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543 lines
14 KiB
543 lines
14 KiB
#include <stdio.h> |
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#include <memory.h> |
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#include "cuda_lyra2_vectors.h" |
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#define TPB 8 |
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// |
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#if __CUDA_ARCH__ < 500 |
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#define vectype ulonglong4 |
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#define u64type uint64_t |
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#define memshift 4 |
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#elif __CUDA_ARCH__ == 500 |
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#define u64type uint2 |
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#define vectype uint28 |
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#define memshift 3 |
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#else |
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#define u64type uint2 |
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#define vectype uint28 |
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#define memshift 4 |
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#endif |
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__device__ vectype *DMatrix; |
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#ifdef __CUDA_ARCH__ |
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static __device__ __forceinline__ |
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void Gfunc_v35(uint2 &a, uint2 &b, uint2 &c, uint2 &d) |
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{ |
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a += b; d ^= a; d = SWAPUINT2(d); |
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c += d; b ^= c; b = ROR24(b); |
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a += b; d ^= a; d = ROR16(d); |
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c += d; b ^= c; b = ROR2(b, 63); |
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} |
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#if __CUDA_ARCH__ < 500 |
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static __device__ __forceinline__ |
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void Gfunc_v35(unsigned long long &a, unsigned long long &b, unsigned long long &c, unsigned long long &d) |
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{ |
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a += b; d ^= a; d = ROTR64(d, 32); |
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c += d; b ^= c; b = ROTR64(b, 24); |
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a += b; d ^= a; d = ROTR64(d, 16); |
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c += d; b ^= c; b = ROTR64(b, 63); |
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} |
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#endif |
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static __device__ __forceinline__ |
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void round_lyra_v35(vectype* s) |
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{ |
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Gfunc_v35(s[0].x, s[1].x, s[2].x, s[3].x); |
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Gfunc_v35(s[0].y, s[1].y, s[2].y, s[3].y); |
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Gfunc_v35(s[0].z, s[1].z, s[2].z, s[3].z); |
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Gfunc_v35(s[0].w, s[1].w, s[2].w, s[3].w); |
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Gfunc_v35(s[0].x, s[1].y, s[2].z, s[3].w); |
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Gfunc_v35(s[0].y, s[1].z, s[2].w, s[3].x); |
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Gfunc_v35(s[0].z, s[1].w, s[2].x, s[3].y); |
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Gfunc_v35(s[0].w, s[1].x, s[2].y, s[3].z); |
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} |
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#else |
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#define round_lyra_v35(s) {} |
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#endif |
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static __device__ __forceinline__ |
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void reduceDuplex(vectype state[4], uint32_t thread) |
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{ |
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vectype state1[3]; |
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uint32_t ps1 = (256 * thread); |
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uint32_t ps2 = (memshift * 7 + memshift * 8 + 256 * thread); |
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#pragma unroll 4 |
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for (int i = 0; i < 8; i++) |
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{ |
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uint32_t s1 = ps1 + i*memshift; |
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uint32_t s2 = ps2 - i*memshift; |
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for (int j = 0; j < 3; j++) |
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state1[j] = __ldg4(&(DMatrix+s1)[j]); |
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for (int j = 0; j < 3; j++) |
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state[j] ^= state1[j]; |
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round_lyra_v35(state); |
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for (int j = 0; j < 3; j++) |
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state1[j] ^= state[j]; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s2)[j] = state1[j]; |
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} |
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} |
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static __device__ __forceinline__ |
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void reduceDuplexV3(vectype state[4], uint32_t thread) |
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{ |
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vectype state1[3]; |
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uint32_t ps1 = (256 * thread); |
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// colomn row |
