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820 lines
23 KiB
820 lines
23 KiB
8 years ago
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#include <memory.h>
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#ifdef __INTELLISENSE__
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/* just for vstudio code colors */
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//#define __CUDA_ARCH__ 500
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#define __threadfence_block()
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#define __ldg(x) *(x)
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#define atomicMin(p,y) y
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#endif
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#include "cuda_helper.h"
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#define TPB50 32
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__constant__ uint32_t pTarget[8];
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static __device__ __forceinline__
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void Gfunc(uint2 & a, uint2 &b, uint2 &c, uint2 &d)
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{
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#if __CUDA_ARCH__ > 500
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a += b; uint2 tmp = d; d.y = a.x ^ tmp.x; d.x = a.y ^ tmp.y;
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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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#else
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a += b; d ^= a; d = SWAPUINT2(d);
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c += d; b ^= c; b = ROR2(b, 24);
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a += b; d ^= a; d = ROR2(d, 16);
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c += d; b ^= c; b = ROR2(b, 63);
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#endif
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}
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#if __CUDA_ARCH__ == 500 || __CUDA_ARCH__ == 350
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#include "cuda_lyra2_vectors.h"
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#define Nrow 8
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#define Ncol 8
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#define memshift 3
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__device__ uint2 *DMatrix;
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__device__ __forceinline__ uint2 LD4S(const int index)
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{
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extern __shared__ uint2 shared_mem[];
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return shared_mem[(index * blockDim.y + threadIdx.y) * blockDim.x + threadIdx.x];
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}
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__device__ __forceinline__ void ST4S(const int index, const uint2 data)
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{
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extern __shared__ uint2 shared_mem[];
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shared_mem[(index * blockDim.y + threadIdx.y) * blockDim.x + threadIdx.x] = data;
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}
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#if __CUDA_ARCH__ == 300
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__device__ __forceinline__ uint32_t WarpShuffle(uint32_t a, uint32_t b, uint32_t c)
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{
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return __shfl(a, b, c);
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}
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__device__ __forceinline__ uint2 WarpShuffle(uint2 a, uint32_t b, uint32_t c)
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{
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return make_uint2(__shfl(a.x, b, c), __shfl(a.y, b, c));
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}
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__device__ __forceinline__ void WarpShuffle3(uint2 &a1, uint2 &a2, uint2 &a3, uint32_t b1, uint32_t b2, uint32_t b3, uint32_t c)
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{
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a1 = WarpShuffle(a1, b1, c);
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a2 = WarpShuffle(a2, b2, c);
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a3 = WarpShuffle(a3, b3, c);
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}
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#else // != 300
