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173 lines
6.0 KiB
173 lines
6.0 KiB
// Auf QuarkCoin spezialisierte Version von Groestl inkl. Bitslice |
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#include <cuda.h> |
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#include "cuda_runtime.h" |
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#include "device_launch_parameters.h" |
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#include <stdio.h> |
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#include <memory.h> |
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// aus cpu-miner.c |
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extern int device_map[8]; |
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// aus heavy.cu |
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extern cudaError_t MyStreamSynchronize(cudaStream_t stream, int situation, int thr_id); |
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// Folgende Definitionen später durch header ersetzen |
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typedef unsigned char uint8_t; |
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typedef unsigned short uint16_t; |
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typedef unsigned int uint32_t; |
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// diese Struktur wird in der Init Funktion angefordert |
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static cudaDeviceProp props[8]; |
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// 64 Register Variante für Compute 3.0 |
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#include "groestl_functions_quad.cu" |
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#include "bitslice_transformations_quad.cu" |
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__global__ void __launch_bounds__(256, 4) |
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quark_groestl512_gpu_hash_64_quad(int threads, uint32_t startNounce, uint32_t *g_hash, uint32_t *g_nonceVector) |
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{ |
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// durch 4 dividieren, weil jeweils 4 Threads zusammen ein Hash berechnen |
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int thread = (blockDim.x * blockIdx.x + threadIdx.x) >> 2; |
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if (thread < threads) |
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{ |
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// GROESTL |
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uint32_t message[8]; |
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uint32_t state[8]; |
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uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread); |
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int hashPosition = nounce - startNounce; |
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uint32_t *inpHash = &g_hash[hashPosition<<4]; |
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#pragma unroll 4 |
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for(int k=0;k<4;k++) message[k] = inpHash[(k<<2) + (threadIdx.x&0x03)]; |
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#pragma unroll 4 |
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for(int k=4;k<8;k++) message[k] = 0; |
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if ((threadIdx.x&0x03) == 0) message[4] = 0x80; |
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if ((threadIdx.x&0x03) == 3) message[7] = 0x01000000; |
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uint32_t msgBitsliced[8]; |
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to_bitslice_quad(message, msgBitsliced); |
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groestl512_progressMessage_quad(state, msgBitsliced); |
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// Nur der erste von jeweils 4 Threads bekommt das Ergebns-Hash |
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uint32_t *outpHash = &g_hash[hashPosition<<4]; |
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uint32_t hash[16]; |
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from_bitslice_quad(state, hash); |
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if ((threadIdx.x & 0x03) == 0) |
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{ |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) outpHash[k] = hash[k]; |
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} |
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} |
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} |
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__global__ void __launch_bounds__(256, 4) |
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quark_doublegroestl512_gpu_hash_64_quad(int threads, uint32_t startNounce, uint32_t *g_hash, uint32_t *g_nonceVector) |
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{ |
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int thread = (blockDim.x * blockIdx.x + threadIdx.x)>>2; |
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if (thread < threads) |
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{ |
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// GROESTL |
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uint32_t message[8]; |
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uint32_t state[8]; |
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uint32_t nounce = (g_nonceVector != NULL) ? g_nonceVector[thread] : (startNounce + thread); |
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int hashPosition = nounce - startNounce; |
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uint32_t *inpHash = &g_hash[hashPosition<<4]; |
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#pragma unroll 4 |
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for(int k=0;k<4;k++) message[k] = inpHash[(k<<2)+(threadIdx.x&0x03)]; |
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#pragma unroll 4 |
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for(int k=4;k<8;k++) message[k] = 0; |
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if ((threadIdx.x&0x03) == 0) message[4] = 0x80; |
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if ((threadIdx.x&0x03) == 3) message[7] = 0x01000000; |
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uint32_t msgBitsliced[8]; |
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to_bitslice_quad(message, msgBitsliced); |
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for (int round=0; round<2; round++) |
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{ |
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groestl512_progressMessage_quad(state, msgBitsliced); |
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if (round < 1) |
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{ |
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// Verkettung zweier Runden inclusive Padding. |
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msgBitsliced[ 0] = __byte_perm(state[ 0], 0x00800100, 0x4341 + (((threadIdx.x%4)==3)<<13)); |
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msgBitsliced[ 1] = __byte_perm(state[ 1], 0x00800100, 0x4341); |
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msgBitsliced[ 2] = __byte_perm(state[ 2], 0x00800100, 0x4341); |
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msgBitsliced[ 3] = __byte_perm(state[ 3], 0x00800100, 0x4341); |
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msgBitsliced[ 4] = __byte_perm(state[ 4], 0x00800100, 0x4341); |
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msgBitsliced[ 5] = __byte_perm(state[ 5], 0x00800100, 0x4341); |
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msgBitsliced[ 6] = __byte_perm(state[ 6], 0x00800100, 0x4341); |
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msgBitsliced[ 7] = __byte_perm(state[ 7], 0x00800100, 0x4341 + (((threadIdx.x%4)==0)<<4)); |
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} |
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} |
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// Nur der erste von jeweils 4 Threads bekommt das Ergebns-Hash |
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uint32_t *outpHash = &g_hash[hashPosition<<4]; |
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uint32_t hash[16]; |
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from_bitslice_quad(state, hash); |
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if ((threadIdx.x & 0x03) == 0) |
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{ |
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#pragma unroll 16 |
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for(int k=0;k<16;k++) outpHash[k] = hash[k]; |
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} |
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} |
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} |
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// Setup-Funktionen |
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__host__ void quark_groestl512_cpu_init(int thr_id, int threads) |
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{ |
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cudaGetDeviceProperties(&props[thr_id], device_map[thr_id]); |
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} |
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__host__ void quark_groestl512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order) |
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{ |
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int threadsperblock = 256; |
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// Compute 3.0 benutzt die registeroptimierte Quad Variante mit Warp Shuffle |
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// mit den Quad Funktionen brauchen wir jetzt 4 threads pro Hash, daher Faktor 4 bei der Blockzahl |
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const int factor = 4; |
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// berechne wie viele Thread Blocks wir brauchen |
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dim3 grid(factor*((threads + threadsperblock-1)/threadsperblock)); |
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dim3 block(threadsperblock); |
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// Größe des dynamischen Shared Memory Bereichs |
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size_t shared_size = 0; |
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quark_groestl512_gpu_hash_64_quad<<<grid, block, shared_size>>>(threads, startNounce, d_hash, d_nonceVector); |
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// Strategisches Sleep Kommando zur Senkung der CPU Last |
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MyStreamSynchronize(NULL, order, thr_id); |
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} |
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__host__ void quark_doublegroestl512_cpu_hash_64(int thr_id, int threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order) |
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{ |
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int threadsperblock = 256; |
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// Compute 3.0 benutzt die registeroptimierte Quad Variante mit Warp Shuffle |
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// mit den Quad Funktionen brauchen wir jetzt 4 threads pro Hash, daher Faktor 4 bei der Blockzahl |
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const int factor = 4; |
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// berechne wie viele Thread Blocks wir brauchen |
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dim3 grid(factor*((threads + threadsperblock-1)/threadsperblock)); |
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dim3 block(threadsperblock); |
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// Größe des dynamischen Shared Memory Bereichs |
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size_t shared_size = 0; |
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quark_doublegroestl512_gpu_hash_64_quad<<<grid, block, shared_size>>>(threads, startNounce, d_hash, d_nonceVector); |
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// Strategisches Sleep Kommando zur Senkung der CPU Last |
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MyStreamSynchronize(NULL, order, thr_id); |
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}
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