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uint32_t ps2 = (memshift * 7 * 8 + memshift * 1 + 64 * memshift * thread); |
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#pragma unroll 4 |
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for (int i = 0; i < 8; i++) |
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{ |
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uint32_t s1 = ps1 + 8 * i *memshift; |
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uint32_t s2 = ps2 - 8 * i *memshift; |
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for (int j = 0; j < 3; j++) |
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state1[j] = __ldg4(&(DMatrix + s1)[j]); |
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for (int j = 0; j < 3; j++) |
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state[j] ^= state1[j]; |
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round_lyra_v35(state); |
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for (int j = 0; j < 3; j++) |
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state1[j] ^= state[j]; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s2)[j] = state1[j]; |
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} |
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} |
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static __device__ __forceinline__ |
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void reduceDuplexRowSetupV2(const int rowIn, const int rowInOut, const int rowOut, vectype state[4], uint32_t thread) |
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{ |
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vectype state2[3],state1[3]; |
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uint32_t ps1 = ( memshift * 8 * rowIn + 256 * thread); |
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uint32_t ps2 = ( memshift * 8 * rowInOut + 256 * thread); |
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uint32_t ps3 = (memshift*7 + memshift * 8 * rowOut + 256 * thread); |
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#pragma unroll 1 |
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for (int i = 0; i < 8; i++) |
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{ |
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uint32_t s1 = ps1 + i*memshift; |
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uint32_t s2 = ps2 + i*memshift; |
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uint32_t s3 = ps3 - i*memshift; |
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for (int j = 0; j < 3; j++) |
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state1[j]= __ldg4(&(DMatrix + s1)[j]); |
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for (int j = 0; j < 3; j++) |
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state2[j]= __ldg4(&(DMatrix + s2)[j]); |
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for (int j = 0; j < 3; j++) { |
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vectype tmp = state1[j] + state2[j]; |
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state[j] ^= tmp; |
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} |
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round_lyra_v35(state); |
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for (int j = 0; j < 3; j++) { |
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state1[j] ^= state[j]; |
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(DMatrix + s3)[j] = state1[j]; |
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} |
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((uint2*)state2)[0] ^= ((uint2*)state)[11]; |
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for (int j = 0; j < 11; j++) |
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((uint2*)state2)[j+1] ^= ((uint2*)state)[j]; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s2)[j] = state2[j]; |
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} |
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} |
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static __device__ __forceinline__ |
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void reduceDuplexRowSetupV3(const int rowIn, const int rowInOut, const int rowOut, vectype state[4], uint32_t thread) |
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{ |
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vectype state2[3], state1[3]; |
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uint32_t ps1 = ( memshift * rowIn + 64 * memshift * thread); |
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uint32_t ps2 = (memshift * rowInOut + 64 * memshift* thread); |
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uint32_t ps3 = (8 * memshift * 7 + memshift * rowOut + 64 * memshift * thread); |
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/* |
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uint32_t ps1 = (256 * thread); |
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uint32_t ps2 = (256 * thread); |
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uint32_t ps3 = (256 * thread); |
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*/ |
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#pragma nounroll |
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for (int i = 0; i < 8; i++) |
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{ |
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uint32_t s1 = ps1 + 8*i*memshift; |
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uint32_t s2 = ps2 + 8*i*memshift; |
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uint32_t s3 = ps3 - 8*i*memshift; |
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for (int j = 0; j < 3; j++) |
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state1[j] = __ldg4(&(DMatrix + s1 )[j]); |
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for (int j = 0; j < 3; j++) |
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state2[j] = __ldg4(&(DMatrix + s2 )[j]); |
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for (int j = 0; j < 3; j++) { |
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vectype tmp = state1[j] + state2[j]; |
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state[j] ^= tmp; |
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} |
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round_lyra_v35(state); |
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for (int j = 0; j < 3; j++) { |
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state1[j] ^= state[j]; |