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__device__ __forceinline__ uint32_t WarpShuffle(uint32_t a, uint32_t b, uint32_t c)
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{
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extern __shared__ uint2 shared_mem[];
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const uint32_t thread = blockDim.x * threadIdx.y + threadIdx.x;
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uint32_t *_ptr = (uint32_t*)shared_mem;
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__threadfence_block();
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uint32_t buf = _ptr[thread];
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_ptr[thread] = a;
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__threadfence_block();
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uint32_t result = _ptr[(thread&~(c - 1)) + (b&(c - 1))];
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__threadfence_block();
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_ptr[thread] = buf;
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__threadfence_block();
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return result;
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}
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__device__ __forceinline__ uint2 WarpShuffle(uint2 a, uint32_t b, uint32_t c)
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{
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extern __shared__ uint2 shared_mem[];
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const uint32_t thread = blockDim.x * threadIdx.y + threadIdx.x;
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__threadfence_block();
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uint2 buf = shared_mem[thread];
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shared_mem[thread] = a;
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__threadfence_block();
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uint2 result = shared_mem[(thread&~(c - 1)) + (b&(c - 1))];
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__threadfence_block();
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shared_mem[thread] = buf;
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__threadfence_block();
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return result;
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}
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__device__ __forceinline__ void WarpShuffle3(uint2 &a1, uint2 &a2, uint2 &a3, uint32_t b1, uint32_t b2, uint32_t b3, uint32_t c)
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{
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extern __shared__ uint2 shared_mem[];
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const uint32_t thread = blockDim.x * threadIdx.y + threadIdx.x;
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__threadfence_block();
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uint2 buf = shared_mem[thread];
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shared_mem[thread] = a1;
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__threadfence_block();
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a1 = shared_mem[(thread&~(c - 1)) + (b1&(c - 1))];
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__threadfence_block();
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shared_mem[thread] = a2;
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__threadfence_block();
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a2 = shared_mem[(thread&~(c - 1)) + (b2&(c - 1))];
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__threadfence_block();
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shared_mem[thread] = a3;
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__threadfence_block();
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a3 = shared_mem[(thread&~(c - 1)) + (b3&(c - 1))];
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__threadfence_block();
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shared_mem[thread] = buf;
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__threadfence_block();
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}
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#endif // != 300
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__device__ __forceinline__ void round_lyra(uint2 s[4])
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{
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Gfunc(s[0], s[1], s[2], s[3]);
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WarpShuffle3(s[1], s[2], s[3], threadIdx.x + 1, threadIdx.x + 2, threadIdx.x + 3, 4);
