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// Auf Groestlcoin 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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#include <host_defines.h>
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// globaler Speicher für alle HeftyHashes aller Threads
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__constant__ uint32_t pTarget[8]; // Single GPU
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extern uint32_t *d_resultNonce[8];
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__constant__ uint32_t groestlcoin_gpu_msg[32];
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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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#define SWAB32(x) cuda_swab32(x)
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__global__ __launch_bounds__(256, 4)
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void groestlcoin_gpu_hash_quad(int threads, uint32_t startNounce, uint32_t *resNounce)
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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) / 4;
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if (thread < threads)
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{
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// GROESTL
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uint32_t paddedInput[8];
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#pragma unroll 8
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for(int k=0;k<8;k++) paddedInput[k] = groestlcoin_gpu_msg[4*k+threadIdx.x%4];
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uint32_t nounce = startNounce + thread;
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if ((threadIdx.x % 4) == 3)
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paddedInput[4] = SWAB32(nounce); // 4*4+3 = 19
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uint32_t msgBitsliced[8];
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to_bitslice_quad(paddedInput, msgBitsliced);
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uint32_t state[8];
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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)*0x2000);
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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)*0x0010);
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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 out_state[16];
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from_bitslice_quad(state, out_state);
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if (threadIdx.x % 4 == 0)
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{
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int i, position = -1;
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bool rc = true;
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#pragma unroll 8
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for (i = 7; i >= 0; i--) {
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if (out_state[i] > pTarget[i]) {
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if(position < i) {
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position = i;
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rc = false;
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}
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}
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if (out_state[i] < pTarget[i]) {
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if(position < i) {
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position = i;
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rc = true;
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}
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}
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}
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if(rc == true)
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if(resNounce[0] > nounce)
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resNounce[0] = nounce;
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}
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}
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}
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// Setup-Funktionen
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__host__ void groestlcoin_cpu_init(int thr_id, int threads)
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{
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cudaSetDevice(device_map[thr_id]);
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// Speicher für Gewinner-Nonce belegen
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cudaMalloc(&d_resultNonce[thr_id], sizeof(uint32_t));
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}
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__host__ void groestlcoin_cpu_setBlock(int thr_id, void *data, void *pTargetIn)
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{
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// Nachricht expandieren und setzen
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uint32_t msgBlock[32];
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memset(msgBlock, 0, sizeof(uint32_t) * 32);
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memcpy(&msgBlock[0], data, 80);
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// Erweitere die Nachricht auf den Nachrichtenblock (padding)
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// Unsere Nachricht hat 80 Byte
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msgBlock[20] = 0x80;
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msgBlock[31] = 0x01000000;
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// groestl512 braucht hierfür keinen CPU-Code (die einzige Runde wird
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// auf der GPU ausgeführt)
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// Blockheader setzen (korrekte Nonce und Hefty Hash fehlen da drin noch)
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cudaMemcpyToSymbol( groestlcoin_gpu_msg,
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msgBlock,
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128);
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cudaMemset(d_resultNonce[thr_id], 0xFF, sizeof(uint32_t));
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cudaMemcpyToSymbol( pTarget,
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pTargetIn,
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sizeof(uint32_t) * 8 );
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}
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__host__ void groestlcoin_cpu_hash(int thr_id, int threads, uint32_t startNounce, void *outputHashes, uint32_t *nounce)
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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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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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cudaMemset(d_resultNonce[thr_id], 0xFF, sizeof(uint32_t));
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groestlcoin_gpu_hash_quad<<<grid, block, shared_size>>>(threads, startNounce, d_resultNonce[thr_id]);
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// Strategisches Sleep Kommando zur Senkung der CPU Last
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MyStreamSynchronize(NULL, 0, thr_id);
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cudaMemcpy(nounce, d_resultNonce[thr_id], sizeof(uint32_t), cudaMemcpyDeviceToHost);
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}
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