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