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// Auf QuarkCoin spezialisierte Version von Groestl inkl. Bitslice
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#include <stdio.h>
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#include <memory.h>
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#include "cuda_helper.h"
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#define TPB 256
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#define THF 4
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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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// diese Struktur wird in der Init Funktion angefordert
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static cudaDeviceProp props[8];
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// 64 Register Variante f<EFBFBD>r 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__ __launch_bounds__(TPB, THF)
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void quark_groestl512_gpu_hash_64_quad(int threads, uint32_t startNounce, uint32_t * __restrict g_hash, uint32_t * __restrict 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 ? 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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const uint16_t thr = threadIdx.x % THF;
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#pragma unroll
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for(int k=0;k<4;k++) message[k] = inpHash[(k * THF) + thr];
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#pragma unroll
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for(int k=4;k<8;k++) message[k] = 0;
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if (thr == 0) message[4] = 0x80;
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if (thr == 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 = inpHash;
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uint32_t hash[16];
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from_bitslice_quad(state, hash);
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if (thr == 0)
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{
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#pragma unroll
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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__(TPB, THF)
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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 ? 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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const uint16_t thr = threadIdx.x % THF;
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#pragma unroll
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for(int k=0;k<4;k++) message[k] = inpHash[(k * THF) + thr];
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#pragma unroll
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for(int k=4;k<8;k++) message[k] = 0;
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if (thr == 0) message[4] = 0x80;
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if (thr == 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 = inpHash;
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uint32_t hash[16];
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from_bitslice_quad(state, hash);
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if (thr == 0)
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{
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#pragma unroll
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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 = TPB;
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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 = THF;
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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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// Gr<EFBFBD><EFBFBD>e 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 = TPB;
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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 = THF;
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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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// Gr<EFBFBD><EFBFBD>e 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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