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(DMatrix + s3)[j] = state1[j]; |
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} |
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((uint2*)state2)[0] ^= ((uint2*)state)[11]; |
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for (int j = 0; j < 11; j++) |
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((uint2*)state2)[j + 1] ^= ((uint2*)state)[j]; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s2)[j] = state2[j]; |
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} |
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} |
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static __device__ __forceinline__ |
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void reduceDuplexRowtV2(const int rowIn, const int rowInOut, const int rowOut, vectype* state, uint32_t thread) |
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{ |
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vectype state1[3], state2[3]; |
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uint32_t ps1 = (memshift * 8 * rowIn + 256 * thread); |
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uint32_t ps2 = (memshift * 8 * rowInOut + 256 * thread); |
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uint32_t ps3 = (memshift * 8 * rowOut + 256 * thread); |
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#pragma unroll 1 |
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for (int i = 0; i < 8; i++) |
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{ |
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uint32_t s1 = ps1 + i*memshift; |
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uint32_t s2 = ps2 + i*memshift; |
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uint32_t s3 = ps3 + i*memshift; |
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for (int j = 0; j < 3; j++) |
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state1[j] = __ldg4(&(DMatrix + s1)[j]); |
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for (int j = 0; j < 3; j++) |
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state2[j] = __ldg4(&(DMatrix + s2)[j]); |
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for (int j = 0; j < 3; j++) |
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state1[j] += state2[j]; |
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for (int j = 0; j < 3; j++) |
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state[j] ^= state1[j]; |
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round_lyra_v35(state); |
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((uint2*)state2)[0] ^= ((uint2*)state)[11]; |
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for (int j = 0; j < 11; j++) |
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((uint2*)state2)[j + 1] ^= ((uint2*)state)[j]; |
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if (rowInOut != rowOut) { |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s2)[j] = state2[j]; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s3)[j] ^= state[j]; |
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} else { |
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for (int j = 0; j < 3; j++) |
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state2[j] ^= state[j]; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s2)[j]=state2[j]; |
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} |
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} |
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} |
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static __device__ __forceinline__ |
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void reduceDuplexRowtV3(const int rowIn, const int rowInOut, const int rowOut, vectype* state, uint32_t thread) |
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{ |
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vectype state1[3], state2[3]; |
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uint32_t ps1 = (memshift * rowIn + 64 * memshift * thread); |
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uint32_t ps2 = (memshift * rowInOut + 64 * memshift * thread); |
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uint32_t ps3 = (memshift * rowOut + 64 *memshift * thread); |
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#pragma nounroll |
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for (int i = 0; i < 8; i++) |
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{ |
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uint32_t s1 = ps1 + 8 * i*memshift; |
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uint32_t s2 = ps2 + 8 * i*memshift; |
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uint32_t s3 = ps3 + 8 * i*memshift; |
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for (int j = 0; j < 3; j++) |
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state1[j] = __ldg4(&(DMatrix + s1)[j]); |
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for (int j = 0; j < 3; j++) |
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state2[j] = __ldg4(&(DMatrix + s2)[j]); |
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for (int j = 0; j < 3; j++) |
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state1[j] += state2[j]; |
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for (int j = 0; j < 3; j++) |
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state[j] ^= state1[j]; |
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round_lyra_v35(state); |
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((uint2*)state2)[0] ^= ((uint2*)state)[11]; |
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for (int j = 0; j < 11; j++) |
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((uint2*)state2)[j + 1] ^= ((uint2*)state)[j]; |
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if (rowInOut != rowOut) { |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s2)[j] = state2[j]; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s3)[j] ^= state[j]; |
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} |
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else { |
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for (int j = 0; j < 3; j++) |
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state2[j] ^= state[j]; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s2)[j] = state2[j]; |
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} |
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} |
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} |
