GOSTcoin support for ccminer CUDA miner project, compatible with most nvidia cards
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#include <cuda.h>
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
// Folgende Definitionen sp<EFBFBD>ter durch header ersetzen
typedef unsigned int uint32_t;
// globaler Speicher f<EFBFBD>r unsere Ergebnisse
uint32_t *d_hashoutput[8];
extern uint32_t *d_hash2output[8];
extern uint32_t *d_hash3output[8];
extern uint32_t *d_hash4output[8];
extern uint32_t *d_hash5output[8];
extern uint32_t *d_nonceVector[8];
/* Combines top 64-bits from each hash into a single hash */
static void __device__ combine_hashes(uint32_t *out, uint32_t *hash1, uint32_t *hash2, uint32_t *hash3, uint32_t *hash4)
{
uint32_t lout[8]; // Combining in Registern machen
#pragma unroll 8
for (int i=0; i < 8; ++i)
lout[i] = 0;
// das Makro setzt jeweils 4 Bits aus vier verschiedenen Hashes zu einem Nibble zusammen
#define MIX(bits, mask, i) \
lout[(255 - (bits+3))/32] <<= 4; \
if ((hash1[i] & mask) != 0) lout[(255 - (bits+0))/32] |= 8; \
if ((hash2[i] & mask) != 0) lout[(255 - (bits+1))/32] |= 4; \
if ((hash3[i] & mask) != 0) lout[(255 - (bits+2))/32] |= 2; \
if ((hash4[i] & mask) != 0) lout[(255 - (bits+3))/32] |= 1; \
/* Transpose first 64 bits of each hash into out */
MIX( 0, 0x80000000, 7);
MIX( 4, 0x40000000, 7);
MIX( 8, 0x20000000, 7);
MIX( 12, 0x10000000, 7);
MIX( 16, 0x08000000, 7);
MIX( 20, 0x04000000, 7);
MIX( 24, 0x02000000, 7);
MIX( 28, 0x01000000, 7);
MIX( 32, 0x00800000, 7);
MIX( 36, 0x00400000, 7);
MIX( 40, 0x00200000, 7);
MIX( 44, 0x00100000, 7);
MIX( 48, 0x00080000, 7);
MIX( 52, 0x00040000, 7);
MIX( 56, 0x00020000, 7);
MIX( 60, 0x00010000, 7);
MIX( 64, 0x00008000, 7);
MIX( 68, 0x00004000, 7);
MIX( 72, 0x00002000, 7);
MIX( 76, 0x00001000, 7);
MIX( 80, 0x00000800, 7);
MIX( 84, 0x00000400, 7);
MIX( 88, 0x00000200, 7);
MIX( 92, 0x00000100, 7);
MIX( 96, 0x00000080, 7);
MIX(100, 0x00000040, 7);
MIX(104, 0x00000020, 7);
MIX(108, 0x00000010, 7);
MIX(112, 0x00000008, 7);
MIX(116, 0x00000004, 7);
MIX(120, 0x00000002, 7);
MIX(124, 0x00000001, 7);
MIX(128, 0x80000000, 6);
MIX(132, 0x40000000, 6);
MIX(136, 0x20000000, 6);
MIX(140, 0x10000000, 6);
MIX(144, 0x08000000, 6);
MIX(148, 0x04000000, 6);
MIX(152, 0x02000000, 6);
MIX(156, 0x01000000, 6);
MIX(160, 0x00800000, 6);
MIX(164, 0x00400000, 6);
MIX(168, 0x00200000, 6);
MIX(172, 0x00100000, 6);
MIX(176, 0x00080000, 6);
MIX(180, 0x00040000, 6);
MIX(184, 0x00020000, 6);
MIX(188, 0x00010000, 6);
MIX(192, 0x00008000, 6);
MIX(196, 0x00004000, 6);
MIX(200, 0x00002000, 6);
MIX(204, 0x00001000, 6);
MIX(208, 0x00000800, 6);
MIX(212, 0x00000400, 6);
MIX(216, 0x00000200, 6);
MIX(220, 0x00000100, 6);
MIX(224, 0x00000080, 6);
MIX(228, 0x00000040, 6);
MIX(232, 0x00000020, 6);
MIX(236, 0x00000010, 6);
MIX(240, 0x00000008, 6);
MIX(244, 0x00000004, 6);
MIX(248, 0x00000002, 6);
MIX(252, 0x00000001, 6);
#pragma unroll 8
for (int i=0; i < 8; ++i)
out[i] = lout[i];
}
__global__ void combine_gpu_hash(int threads, uint32_t startNounce, uint32_t *out, uint32_t *hash2, uint32_t *hash3, uint32_t *hash4, uint32_t *hash5, uint32_t *nonceVector)
{
int thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
uint32_t nounce = nonceVector[thread];
uint32_t hashPosition = nounce - startNounce;
// Die Aufgabe der combine-funktion besteht aus zwei Teilen.
// 1) Komprimiere die hashes zu einem kleinen Array
// 2) Errechne dort den combines-value
// Die Kompression wird dadurch verwirklicht, dass im out-array weiterhin mit "thread" indiziert
// wird. Die anderen Werte werden mit der nonce indiziert
combine_hashes(&out[8 * thread], &hash2[8 * hashPosition], &hash3[16 * hashPosition], &hash4[16 * hashPosition], &hash5[16 * hashPosition]);
}
}
// Setup-Funktionen
__host__ void combine_cpu_init(int thr_id, int threads)
{
// Speicher f<EFBFBD>r alle Ergebnisse belegen
cudaMalloc(&d_hashoutput[thr_id], 8 * sizeof(uint32_t) * threads);
}
void combine_cpu_hash(int thr_id, int threads, uint32_t startNounce, uint32_t *hash)
{
// diese Kopien sind optional, da die Hashes jetzt bereits auf der GPU liegen sollten
const int threadsperblock = 128;
// berechne wie viele Thread Blocks wir brauchen
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
// Gr<EFBFBD><EFBFBD>e des dynamischen Shared Memory Bereichs
size_t shared_size = 0;
// fprintf(stderr, "threads=%d, %d blocks, %d threads per block, %d bytes shared\n", threads, grid.x, block.x, shared_size);
combine_gpu_hash<<<grid, block, shared_size>>>(threads, startNounce, d_hashoutput[thr_id], d_hash2output[thr_id], d_hash3output[thr_id], d_hash4output[thr_id], d_hash5output[thr_id], d_nonceVector[thr_id]);
// da die Hash Auswertung noch auf der CPU erfolgt, m<EFBFBD>ssen die Ergebnisse auf jeden Fall zum Host kopiert werden
cudaMemcpy(hash, d_hashoutput[thr_id], 8 * sizeof(uint32_t) * threads, cudaMemcpyDeviceToHost);
}