(state, mixtabs); |
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state[31] ^= 0x20000; |
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quark_groestl512_perm_Q(message, mixtabs); |
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#else |
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quark_groestl512_perm_P(state, NULL); |
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state[31] ^= 0x20000; |
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quark_groestl512_perm_Q(message, NULL); |
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#endif |
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#pragma unroll 32 |
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for(int u=0;u<32;u++) state[u] ^= message[u]; |
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#pragma unroll 32 |
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for(int u=0;u<32;u++) message[u] = state[u]; |
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#if USE_SHARED |
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quark_groestl512_perm_P(message, mixtabs); |
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#else |
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quark_groestl512_perm_P(message, NULL); |
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#endif |
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#pragma unroll 32 |
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for(int u=0;u<32;u++) state[u] ^= message[u]; |
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// Erzeugten Hash rausschreiben |
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uint32_t *outpHash = &g_hash[16 * hashPosition]; |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) outpHash[k] = state[k+16]; |
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} |
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} |
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#define texDef(texname, texmem, texsource, texsize) \ |
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unsigned int *texmem; \ |
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cudaMalloc(&texmem, texsize); \ |
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cudaMemcpy(texmem, texsource, texsize, cudaMemcpyHostToDevice); \ |
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texname.normalized = 0; \ |
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texname.filterMode = cudaFilterModePoint; \ |
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texname.addressMode[0] = cudaAddressModeClamp; \ |
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{ cudaChannelFormatDesc channelDesc = cudaCreateChannelDesc<unsigned int>(); \ |
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cudaBindTexture(NULL, &texname, texmem, &channelDesc, texsize ); } \ |
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// Setup-Funktionen |
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__host__ void quark_groestl512_cpu_init(int thr_id, int threads) |
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{ |
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cudaGetDeviceProperties(&props[thr_id], device_map[thr_id]); |
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// Texturen mit obigem Makro initialisieren |
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texDef(t0up1, d_T0up, T0up_cpu, sizeof(uint32_t)*256); |
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texDef(t0dn1, d_T0dn, T0dn_cpu, sizeof(uint32_t)*256); |
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texDef(t1up1, d_T1up, T1up_cpu, sizeof(uint32_t)*256); |
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texDef(t1dn1, d_T1dn, T1dn_cpu, sizeof(uint32_t)*256); |
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texDef(t2up1, d_T2up, T2up_cpu, sizeof(uint32_t)*256); |
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texDef(t2dn1, d_T2dn, T2dn_cpu, sizeof(uint32_t)*256); |
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texDef(t3up1, d_T3up, T3up_cpu, sizeof(uint32_t)*256); |
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texDef(t3dn1, d_T3dn, T3dn_cpu, sizeof(uint32_t)*256); |
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} |
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__host__ void quark_groestl512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order) |
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{ |
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// Compute 3.5 und 5.x Geräte am besten mit 768 Threads ansteuern, |
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// alle anderen mit 512 Threads. |
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int threadsperblock = ((props[thr_id].major == 3 && props[thr_id].minor == 5) || props[thr_id].major > 3) ? 768 : 512; |
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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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#if USE_SHARED |
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size_t shared_size = 8 * 256 * sizeof(uint32_t); |
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#else |
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size_t shared_size = 0; |
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#endif |
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// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size); |
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//fprintf(stderr, "ThrID: %d\n", thr_id); |
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quark_groestl512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, d_hash, d_nonceVector); |
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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_doublegroestl512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order) |
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{ |
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// Compute 3.5 und 5.x Geräte am besten mit 768 Threads ansteuern, |
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// alle anderen mit 512 Threads. |
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int threadsperblock = ((props[thr_id].major == 3 && props[thr_id].minor == 5) || props[thr_id].major > 3) ? 768 : 512; |
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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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#if USE_SHARED |
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size_t shared_size = 8 * 256 * sizeof(uint32_t); |
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#else |
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size_t shared_size = 0; |
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#endif |
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// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size); |
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//fprintf(stderr, "ThrID: %d\n", thr_id); |
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quark_groestl512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, d_hash, d_nonceVector); |
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quark_groestl512_gpu_hash_64<<<grid, block, shared_size>>>(threads, startNounce, d_hash, d_nonceVector); |
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|
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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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