GOSTcoin support for ccminer CUDA miner project, compatible with most nvidia cards
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/**
* Penta Blake-512 Cuda Kernel (Tested on SM 5.0)
*
* Tanguy Pruvot - Aug. 2014
*/
#include "miner.h"
extern "C" {
#include "sph/sph_blake.h"
#include <stdint.h>
#include <memory.h>
}
/* threads per block */
#define TPB 192
/* hash by cpu with blake 256 */
extern "C" void pentablakehash(void *output, const void *input)
{
unsigned char hash[128];
#define hashB hash + 64
sph_blake512_context ctx;
sph_blake512_init(&ctx);
sph_blake512(&ctx, input, 80);
sph_blake512_close(&ctx, hash);
sph_blake512(&ctx, hash, 64);
sph_blake512_close(&ctx, hashB);
sph_blake512(&ctx, hashB, 64);
sph_blake512_close(&ctx, hash);
sph_blake512(&ctx, hash, 64);
sph_blake512_close(&ctx, hashB);
sph_blake512(&ctx, hashB, 64);
sph_blake512_close(&ctx, hash);
memcpy(output, hash, 32);
}
#include "cuda_helper.h"
__constant__
static uint32_t __align__(32) c_Target[8];
__constant__
static uint64_t __align__(32) c_data[32];
static uint32_t *d_hash[MAX_GPUS];
static uint32_t *d_resNounce[MAX_GPUS];
static uint32_t *h_resNounce[MAX_GPUS];
static uint32_t extra_results[2] = { UINT32_MAX, UINT32_MAX };
/* prefer uint32_t to prevent size conversions = speed +5/10 % */
__constant__
static uint32_t __align__(32) c_sigma[16][16];
const uint32_t host_sigma[16][16] = {
{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 },
{14, 10, 4, 8, 9, 15, 13, 6, 1, 12, 0, 2, 11, 7, 5, 3 },
{11, 8, 12, 0, 5, 2, 15, 13, 10, 14, 3, 6, 7, 1, 9, 4 },
{ 7, 9, 3, 1, 13, 12, 11, 14, 2, 6, 5, 10, 4, 0, 15, 8 },
{ 9, 0, 5, 7, 2, 4, 10, 15, 14, 1, 11, 12, 6, 8, 3, 13 },
{ 2, 12, 6, 10, 0, 11, 8, 3, 4, 13, 7, 5, 15, 14, 1, 9 },
{12, 5, 1, 15, 14, 13, 4, 10, 0, 7, 6, 3, 9, 2, 8, 11 },
{13, 11, 7, 14, 12, 1, 3, 9, 5, 0, 15, 4, 8, 6, 2, 10 },
{ 6, 15, 14, 9, 11, 3, 0, 8, 12, 2, 13, 7, 1, 4, 10, 5 },
{10, 2, 8, 4, 7, 6, 1, 5, 15, 11, 9, 14, 3, 12, 13 , 0 },
{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 },
{14, 10, 4, 8, 9, 15, 13, 6, 1, 12, 0, 2, 11, 7, 5, 3 },
{11, 8, 12, 0, 5, 2, 15, 13, 10, 14, 3, 6, 7, 1, 9, 4 },
{ 7, 9, 3, 1, 13, 12, 11, 14, 2, 6, 5, 10, 4, 0, 15, 8 },
{ 9, 0, 5, 7, 2, 4, 10, 15, 14, 1, 11, 12, 6, 8, 3, 13 },
{ 2, 12, 6, 10, 0, 11, 8, 3, 4, 13, 7, 5, 15, 14, 1, 9 }
};
__device__ __constant__
static const uint64_t __align__(32) c_IV512[8] = {
0x6a09e667f3bcc908ULL,
0xbb67ae8584caa73bULL,
0x3c6ef372fe94f82bULL,
0xa54ff53a5f1d36f1ULL,
0x510e527fade682d1ULL,
0x9b05688c2b3e6c1fULL,
0x1f83d9abfb41bd6bULL,
0x5be0cd19137e2179ULL
};
__device__ __constant__
const uint64_t c_u512[16] =
{
0x243f6a8885a308d3ULL, 0x13198a2e03707344ULL,
0xa4093822299f31d0ULL, 0x082efa98ec4e6c89ULL,
0x452821e638d01377ULL, 0xbe5466cf34e90c6cULL,
0xc0ac29b7c97c50ddULL, 0x3f84d5b5b5470917ULL,
0x9216d5d98979fb1bULL, 0xd1310ba698dfb5acULL,
