GOSTcoin support for ccminer CUDA miner project, compatible with most nvidia cards
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// Auf QuarkCoin spezialisierte Version von Groestl inkl. Bitslice
#include <stdio.h>
#include <memory.h>
#include "cuda_helper.h"
#define TPB 256
#define THF 4
#if __CUDA_ARCH__ >= 300
#include "groestl_functions_quad.cu"
#include "bitslice_transformations_quad.cu"
#endif
#include "quark/cuda_quark_groestl512_sm20.cu"
__global__ __launch_bounds__(TPB, THF)
void quark_groestl512_gpu_hash_64_quad(uint32_t threads, uint32_t startNounce, uint32_t * __restrict g_hash, uint32_t * __restrict g_nonceVector)
{
#if __CUDA_ARCH__ >= 300
// durch 4 dividieren, weil jeweils 4 Threads zusammen ein Hash berechnen
uint32_t 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 ? g_nonceVector[thread] : (startNounce + thread);
int hashPosition = nounce - startNounce;
uint32_t *inpHash = &g_hash[hashPosition << 4];
const uint16_t thr = threadIdx.x % THF;
#pragma unroll
for(int k=0;k<4;k++) message[k] = inpHash[(k * THF) + thr];
#pragma unroll
for(int k=4;k<8;k++) message[k] = 0;
if (thr == 0) message[4] = 0x80;
if (thr == 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 = inpHash;
uint32_t hash[16];
from_bitslice_quad(state, hash);
// uint4 = 4x4 uint32_t = 16 bytes
if (thr == 0) {
uint4 *phash = (uint4*) hash;
uint4 *outpt = (uint4*) outpHash; /* var kept for hash align */
outpt[0] = phash[0];
outpt[1] = phash[1];
outpt[2] = phash[2];
outpt[3] = phash[3];
}
/*
if (thr == 0) {
#pragma unroll
for(int k=0;k<16;k++) outpHash[k] = hash[k];
}
*/
}
#endif
}
__global__ void __launch_bounds__(TPB, THF)
quark_doublegroestl512_gpu_hash_64_quad(uint32_t threads, uint32_t startNounce, uint32_t *g_hash, uint32_t *g_nonceVector)
{
#if __CUDA_ARCH__ >= 300
uint32_t 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 ? g_nonceVector[thread] : (startNounce + thread);
int hashPosition = nounce - startNounce;
uint32_t * inpHash = &g_hash[hashPosition<<4];
const uint16_t thr = threadIdx.x % THF;
#pragma unroll
for(int k=0;k<4;k++) message[k] = inpHash[(k * THF) + thr];
#pragma unroll
for(int k=4;k<8;k++) message[k] = 0;
if (thr == 0) message[4] = 0x80;
if (thr == 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 = inpHash;
uint32_t hash[16];
from_bitslice_quad(state, hash);
if (thr == 0)
{
#pragma unroll
for(int k=0;k<16;k++) outpHash[k] = hash[k];
}
}
#endif
}
__host__
void quark_groestl512_cpu_init(int thr_id, uint32_t threads)
{
int dev_id = device_map[thr_id];
cuda_get_arch(thr_id);
if (device_sm[dev_id] < 300 || cuda_arch[dev_id] < 300)
quark_groestl512_sm20_init(thr_id, threads);
}
__host__
void quark_groestl512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order)
{
int threadsperblock = TPB;
// 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 = THF;
// berechne wie viele Thread Blocks wir brauchen
dim3 grid(factor*((threads + threadsperblock-1)/threadsperblock));
dim3 block(threadsperblock);
int dev_id = device_map[thr_id];
if (device_sm[dev_id] >= 300 && cuda_arch[dev_id] >= 300)
quark_groestl512_gpu_hash_64_quad<<<grid, block>>>(threads, startNounce, d_hash, d_nonceVector);
else
quark_groestl512_sm20_hash_64(thr_id, threads, startNounce, d_nonceVector, d_hash, order);
// Strategisches Sleep Kommando zur Senkung der CPU Last
MyStreamSynchronize(NULL, order, thr_id);
}
__host__
void quark_doublegroestl512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order)
{
const int factor = THF;
int threadsperblock = TPB;
dim3 grid(factor*((threads + threadsperblock-1)/threadsperblock));
dim3 block(threadsperblock);
int dev_id = device_map[thr_id];
if (device_sm[dev_id] >= 300 && cuda_arch[dev_id] >= 300)
quark_doublegroestl512_gpu_hash_64_quad<<<grid, block>>>(threads, startNounce, d_hash, d_nonceVector);
else
quark_doublegroestl512_sm20_hash_64(thr_id, threads, startNounce, d_nonceVector, d_hash, order);
MyStreamSynchronize(NULL, order, thr_id);
}