GOSTcoin support for ccminer CUDA miner project, compatible with most nvidia cards
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// Auf Groestlcoin spezialisierte Version von Groestl inkl. Bitslice
#include <stdio.h>
#include <memory.h>
#include "cuda_helper.h"
#include <host_defines.h>
// globaler Speicher für alle HeftyHashes aller Threads
__constant__ uint32_t pTarget[8]; // Single GPU
__constant__ uint32_t groestlcoin_gpu_msg[32];
static uint32_t *d_resultNonce[MAX_GPUS];
#if __CUDA_ARCH__ >= 300
// 64 Registers Variant for Compute 3.0+
#include "quark/groestl_functions_quad.h"
#include "quark/groestl_transf_quad.h"
#endif
#define SWAB32(x) cuda_swab32(x)
__global__ __launch_bounds__(256, 4)
void groestlcoin_gpu_hash_quad(uint32_t threads, uint32_t startNounce, uint32_t *resNounce)
{
#if __CUDA_ARCH__ >= 300
// durch 4 dividieren, weil jeweils 4 Threads zusammen ein Hash berechnen
uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x) / 4;
if (thread < threads)
{
// GROESTL
uint32_t paddedInput[8];
#pragma unroll 8
for(int k=0;k<8;k++) paddedInput[k] = groestlcoin_gpu_msg[4*k+threadIdx.x%4];
uint32_t nounce = startNounce + thread;
if ((threadIdx.x % 4) == 3)
paddedInput[4] = SWAB32(nounce); // 4*4+3 = 19
uint32_t msgBitsliced[8];
to_bitslice_quad(paddedInput, msgBitsliced);
uint32_t state[8];
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)*0x2000);
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)*0x0010);
}
}
// Nur der erste von jeweils 4 Threads bekommt das Ergebns-Hash
uint32_t out_state[16];
from_bitslice_quad(state, out_state);
if (threadIdx.x % 4 == 0)
{
int i, position = -1;
bool rc = true;
#pragma unroll 8
for (i = 7; i >= 0; i--) {
if (out_state[i] > pTarget[i]) {
if(position < i) {
position = i;
rc = false;
}
}
if (out_state[i] < pTarget[i]) {
if(position < i) {
position = i;
rc = true;
}
}
}
if(rc == true)
if(resNounce[0] > nounce)
resNounce[0] = nounce;
}
}
#endif
}
__host__
void groestlcoin_cpu_init(int thr_id, uint32_t threads)
{
cudaMalloc(&d_resultNonce[thr_id], sizeof(uint32_t));
}
__host__
void groestlcoin_cpu_setBlock(int thr_id, void *data, void *pTargetIn)
{
// Nachricht expandieren und setzen
uint32_t msgBlock[32];
memset(msgBlock, 0, sizeof(uint32_t) * 32);
memcpy(&msgBlock[0], data, 80);
// Erweitere die Nachricht auf den Nachrichtenblock (padding)
// Unsere Nachricht hat 80 Byte
msgBlock[20] = 0x80;
msgBlock[31] = 0x01000000;
// groestl512 braucht hierfür keinen CPU-Code (die einzige Runde wird
// auf der GPU ausgeführt)
// Blockheader setzen (korrekte Nonce und Hefty Hash fehlen da drin noch)
cudaMemcpyToSymbol( groestlcoin_gpu_msg,
msgBlock,
128);
cudaMemset(d_resultNonce[thr_id], 0xFF, sizeof(uint32_t));
cudaMemcpyToSymbol( pTarget,
pTargetIn,
sizeof(uint32_t) * 8 );
}
__host__
void groestlcoin_cpu_hash(int thr_id, uint32_t threads, uint32_t startNounce, void *outputHashes, uint32_t *nounce)
{
uint32_t 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
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;
if (device_sm[device_map[thr_id]] < 300) {
printf("Sorry, This algo is not supported by this GPU arch (SM 3.0 required)");
return;
}
cudaMemset(d_resultNonce[thr_id], 0xFF, sizeof(uint32_t));
groestlcoin_gpu_hash_quad<<<grid, block, shared_size>>>(threads, startNounce, d_resultNonce[thr_id]);
// Strategisches Sleep Kommando zur Senkung der CPU Last
MyStreamSynchronize(NULL, 0, thr_id);
cudaMemcpy(nounce, d_resultNonce[thr_id], sizeof(uint32_t), cudaMemcpyDeviceToHost);
}