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Gfunc(s[0], s[1], s[2], s[3]);
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WarpShuffle3(s[1], s[2], s[3], threadIdx.x + 3, threadIdx.x + 2, threadIdx.x + 1, 4);
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}
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static __device__ __forceinline__
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void round_lyra(uint2x4* s)
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{
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Gfunc(s[0].x, s[1].x, s[2].x, s[3].x);
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Gfunc(s[0].y, s[1].y, s[2].y, s[3].y);
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Gfunc(s[0].z, s[1].z, s[2].z, s[3].z);
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Gfunc(s[0].w, s[1].w, s[2].w, s[3].w);
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Gfunc(s[0].x, s[1].y, s[2].z, s[3].w);
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Gfunc(s[0].y, s[1].z, s[2].w, s[3].x);
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Gfunc(s[0].z, s[1].w, s[2].x, s[3].y);
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Gfunc(s[0].w, s[1].x, s[2].y, s[3].z);
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}
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static __device__ __forceinline__
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void reduceDuplexV5(uint2 state[4], const uint32_t thread, const uint32_t threads)
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{
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uint2 state1[3], state2[3];
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const uint32_t ps0 = (memshift * Ncol * 0 * threads + thread)*blockDim.x + threadIdx.x;
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const uint32_t ps1 = (memshift * Ncol * 1 * threads + thread)*blockDim.x + threadIdx.x;
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const uint32_t ps2 = (memshift * Ncol * 2 * threads + thread)*blockDim.x + threadIdx.x;
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const uint32_t ps3 = (memshift * Ncol * 3 * threads + thread)*blockDim.x + threadIdx.x;
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const uint32_t ps4 = (memshift * Ncol * 4 * threads + thread)*blockDim.x + threadIdx.x;
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const uint32_t ps5 = (memshift * Ncol * 5 * threads + thread)*blockDim.x + threadIdx.x;
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const uint32_t ps6 = (memshift * Ncol * 6 * threads + thread)*blockDim.x + threadIdx.x;
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const uint32_t ps7 = (memshift * Ncol * 7 * threads + thread)*blockDim.x + threadIdx.x;
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for (int i = 0; i < 8; i++)
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{
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const uint32_t s0 = memshift * Ncol * 0 + (Ncol - 1 - i) * memshift;
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#pragma unroll
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for (int j = 0; j < 3; j++)
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ST4S(s0 + j, state[j]);
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round_lyra(state);
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}
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for (int i = 0; i < 8; i++)
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{
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const uint32_t s0 = memshift * Ncol * 0 + i * memshift;
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const uint32_t s1 = ps1 + (7 - i)*memshift* threads*blockDim.x;
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state1[j] = LD4S(s0 + j);
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#pragma unroll
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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(state);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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*(DMatrix + s1 + j*threads*blockDim.x) = state1[j] ^ state[j];
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}
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// 1, 0, 2
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for (int i = 0; i < 8; i++)
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{
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const uint32_t s0 = memshift * Ncol * 0 + i * memshift;
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const uint32_t s1 = ps1 + i * memshift* threads*blockDim.x;
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const uint32_t s2 = ps2 + (7 - i)*memshift* threads*blockDim.x;
