mirror of https://github.com/GOSTSec/ccminer
Browse Source
Reduce a bit the 750Ti speed but improve a lot the 9xx speed.
Keep compat for SM 3/3.5 in a second file..
Note: With this code and Cuda 7.5, the speed won is the reverse...
May be "reverted" soon
2upstream
Tanguy Pruvot
9 years ago
4 changed files with 397 additions and 291 deletions
@ -0,0 +1,253 @@
@@ -0,0 +1,253 @@
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/* SM 3/3.5 Variant for lyra2REv2 */ |
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#ifdef __INTELLISENSE__ |
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/* just for vstudio code colors */ |
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#undef __CUDA_ARCH__ |
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#define __CUDA_ARCH__ 350 |
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#endif |
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#define TPB30 16 |
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#define TPB35 64 |
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#if __CUDA_ARCH__ >= 300 && __CUDA_ARCH__ < 500 |
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#define Nrow 4 |
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#define Ncol 4 |
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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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__device__ vectype *DMatrix; |
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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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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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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 = (Nrow * Ncol * memshift * thread); |
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uint32_t ps2 = (memshift * (Ncol - 1) * Nrow + memshift * 1 + Nrow * Ncol * memshift * thread); |
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#pragma unroll 4 |
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for (int i = 0; i < Ncol; i++) |
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{ |
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uint32_t s1 = ps1 + Nrow * i *memshift; |
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uint32_t s2 = ps2 - Nrow * 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 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 + Nrow * Ncol * memshift * thread); |
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uint32_t ps2 = (memshift * rowInOut + Nrow * Ncol * memshift * thread); |
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uint32_t ps3 = (Nrow * memshift * (Ncol - 1) + memshift * rowOut + Nrow * Ncol * memshift * thread); |
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for (int i = 0; i < Ncol; i++) |
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{ |
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uint32_t s1 = ps1 + Nrow*i*memshift; |
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uint32_t s2 = ps2 + Nrow*i*memshift; |
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uint32_t s3 = ps3 - Nrow*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 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 + Nrow * Ncol * memshift * thread); |
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uint32_t ps2 = (memshift * rowInOut + Nrow * Ncol * memshift * thread); |
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uint32_t ps3 = (memshift * rowOut + Nrow * Ncol * memshift * thread); |
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#pragma nounroll |
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for (int i = 0; i < Ncol; i++) |
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{ |
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uint32_t s1 = ps1 + Nrow * i*memshift; |
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uint32_t s2 = ps2 + Nrow * i*memshift; |
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uint32_t s3 = ps3 + Nrow * 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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__global__ __launch_bounds__(TPB35, 1) |
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void lyra2v2_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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uint28 blake2b_IV[2]; |
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uint28 padding[2]; |
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if (threadIdx.x == 0) { |
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((uint16*)blake2b_IV)[0] = make_uint16( |
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0xf3bcc908, 0x6a09e667 , 0x84caa73b, 0xbb67ae85 , |
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0xfe94f82b, 0x3c6ef372 , 0x5f1d36f1, 0xa54ff53a , |
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0xade682d1, 0x510e527f , 0x2b3e6c1f, 0x9b05688c , |
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0xfb41bd6b, 0x1f83d9ab , 0x137e2179, 0x5be0cd19 |
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); |
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((uint16*)padding)[0] = make_uint16( |
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0x20, 0x0 , 0x20, 0x0 , 0x20, 0x0 , 0x01, 0x0 , |
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0x04, 0x0 , 0x04, 0x0 , 0x80, 0x0 , 0x0, 0x01000000 |
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); |
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} |
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if (thread < threads) |
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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] = shuffle4(((vectype*)blake2b_IV)[0], 0); |
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state[3] = shuffle4(((vectype*)blake2b_IV)[1], 0); |
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for (int i = 0; i<12; i++) |
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round_lyra_v35(state); |
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state[0] ^= shuffle4(((vectype*)padding)[0], 0); |
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state[1] ^= shuffle4(((vectype*)padding)[1], 0); |
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for (int i = 0; i<12; i++) |
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round_lyra_v35(state); |
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uint32_t ps1 = (4 * memshift * 3 + 16 * memshift * thread); |
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//#pragma unroll 4 |
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for (int i = 0; i < 4; i++) |
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{ |
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uint32_t s1 = ps1 - 4 * 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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uint32_t rowa; |
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int prev = 3; |
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for (int i = 0; i < 4; i++) |
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{ |
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rowa = ((uint2*)state)[0].x & 3; reduceDuplexRowtV3(prev, rowa, i, state, thread); |
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prev = i; |
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} |
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uint32_t shift = (memshift * rowa + 16 * memshift * 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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} //thread |
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} |
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#else |
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/* if __CUDA_ARCH__ < 300 .. */ |
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__global__ void lyra2v2_gpu_hash_32_v3(uint32_t threads, uint32_t startNounce, uint2 *outputHash) {} |
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#endif |
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