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#if __CUDA_ARCH__ < 500 |
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__global__ __launch_bounds__(48, 1) |
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#elif __CUDA_ARCH__ == 500 |
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__global__ __launch_bounds__(16, 1) |
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#else |
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__global__ __launch_bounds__(TPB, 1) |
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#endif |
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void lyra2_gpu_hash_32(uint32_t threads, uint32_t startNounce, uint2 *outputHash) |
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{ |
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uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x); |
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vectype state[4]; |
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#if __CUDA_ARCH__ > 350 |
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const uint28 blake2b_IV[2] = { |
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{{ 0xf3bcc908, 0x6a09e667 }, { 0x84caa73b, 0xbb67ae85 }, { 0xfe94f82b, 0x3c6ef372 }, { 0x5f1d36f1, 0xa54ff53a }}, |
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{{ 0xade682d1, 0x510e527f }, { 0x2b3e6c1f, 0x9b05688c }, { 0xfb41bd6b, 0x1f83d9ab }, { 0x137e2179, 0x5be0cd19 }} |
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}; |
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#else |
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const ulonglong4 blake2b_IV[2] = { |
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{ 0x6a09e667f3bcc908, 0xbb67ae8584caa73b, 0x3c6ef372fe94f82b, 0xa54ff53a5f1d36f1 }, |
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{ 0x510e527fade682d1, 0x9b05688c2b3e6c1f, 0x1f83d9abfb41bd6b, 0x5be0cd19137e2179 } |
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}; |
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#endif |
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#if __CUDA_ARCH__ == 350 |
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if (thread < threads) |
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#endif |
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{ |
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((uint2*)state)[0] = __ldg(&outputHash[thread]); |
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((uint2*)state)[1] = __ldg(&outputHash[thread + threads]); |
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((uint2*)state)[2] = __ldg(&outputHash[thread + 2 * threads]); |
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((uint2*)state)[3] = __ldg(&outputHash[thread + 3 * threads]); |
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// state[0] = __ldg4(&((vectype*)outputHash)[thread]); |
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state[1] = state[0]; |
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state[2] = ((vectype*)blake2b_IV)[0]; |
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state[3] = ((vectype*)blake2b_IV)[1]; |
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for (int i = 0; i<24; i++) { //because 12 is not enough |
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round_lyra_v35(state); |
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} |
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uint32_t ps1 = (memshift * 7 + 256 * thread); |
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for (int i = 0; i < 8; i++) |
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{ |
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uint32_t s1 = ps1 - memshift * i; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s1)[j] = (state)[j]; |
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round_lyra_v35(state); |
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} |
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reduceDuplex(state, thread); |
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reduceDuplexRowSetupV2(1, 0, 2, state, thread); |
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reduceDuplexRowSetupV2(2, 1, 3, state, thread); |
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reduceDuplexRowSetupV2(3, 0, 4, state, thread); |
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reduceDuplexRowSetupV2(4, 3, 5, state, thread); |
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reduceDuplexRowSetupV2(5, 2, 6, state, thread); |
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reduceDuplexRowSetupV2(6, 1, 7, state, thread); |
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uint32_t rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV2(7, rowa, 0, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV2(0, rowa, 3, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV2(3, rowa, 6, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV2(6, rowa, 1, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV2(1, rowa, 4, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV2(4, rowa, 7, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV2(7, rowa, 2, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV2(2, rowa, 5, state, thread); |
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uint32_t shift = (memshift * 8 * rowa + 256 * thread); |
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for (int j = 0; j < 3; j++) |
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state[j] ^= __ldg4(&(DMatrix + shift)[j]); |
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for (int i = 0; i < 12; i++) |
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round_lyra_v35(state); |
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outputHash[thread]= ((uint2*)state)[0]; |
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outputHash[thread + threads] = ((uint2*)state)[1]; |
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outputHash[thread + 2 * threads] = ((uint2*)state)[2]; |
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outputHash[thread + 3 * threads] = ((uint2*)state)[3]; |
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// ((vectype*)outputHash)[thread] = state[0]; |
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} //thread |
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} |
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#if __CUDA_ARCH__ < 500 |
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__global__ __launch_bounds__(48, 1) |