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state1[j] = *(DMatrix + s1 + j*threads*blockDim.x);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state2[j] = LD4S(s0 + j);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state[j] ^= state1[j] + state2[j];
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round_lyra(state);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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*(DMatrix + s2 + j*threads*blockDim.x) = state1[j] ^ state[j];
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//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
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uint2 Data0 = state[0];
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uint2 Data1 = state[1];
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uint2 Data2 = state[2];
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WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
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if (threadIdx.x == 0)
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{
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state2[0] ^= Data2;
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state2[1] ^= Data0;
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state2[2] ^= Data1;
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}
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else
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{
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state2[0] ^= Data0;
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state2[1] ^= Data1;
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state2[2] ^= Data2;
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}
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#pragma unroll
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for (int j = 0; j < 3; j++)
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ST4S(s0 + j, state2[j]);
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}
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// 2, 1, 3
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for (int i = 0; i < 8; i++)
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{
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const uint32_t s1 = ps1 + i * memshift* threads*blockDim.x;
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const uint32_t s2 = ps2 + i * memshift* threads*blockDim.x;
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const uint32_t s3 = ps3 + (7 - i)*memshift* threads*blockDim.x;
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state1[j] = *(DMatrix + s2 + j*threads*blockDim.x);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state2[j] = *(DMatrix + s1 + j*threads*blockDim.x);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state[j] ^= state1[j] + state2[j];
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round_lyra(state);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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*(DMatrix + s3 + j*threads*blockDim.x) = state1[j] ^ state[j];
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//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
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uint2 Data0 = state[0];
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uint2 Data1 = state[1];
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uint2 Data2 = state[2];
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WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
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if (threadIdx.x == 0)
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{
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state2[0] ^= Data2;
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state2[1] ^= Data0;
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state2[2] ^= Data1;
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} else {
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state2[0] ^= Data0;
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state2[1] ^= Data1;
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state2[2] ^= Data2;
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}
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#pragma unroll
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for (int j = 0; j < 3; j++)
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*(DMatrix + s1 + j*threads*blockDim.x) = state2[j];
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}
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// 3, 0, 4
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for (int i = 0; i < 8; i++)
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{