0x2ffd72dbd01adfb7ULL, 0xb8e1afed6a267e96ULL,
0xba7c9045f12c7f99ULL, 0x24a19947b3916cf7ULL,
0x0801f2e2858efc16ULL, 0x636920d871574e69ULL
};
#define G(a,b,c,d,x) { \
uint32_t idx1 = c_sigma[i][x]; \
uint32_t idx2 = c_sigma[i][x+1]; \
v[a] += (m[idx1] ^ c_u512[idx2]) + v[b]; \
v[d] = SWAPDWORDS(v[d] ^ v[a]); \
v[c] += v[d]; \
v[b] = ROTR64(v[b] ^ v[c], 25); \
v[a] += (m[idx2] ^ c_u512[idx1]) + v[b]; \
v[d] = ROTR64(v[d] ^ v[a], 16); \
v[c] += v[d]; \
v[b] = ROTR64(v[b] ^ v[c], 11); \
}
// Hash-Padding
__device__ __constant__
static const uint64_t d_constHashPadding[8] = {
0x0000000000000080ull,
0,
0,
0,
0,
0x0100000000000000ull,
0,
0x0002000000000000ull
};
__device__ static
void pentablake_compress(uint64_t *h, const uint64_t *block, const uint64_t T0)
{
uint64_t v[16], m[16], i;
#pragma unroll 16
for(i = 0; i < 16; i++) {
m[i] = cuda_swab64(block[i]);
}
#pragma unroll 8
for (i = 0; i < 8; i++)
v[i] = h[i];
v[ 8] = c_u512[0];
v[ 9] = c_u512[1];
v[10] = c_u512[2];
v[11] = c_u512[3];
v[12] = c_u512[4] ^ T0;
v[13] = c_u512[5] ^ T0;
v[14] = c_u512[6];
v[15] = c_u512[7];
//#pragma unroll 16
for( i = 0; i < 16; i++)
{
/* column step */
G(0, 4, 0x8, 0xC, 0x0);
G(1, 5, 0x9, 0xD, 0x2);
G(2, 6, 0xA, 0xE, 0x4);
G(3, 7, 0xB, 0xF, 0x6);
/* diagonal step */
G(0, 5, 0xA, 0xF, 0x8);
G(1, 6, 0xB, 0xC, 0xA);
G(2, 7, 0x8, 0xD, 0xC);
G(3, 4, 0x9, 0xE, 0xE);
}
//#pragma unroll 16
for (i = 0; i < 16; i++) {
uint32_t idx = i % 8;
h[idx] ^= v[i];
}
}
__global__
void pentablake_gpu_hash_80(uint32_t threads, const uint32_t startNounce, void *outputHash)
{
uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
uint64_t h[8];
uint64_t buf[16];
uint32_t nounce = startNounce + thread;
//#pragma unroll 8
for(int i=0; i<8; i++)
h[i] = c_IV512[i];
//#pragma unroll 16
for (int i=0; i < 16; i++)
buf[i] = c_data[i];
// The test Nonce
((uint32_t*)buf)[19] = cuda_swab32(nounce);
pentablake_compress(h, buf, 640ULL);
#if __CUDA_ARCH__ < 300
uint32_t *outHash = (uint32_t *)outputHash + 16 * thread;
#pragma unroll 8
for (uint32_t i=0; i < 8; i++) {
outHash[2*i] = cuda_swab32( _HIDWORD(h[i]) );
outHash[2*i+1] = cuda_swab32( _LODWORD(h[i]) );
}
#else
uint64_t *outHash = (uint64_t *)outputHash + 8 * thread;
for (uint32_t i=0; i < 8; i++) {
outHash[i] = cuda_swab64( h[i] );
}
#endif
}
}
__host__
void pentablake_cpu_hash_80(int thr_id, uint32_t threads, const uint32_t startNounce, uint32_t *d_outputHash, int order)
{
const uint32_t threadsperblock = TPB;
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
size_t shared_size = 0;
pentablake_gpu_hash_80 <<<grid, block, shared_size>>> (threads, startNounce, d_outputHash);
MyStreamSynchronize(NULL, order, thr_id);
}
__global__
void pentablake_gpu_hash_64(uint32_t threads, uint32_t startNounce, uint64_t *g_hash)
{
uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