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#elif __CUDA_ARCH__ == 500 |
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__global__ __launch_bounds__(16, 1) |
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#else |
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__global__ __launch_bounds__(TPB, 1) |
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#endif |
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void lyra2_gpu_hash_32_v3(uint32_t threads, uint32_t startNounce, uint2 *outputHash) |
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{ |
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uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x); |
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vectype state[4]; |
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#if __CUDA_ARCH__ > 350 |
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const uint28 blake2b_IV[2] = { |
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{ { 0xf3bcc908, 0x6a09e667 }, { 0x84caa73b, 0xbb67ae85 }, { 0xfe94f82b, 0x3c6ef372 }, { 0x5f1d36f1, 0xa54ff53a } }, |
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{ { 0xade682d1, 0x510e527f }, { 0x2b3e6c1f, 0x9b05688c }, { 0xfb41bd6b, 0x1f83d9ab }, { 0x137e2179, 0x5be0cd19 } } |
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}; |
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#else |
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const ulonglong4 blake2b_IV[2] = { |
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{ 0x6a09e667f3bcc908, 0xbb67ae8584caa73b, 0x3c6ef372fe94f82b, 0xa54ff53a5f1d36f1 }, |
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{ 0x510e527fade682d1, 0x9b05688c2b3e6c1f, 0x1f83d9abfb41bd6b, 0x5be0cd19137e2179 } |
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}; |
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#endif |
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#if __CUDA_ARCH__ == 350 |
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if (thread < threads) |
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#endif |
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{ |
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((uint2*)state)[0] = __ldg(&outputHash[thread]); |
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((uint2*)state)[1] = __ldg(&outputHash[thread + threads]); |
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((uint2*)state)[2] = __ldg(&outputHash[thread + 2 * threads]); |
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((uint2*)state)[3] = __ldg(&outputHash[thread + 3 * threads]); |
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state[1] = state[0]; |
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state[2] = ((vectype*)blake2b_IV)[0]; |
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state[3] = ((vectype*)blake2b_IV)[1]; |
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for (int i = 0; i<24; i++) |
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round_lyra_v35(state); //because 12 is not enough |
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uint32_t ps1 = (8 * memshift * 7 + 64 * memshift * thread); |
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for (int i = 0; i < 8; i++) |
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{ |
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uint32_t s1 = ps1 - 8 * memshift * i; |
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for (int j = 0; j < 3; j++) |
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(DMatrix + s1)[j] = (state)[j]; |
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round_lyra_v35(state); |
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} |
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reduceDuplexV3(state, thread); |
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reduceDuplexRowSetupV3(1, 0, 2, state, thread); |
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reduceDuplexRowSetupV3(2, 1, 3, state, thread); |
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reduceDuplexRowSetupV3(3, 0, 4, state, thread); |
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reduceDuplexRowSetupV3(4, 3, 5, state, thread); |
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reduceDuplexRowSetupV3(5, 2, 6, state, thread); |
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reduceDuplexRowSetupV3(6, 1, 7, state, thread); |
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uint32_t rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV3(7, rowa, 0, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV3(0, rowa, 3, state, thread); |
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rowa = ((uint2*)state)[0].x & 7; |
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reduceDuplexRowtV3(3, rowa, 6, state, thread); |
|
rowa = ((uint2*)state)[0].x & 7; |
|
reduceDuplexRowtV3(6, rowa, 1, state, thread); |
|
rowa = ((uint2*)state)[0].x & 7; |
|
reduceDuplexRowtV3(1, rowa, 4, state, thread); |
|
rowa = ((uint2*)state)[0].x & 7; |
|
reduceDuplexRowtV3(4, rowa, 7, state, thread); |
|
rowa = ((uint2*)state)[0].x & 7; |
|
reduceDuplexRowtV3(7, rowa, 2, state, thread); |
|
rowa = ((uint2*)state)[0].x & 7; |
|
reduceDuplexRowtV3(2, rowa, 5, state, thread); |
|
|
|
uint32_t shift = (memshift * rowa + 64 * memshift * thread); |
|
|
|
for (int j = 0; j < 3; j++) |
|
state[j] ^= __ldg4(&(DMatrix + shift)[j]); |
|
|
|
for (int i = 0; i < 12; i++) |
|
round_lyra_v35(state); |
|
|
|
|
|
outputHash[thread] = ((uint2*)state)[0]; |
|
outputHash[thread + threads] = ((uint2*)state)[1]; |
|
outputHash[thread + 2 * threads] = ((uint2*)state)[2]; |
|
outputHash[thread + 3 * threads] = ((uint2*)state)[3]; |
|
|
|
} //thread |
|
} |
|
|
|
__host__ |
|
void lyra2_cpu_init(int thr_id, uint32_t threads, uint64_t *hash) |
|
{ |
|
cudaMemcpyToSymbol(DMatrix, &hash, sizeof(hash), 0, cudaMemcpyHostToDevice); |
|
} |
|
|
|
void lyra2_cpu_hash_32(int thr_id, uint32_t threads, uint32_t startNounce, uint64_t *d_outputHash, int order) |
|
{ |
|
uint32_t tpb; |
|
if (device_sm[device_map[thr_id]]<500) |
|
tpb = 48; |
|
else if (device_sm[device_map[thr_id]]==500) |
|
tpb = 16; |
|
else |
|
tpb = TPB; |
|
|
|
dim3 grid((threads + tpb - 1) / tpb); |
|
dim3 block(tpb); |
|
|
|
if (device_sm[device_map[thr_id]] == 500) |
|
lyra2_gpu_hash_32 <<< grid, block >>> (threads, startNounce, (uint2*)d_outputHash); |
|
else |
|
lyra2_gpu_hash_32_v3 <<< grid, block >>> (threads, startNounce, (uint2*)d_outputHash); |
|
|
|
MyStreamSynchronize(NULL, order, thr_id); |
|
}
|
|
|