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const uint32_t ls0 = memshift * Ncol * 0 + i * memshift;
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const uint32_t s0 = ps0 + i * memshift* threads*blockDim.x;
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const uint32_t s3 = ps3 + i * memshift* threads*blockDim.x;
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const uint32_t s4 = ps4 + (7 - i)*memshift* threads*blockDim.x;
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state1[j] = *(DMatrix + s3 + j*threads*blockDim.x);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state2[j] = LD4S(ls0 + j);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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state[j] ^= state1[j] + state2[j];
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round_lyra(state);
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#pragma unroll
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for (int j = 0; j < 3; j++)
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*(DMatrix + s4 + j*threads*blockDim.x) = state1[j] ^ state[j];
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//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
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uint2 Data0 = state[0];
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uint2 Data1 = state[1];
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uint2 Data2 = state[2];
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WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
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if (threadIdx.x == 0)
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{
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state2[0] ^= Data2;
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state2[1] ^= Data0;
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state2[2] ^= Data1;
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} else {
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state2[0] ^= Data0;
|
||
|
|
state2[1] ^= Data1;
|
||
|
|
state2[2] ^= Data2;
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
*(DMatrix + s0 + j*threads*blockDim.x) = state2[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
// 4, 3, 5
|
||
|
|
for (int i = 0; i < 8; i++)
|
||
|
|
{
|
||
|
|
const uint32_t s3 = ps3 + i * memshift* threads*blockDim.x;
|
||
|
|
const uint32_t s4 = ps4 + i * memshift* threads*blockDim.x;
|
||
|
|
const uint32_t s5 = ps5 + (7 - i)*memshift* threads*blockDim.x;
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state1[j] = *(DMatrix + s4 + j*threads*blockDim.x);
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state2[j] = *(DMatrix + s3 + j*threads*blockDim.x);
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state[j] ^= state1[j] + state2[j];
|
||
|
|
|
||
|
|
round_lyra(state);
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
*(DMatrix + s5 + j*threads*blockDim.x) = state1[j] ^ state[j];
|
||
|
|
|
||
|
|
//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
|
||
|
|
uint2 Data0 = state[0];
|
||
|
|
uint2 Data1 = state[1];
|
||
|
|
uint2 Data2 = state[2];
|
||
|
|
WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
|
||
|
|
|
||
|
|
if (threadIdx.x == 0)
|
||
|
|
{
|
||
|
|
state2[0] ^= Data2;
|
||
|
|
state2[1] ^= Data0;
|
||
|
|
state2[2] ^= Data1;
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
state2[0] ^= Data0;
|
||
|
|
state2[1] ^= Data1;
|
||
|
|
state2[2] ^= Data2;
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
*(DMatrix + s3 + j*threads*blockDim.x) = state2[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
// 5, 2, 6
|
||
|
|
for (int i = 0; i < 8; i++)
|
||
|
|
{
|
||
|
|
const uint32_t s2 = ps2 + i * memshift* threads*blockDim.x;
|
||
|
|
const uint32_t s5 = ps5 + i * memshift* threads*blockDim.x;
|
||
|
|
const uint32_t s6 = ps6 + (7 - i)*memshift* threads*blockDim.x;
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state1[j] = *(DMatrix + s5 + j*threads*blockDim.x);
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state2[j] = *(DMatrix + s2 + j*threads*blockDim.x);
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state[j] ^= state1[j] + state2[j];
|
||
|
|
|
||
|
|
round_lyra(state);
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
*(DMatrix + s6 + j*threads*blockDim.x) = state1[j] ^ state[j];
|
||
|
|
|
||
|
|
//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
|
||
|
|
uint2 Data0 = state[0];
|
||
|
|
uint2 Data1 = state[1];
|
||
|
|
uint2 Data2 = state[2];
|
||
|
|
WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
|
||
|
|
|
||
|
|
if (threadIdx.x == 0)
|
||
|
|
{
|
||
|
|
state2[0] ^= Data2;
|
||
|
|
state2[1] ^= Data0;
|
||