uint64_t *inpHash = &g_hash[thread<<3]; // hashPosition * 8
uint64_t buf[16]; // 128 Bytes
uint64_t h[8]; // State
#pragma unroll 8
for (int i=0; i<8; i++)
h[i] = c_IV512[i];
// Message for first round
#pragma unroll 8
for (int i=0; i < 8; ++i)
buf[i] = inpHash[i];
#pragma unroll 8
for (int i=0; i < 8; i++)
buf[i+8] = d_constHashPadding[i];
// Ending round
pentablake_compress(h, buf, 512);
#if __CUDA_ARCH__ < 300
uint32_t *outHash = (uint32_t*)&g_hash[thread<<3];
#pragma unroll 8
for (int i=0; i < 8; i++) {
outHash[2*i+0] = cuda_swab32( _HIDWORD(h[i]) );
outHash[2*i+1] = cuda_swab32( _LODWORD(h[i]) );
}
#else
uint64_t *outHash = &g_hash[thread<<3];
for (int i=0; i < 8; i++) {
outHash[i] = cuda_swab64(h[i]);
}
#endif
}
}
__host__
void pentablake_cpu_hash_64(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_outputHash, int order)
{
const uint32_t threadsperblock = TPB;
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
size_t shared_size = 0;
pentablake_gpu_hash_64 <<<grid, block, shared_size>>> (threads, startNounce, (uint64_t*)d_outputHash);
MyStreamSynchronize(NULL, order, thr_id);
}
__global__
void pentablake_gpu_check_hash(uint32_t threads, uint32_t startNounce, uint32_t *g_hash, uint32_t *resNounce)
{
uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x);
if (thread < threads)
{
uint32_t nounce = startNounce + thread;
uint32_t *inpHash = &g_hash[thread<<4];
uint32_t h[8];
#pragma unroll 8
for (int i=0; i < 8; i++)
h[i] = inpHash[i];
for (int i = 7; i >= 0; i--) {
uint32_t hash = h[i]; // cuda_swab32(h[i]);
if (hash > c_Target[i]) {
return;
}
if (hash < c_Target[i]) {
break;
}
}
/* keep the smallest nounce, + extra one if found */
if (resNounce[0] > nounce) {
resNounce[1] = resNounce[0];
resNounce[0] = nounce;
}
else
resNounce[1] = nounce;
}
}
__host__ static
uint32_t pentablake_check_hash(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_inputHash, int order)
{
const uint32_t threadsperblock = TPB;
uint32_t result = UINT32_MAX;
dim3 grid((threads + threadsperblock-1)/threadsperblock);
dim3 block(threadsperblock);
size_t shared_size = 0;
/* Check error on Ctrl+C or kill to prevent segfaults on exit */
if (cudaMemset(d_resNounce[thr_id], 0xff, 2*sizeof(uint32_t)) != cudaSuccess)
return result;
pentablake_gpu_check_hash <<<grid, block, shared_size>>> (threads, startNounce, d_inputHash, d_resNounce[thr_id]);
CUDA_SAFE_CALL(cudaThreadSynchronize());
if (cudaSuccess == cudaMemcpy(h_resNounce[thr_id], d_resNounce[thr_id], 2*sizeof(uint32_t), cudaMemcpyDeviceToHost)) {
cudaThreadSynchronize();
result = h_resNounce[thr_id][0];
extra_results[0] = h_resNounce[thr_id][1];
}
return result;
}
__host__
void pentablake_cpu_setBlock_80(uint32_t *pdata, const uint32_t *ptarget)
{
uint8_t data[128];
memcpy((void*) data, (void*) pdata, 80);
memset(data+80, 0, 48);
// to swab...