|
|
state2[2] ^= Data1;
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
state2[0] ^= Data0;
|
||
|
|
state2[1] ^= Data1;
|
||
|
|
state2[2] ^= Data2;
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
*(DMatrix + s2 + j*threads*blockDim.x) = state2[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
// 6, 1, 7
|
||
|
|
for (int i = 0; i < 8; i++)
|
||
|
|
{
|
||
|
|
const uint32_t s1 = ps1 + i * memshift* threads*blockDim.x;
|
||
|
|
const uint32_t s6 = ps6 + i * memshift* threads*blockDim.x;
|
||
|
|
const uint32_t s7 = ps7 + (7 - i)*memshift* threads*blockDim.x;
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state1[j] = *(DMatrix + s6 + j*threads*blockDim.x);
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state2[j] = *(DMatrix + s1 + j*threads*blockDim.x);
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state[j] ^= state1[j] + state2[j];
|
||
|
|
|
||
|
|
round_lyra(state);
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
*(DMatrix + s7 + j*threads*blockDim.x) = state1[j] ^ state[j];
|
||
|
|
|
||
|
|
//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
|
||
|
|
uint2 Data0 = state[0];
|
||
|
|
uint2 Data1 = state[1];
|
||
|
|
uint2 Data2 = state[2];
|
||
|
|
WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
|
||
|
|
|
||
|
|
if (threadIdx.x == 0)
|
||
|
|
{
|
||
|
|
state2[0] ^= Data2;
|
||
|
|
state2[1] ^= Data0;
|
||
|
|
state2[2] ^= Data1;
|
||
|
|
} else {
|
||
|
|
state2[0] ^= Data0;
|
||
|
|
state2[1] ^= Data1;
|
||
|
|
state2[2] ^= Data2;
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
*(DMatrix + s1 + j*threads*blockDim.x) = state2[j];
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
static __device__ __forceinline__
|
||
|
|
void reduceDuplexRowV50(const int rowIn, const int rowInOut, const int rowOut, uint2 state[4], const uint32_t thread, const uint32_t threads)
|
||
|
|
{
|
||
|
|
const uint32_t ps1 = (memshift * Ncol * rowIn*threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
const uint32_t ps2 = (memshift * Ncol * rowInOut *threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
const uint32_t ps3 = (memshift * Ncol * rowOut*threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
|
||
|
|
#pragma unroll 1
|
||
|
|
for (int i = 0; i < 8; i++)
|
||
|
|
{
|
||
|
|
uint2 state1[3], state2[3];
|
||
|
|
|
||
|
|
const uint32_t s1 = ps1 + i*memshift*threads *blockDim.x;
|
||
|
|
const uint32_t s2 = ps2 + i*memshift*threads *blockDim.x;
|
||
|
|
const uint32_t s3 = ps3 + i*memshift*threads *blockDim.x;
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++) {
|
||
|
|
state1[j] = *(DMatrix + s1 + j*threads*blockDim.x);
|
||
|
|
state2[j] = *(DMatrix + s2 + j*threads*blockDim.x);
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++) {
|
||
|
|
state1[j] += state2[j];
|
||
|
|
state[j] ^= state1[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
round_lyra(state);
|
||
|
|
|
||
|
|
//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
|
||
|
|
uint2 Data0 = state[0];
|
||
|
|
uint2 Data1 = state[1];
|
||
|
|
uint2 Data2 = state[2];
|
||
|
|
WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
|
||
|
|
|
||
|
|
if (threadIdx.x == 0)
|
||
|
|
{
|
||
|
|
state2[0] ^= Data2;
|
||
|
|
state2[1] ^= Data0;
|
||
|
|
state2[2] ^= Data1;
|
||
|
|
} else {
|
||
|
|
state2[0] ^= Data0;
|
||
|
|
state2[1] ^= Data1;
|
||
|
|
state2[2] ^= Data2;
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
{
|
||
|
|
*(DMatrix + s2 + j*threads*blockDim.x) = state2[j];
|
||
|
|
*(DMatrix + s3 + j*threads*blockDim.x) ^= state[j];
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
static __device__ __forceinline__
|
||
|
|
void reduceDuplexRowV50_8(const int rowInOut, uint2 state[4], const uint32_t thread, const uint32_t threads)
|
||
|
|
{
|
||
|
|
const uint32_t ps1 = (memshift * Ncol * 2*threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
const uint32_t ps2 = (memshift * Ncol * rowInOut *threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
// const uint32_t ps3 = (memshift * Ncol * 5*threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
|
||
|
|
uint2 state1[3], last[3];
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++) {
|
||
|
|
state1[j] = *(DMatrix + ps1 + j*threads*blockDim.x);
|
||
|
|
last[j] = *(DMatrix + ps2 + j*threads*blockDim.x);
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++) {
|
||
|
|
state1[j] += last[j];
|
||
|
|
state[j] ^= state1[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
round_lyra(state);
|
||
|
|
|
||
|
|
//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
|
||
|
|
uint2 Data0 = state[0];
|
||
|
|
uint2 Data1 = state[1];
|
||
|
|
uint2 Data2 = state[2];
|
||
|
|
WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
|
||
|
|
|
||
|
|
if (threadIdx.x == 0)
|
||
|
|
{
|
||
|
|
last[0] ^= Data2;
|
||
|
|
last[1] ^= Data0;
|
||
|
|
last[2] ^= Data1;
|
||
|
|
} else {
|
||
|
|
last[0] ^= Data0;
|
||
|
|
last[1] ^= Data1;
|
||
|
|
last[2] ^= Data2;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (rowInOut == 5)
|
||
|
|
{
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
last[j] ^= state[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
for (int i = 1; i < 8; i++)
|
||
|
|
{
|
||
|
|
const uint32_t s1 = ps1 + i*memshift*threads *blockDim.x;
|
||
|
|
const uint32_t s2 = ps2 + i*memshift*threads *blockDim.x;
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state[j] ^= *(DMatrix + s1 + j*threads*blockDim.x) + *(DMatrix + s2 + j*threads*blockDim.x);
|
||
|
|
|
||
|
|
round_lyra(state);
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state[j] ^= last[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
static __device__ __forceinline__
|
||
|
|
void reduceDuplexRowV50_8_v2(const int rowIn, const int rowOut,const int rowInOut, uint2 state[4], const uint32_t thread, const uint32_t threads)
|
||
|
|
{
|
||
|
|
const uint32_t ps1 = (memshift * Ncol * rowIn * threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
const uint32_t ps2 = (memshift * Ncol * rowInOut *threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
// const uint32_t ps3 = (memshift * Ncol * 5*threads + thread)*blockDim.x + threadIdx.x;
|
||
|
|
|
||
|
|
uint2 state1[3], last[3];
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++) {
|
||
|
|
state1[j] = *(DMatrix + ps1 + j*threads*blockDim.x);
|
||
|
|
last[j] = *(DMatrix + ps2 + j*threads*blockDim.x);
|
||
|
|
}
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++) {
|
||
|
|
state1[j] += last[j];
|
||
|
|
state[j] ^= state1[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
round_lyra(state);
|
||
|
|
|
||
|
|
//一個手前のスレッドからデータを貰う(同時に一個先のスレッドにデータを送る)
|
||
|
|
uint2 Data0 = state[0];
|
||
|
|
uint2 Data1 = state[1];
|
||
|
|
uint2 Data2 = state[2];
|
||
|
|
WarpShuffle3(Data0, Data1, Data2, threadIdx.x - 1, threadIdx.x - 1, threadIdx.x - 1, 4);
|
||
|
|
|
||
|
|
if (threadIdx.x == 0)
|
||
|
|
{
|
||
|
|
last[0] ^= Data2;
|
||
|
|
last[1] ^= Data0;
|
||
|
|
last[2] ^= Data1;
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
last[0] ^= Data0;
|
||
|
|
last[1] ^= Data1;
|
||
|
|
last[2] ^= Data2;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (rowInOut == rowOut)
|
||
|
|
{
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
last[j] ^= state[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
for (int i = 1; i < 8; i++)
|
||
|
|
{
|
||
|
|
const uint32_t s1 = ps1 + i*memshift*threads *blockDim.x;
|
||
|
|
const uint32_t s2 = ps2 + i*memshift*threads *blockDim.x;
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state[j] ^= *(DMatrix + s1 + j*threads*blockDim.x) + *(DMatrix + s2 + j*threads*blockDim.x);
|
||
|
|
|
||
|
|
round_lyra(state);
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
#pragma unroll
|
||
|
|
for (int j = 0; j < 3; j++)
|
||
|
|
state[j] ^= last[j];
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
__global__ __launch_bounds__(64, 1)
|
||
|
|
void lyra2Z_gpu_hash_32_1_sm5(uint32_t threads, uint32_t startNounce, uint2 *g_hash)
|
||
|
|
{
|
||
|
|
const uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x);
|
||
|
|
|
||
|
|
const uint2x4 blake2b_IV[2] = {
|
||
|
|
{ { 0xf3bcc908, 0x6a09e667 }, { 0x84caa73b, 0xbb67ae85 }, { 0xfe94f82b, 0x3c6ef372 }, { 0x5f1d36f1, 0xa54ff53a } },
|
||
|
|
{ { 0xade682d1, 0x510e527f }, { 0x2b3e6c1f, 0x9b05688c }, { 0xfb41bd6b, 0x1f83d9ab }, { 0x137e2179, 0x5be0cd19 } }
|
||
|
|
};
|
||
|
|
const uint2x4 Mask[2] = {
|
||
|
|
0x00000020UL, 0x00000000UL, 0x00000020UL, 0x00000000UL,
|
||
|
|
0x00000020UL, 0x00000000UL, 0x00000008UL, 0x00000000UL,
|
||
|
|
0x00000008UL, 0x00000000UL, 0x00000008UL, 0x00000000UL,
|
||
|
|
0x00000080UL, 0x00000000UL, 0x00000000UL, 0x01000000UL
|
||
|
|
};
|
||
|
|
if (thread < threads)
|
||
|
|
{
|
||
|
|
uint2x4 state[4];
|
||
|
|
|
||
|
|
((uint2*)state)[0] = __ldg(&g_hash[thread]);
|
||
|
|
((uint2*)state)[1] = __ldg(&g_hash[thread + threads]);
|
||
|
|
((uint2*)state)[2] = __ldg(&g_hash[thread + threads * 2]);
|
||
|
|
((uint2*)state)[3] = __ldg(&g_hash[thread + threads * 3]);
|
||
|
|
|
||
|
|
state[1] = state[0];
|
||
|
|
state[2] = blake2b_IV[0];
|
||
|
|
state[3] = blake2b_IV[1];
|
||
|
|
|
||
|
|
for (int i = 0; i < 12; i++)
|
||
|
|
round_lyra(state); //because 12 is not enough
|
||
|
|
|
||
|
|
state[0] ^= Mask[0];
|
||
|
|
state[1] ^= Mask[1];
|
||
|
|
|
||
|
|
for (int i = 0; i < 12; i++)
|
||
|
|
round_lyra(state); //because 12 is not enough
|
||
|
|
|
||
|
|
|
||
|
|
((uint2x4*)DMatrix)[0 * threads + thread] = state[0];
|
||