data[80] = 0x80;
data[111] = 1;
data[126] = 0x02;
data[127] = 0x80;
CUDA_SAFE_CALL(cudaMemcpyToSymbol(c_data, data, sizeof(data), 0, cudaMemcpyHostToDevice));
CUDA_SAFE_CALL(cudaMemcpyToSymbol(c_sigma, host_sigma, sizeof(host_sigma), 0, cudaMemcpyHostToDevice));
CUDA_SAFE_CALL(cudaMemcpyToSymbol(c_Target, ptarget, 32, 0, cudaMemcpyHostToDevice));
}
static bool init[MAX_GPUS] = { 0 };
extern "C" int scanhash_pentablake(int thr_id, struct work *work, uint32_t max_nonce, unsigned long *hashes_done)
{
uint32_t _ALIGN(64) endiandata[20];
uint32_t *pdata = work->data;
uint32_t *ptarget = work->target;
const uint32_t first_nonce = pdata[19];
int rc = 0;
uint32_t throughput = device_intensity(thr_id, __func__, 128U * 2560); // 18.5
throughput = min(throughput, max_nonce - first_nonce);
if (opt_benchmark)
((uint32_t*)ptarget)[7] = 0x000F;
if (!init[thr_id]) {
if (active_gpus > 1) {
cudaSetDevice(device_map[thr_id]);
}
CUDA_SAFE_CALL(cudaMalloc(&d_hash[thr_id], (size_t) 64 * throughput));
CUDA_SAFE_CALL(cudaMallocHost(&h_resNounce[thr_id], 2*sizeof(uint32_t)));
CUDA_SAFE_CALL(cudaMalloc(&d_resNounce[thr_id], 2*sizeof(uint32_t)));
init[thr_id] = true;
}
for (int k=0; k < 20; k++)
be32enc(&endiandata[k], pdata[k]);
pentablake_cpu_setBlock_80(endiandata, ptarget);
do {
int order = 0;
// GPU HASH
pentablake_cpu_hash_80(thr_id, throughput, pdata[19], d_hash[thr_id], order++);
pentablake_cpu_hash_64(thr_id, throughput, pdata[19], d_hash[thr_id], order++);
pentablake_cpu_hash_64(thr_id, throughput, pdata[19], d_hash[thr_id], order++);
pentablake_cpu_hash_64(thr_id, throughput, pdata[19], d_hash[thr_id], order++);
pentablake_cpu_hash_64(thr_id, throughput, pdata[19], d_hash[thr_id], order++);
*hashes_done = pdata[19] - first_nonce + throughput;
uint32_t foundNonce = pentablake_check_hash(thr_id, throughput, pdata[19], d_hash[thr_id], order++);
if (foundNonce != UINT32_MAX)
{
uint32_t vhash[8];
be32enc(&endiandata[19], foundNonce);
pentablakehash(vhash, endiandata);
if (vhash[7] <= ptarget[7] && fulltest(vhash, ptarget)) {
rc = 1;
work_set_target_ratio(work, vhash);
if (extra_results[0] != UINT32_MAX) {
// Rare but possible if the throughput is big
be32enc(&endiandata[19], extra_results[0]);
pentablakehash(vhash, endiandata);
if (bn_hash_target_ratio(vhash, ptarget) > work->shareratio)
work_set_target_ratio(work, vhash);
applog(LOG_NOTICE, "GPU found more than one result yippee!");
pdata[21] = extra_results[0];
extra_results[0] = UINT32_MAX;
rc++;
}
pdata[19] = foundNonce;
return rc;
} else {
applog(LOG_WARNING, "GPU #%d: result for nounce %08x does not validate on CPU!", device_map[thr_id], foundNonce);
}
}
pdata[19] += throughput;
} while (pdata[19] < max_nonce && !work_restart[thr_id].restart);
*hashes_done = pdata[19] - first_nonce + 1;
return rc;
}
// cleanup
void free_pentablake(int thr_id)
{
if (!init[thr_id])
return;
cudaSetDevice(device_map[thr_id]);
cudaFree(d_hash[thr_id]);
cudaFreeHost(h_resNounce[thr_id]);
cudaFree(d_resNounce[thr_id]);
init[thr_id] = false;
cudaDeviceSynchronize();
}