|
|
((uint2x4*)DMatrix)[1 * threads + thread] = state[1];
|
||
|
|
((uint2x4*)DMatrix)[2 * threads + thread] = state[2];
|
||
|
|
((uint2x4*)DMatrix)[3 * threads + thread] = state[3];
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
__global__ __launch_bounds__(TPB50, 1)
|
||
|
|
void lyra2Z_gpu_hash_32_2_sm5(uint32_t threads, uint32_t startNounce, uint2 *g_hash)
|
||
|
|
{
|
||
|
|
const uint32_t thread = (blockDim.y * blockIdx.x + threadIdx.y);
|
||
|
|
|
||
|
|
if (thread < threads)
|
||
|
|
{
|
||
|
|
uint2 state[4];
|
||
|
|
|
||
|
|
state[0] = __ldg(&DMatrix[(0 * threads + thread)*blockDim.x + threadIdx.x]);
|
||
|
|
state[1] = __ldg(&DMatrix[(1 * threads + thread)*blockDim.x + threadIdx.x]);
|
||
|
|
state[2] = __ldg(&DMatrix[(2 * threads + thread)*blockDim.x + threadIdx.x]);
|
||
|
|
state[3] = __ldg(&DMatrix[(3 * threads + thread)*blockDim.x + threadIdx.x]);
|
||
|
|
|
||
|
|
reduceDuplexV5(state, thread, threads);
|
||
|
|
|
||
|
|
uint32_t rowa; // = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
uint32_t prev = 7;
|
||
|
|
uint32_t iterator = 0;
|
||
|
|
for (uint32_t i = 0; i<8; i++) {
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50(prev, rowa, iterator, state, thread, threads);
|
||
|
|
prev = iterator;
|
||
|
|
iterator = (iterator + 3) & 7;
|
||
|
|
}
|
||
|
|
for (uint32_t i = 0; i<8; i++) {
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50(prev, rowa, iterator, state, thread, threads);
|
||
|
|
prev = iterator;
|
||
|
|
iterator = (iterator - 1) & 7;
|
||
|
|
}
|
||
|
|
for (uint32_t i = 0; i<8; i++) {
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50(prev, rowa, iterator, state, thread, threads);
|
||
|
|
prev = iterator;
|
||
|
|
iterator = (iterator + 3) & 7;
|
||
|
|
}
|
||
|
|
for (uint32_t i = 0; i<8; i++) {
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50(prev, rowa, iterator, state, thread, threads);
|
||
|
|
prev = iterator;
|
||
|
|
iterator = (iterator - 1) & 7;
|
||
|
|
}
|
||
|
|
for (uint32_t i = 0; i<8; i++) {
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50(prev, rowa, iterator, state, thread, threads);
|
||
|
|
prev = iterator;
|
||
|
|
iterator = (iterator + 3) & 7;
|
||
|
|
}
|
||
|
|
for (uint32_t i = 0; i<8; i++) {
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50(prev, rowa, iterator, state, thread, threads);
|
||
|
|
prev = iterator;
|
||
|
|
iterator = (iterator - 1) & 7;
|
||
|
|
}
|
||
|
|
for (uint32_t i = 0; i<8; i++) {
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50(prev, rowa, iterator, state, thread, threads);
|
||
|
|
prev = iterator;
|
||
|
|
iterator = (iterator + 3) & 7;
|
||
|
|
}
|
||
|
|
for (uint32_t i = 0; i<7; i++) {
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50(prev, rowa, iterator, state, thread, threads);
|
||
|
|
prev = iterator;
|
||
|
|
iterator = (iterator - 1) & 7;
|
||
|
|
}
|
||
|
|
|
||
|
|
rowa = WarpShuffle(state[0].x, 0, 4) & 7;
|
||
|
|
reduceDuplexRowV50_8_v2(prev,iterator,rowa, state, thread, threads);
|
||
|
|
|
||
|
|
DMatrix[(0 * threads + thread)*blockDim.x + threadIdx.x] = state[0];
|
||
|
|
DMatrix[(1 * threads + thread)*blockDim.x + threadIdx.x] = state[1];
|
||
|
|
DMatrix[(2 * threads + thread)*blockDim.x + threadIdx.x] = state[2];
|
||
|
|
DMatrix[(3 * threads + thread)*blockDim.x + threadIdx.x] = state[3];
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
__global__ __launch_bounds__(64, 1)
|
||
|
|
void lyra2Z_gpu_hash_32_3_sm5(uint32_t threads, uint32_t startNounce, uint2 *g_hash, uint32_t *resNonces)
|
||
|
|
{
|
||
|
|
const uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x);
|
||
|
|
|
||
|
|
if (thread < threads)
|
||
|
|
{
|
||
|
|
uint2x4 state[4];
|
||
|
|
|
||
|
|
state[0] = __ldg4(&((uint2x4*)DMatrix)[0 * threads + thread]);
|
||
|
|
state[1] = __ldg4(&((uint2x4*)DMatrix)[1 * threads + thread]);
|
||
|
|
state[2] = __ldg4(&((uint2x4*)DMatrix)[2 * threads + thread]);
|
||
|
|
state[3] = __ldg4(&((uint2x4*)DMatrix)[3 * threads + thread]);
|
||
|
|
|
||
|
|
for (int i = 0; i < 12; i++)
|
||
|
|
round_lyra(state);
|
||
|
|
|
||
|
|
uint32_t nonce = startNounce + thread;
|
||
|
|
if (((uint64_t*)state)[3] <= ((uint64_t*)pTarget)[3]) {
|
||
|
|
atomicMin(&resNonces[1], resNonces[0]);
|
||
|
|
atomicMin(&resNonces[0], nonce);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
#else
|
||
|
|
/* if __CUDA_ARCH__ != 500 .. host */
|
||
|
|
__global__ void lyra2Z_gpu_hash_32_1_sm5(uint32_t threads, uint32_t startNounce, uint2 *g_hash) {}
|
||
|
|
__global__ void lyra2Z_gpu_hash_32_2_sm5(uint32_t threads, uint32_t startNounce, uint2 *g_hash) {}
|
||
|
|
__global__ void lyra2Z_gpu_hash_32_3_sm5(uint32_t threads, uint32_t startNounce, uint2 *g_hash, uint32_t *resNonces) {}
|
||
|
|
#endif
|