GOSTCoin CUDA miner project, compatible with most nvidia cards, containing only gostd algo
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/**
* Blake2-B CUDA Implementation
*
* tpruvot@github July 2016
*
*/
#include <miner.h>
#include <string.h>
#include <stdint.h>
#include <sph/blake2b.h>
#include <cuda_helper.h>
#include <cuda_vector_uint2x4.h>
#define TPB 512
#define NBN 2
static uint32_t *d_resNonces[MAX_GPUS];
__device__ uint64_t d_data[10];
static __constant__ const int8_t blake2b_sigma[12][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 }
};
// host mem align
#define A 64
extern "C" void blake2b_hash(void *output, const void *input)
{
uint8_t _ALIGN(A) hash[32];
blake2b_ctx ctx;
blake2b_init(&ctx, 32, NULL, 0);
blake2b_update(&ctx, input, 80);
blake2b_final(&ctx, hash);
memcpy(output, hash, 32);
}
// ----------------------------------------------------------------
__device__ __forceinline__
static void G(const int r, const int i, uint64_t &a, uint64_t &b, uint64_t &c, uint64_t &d, uint64_t const m[16])
{
a = a + b + m[ blake2b_sigma[r][2*i] ];
((uint2*)&d)[0] = SWAPUINT2( ((uint2*)&d)[0] ^ ((uint2*)&a)[0] );
c = c + d;
((uint2*)&b)[0] = ROR24( ((uint2*)&b)[0] ^ ((uint2*)&c)[0] );
a = a + b + m[ blake2b_sigma[r][2*i+1] ];
((uint2*)&d)[0] = ROR16( ((uint2*)&d)[0] ^ ((uint2*)&a)[0] );
c = c + d;
((uint2*)&b)[0] = ROR2( ((uint2*)&b)[0] ^ ((uint2*)&c)[0], 63U);
}
#define ROUND(r) \
G(r, 0, v[0], v[4], v[ 8], v[12], m); \
G(r, 1, v[1], v[5], v[ 9], v[13], m); \
G(r, 2, v[2], v[6], v[10], v[14], m); \
G(r, 3, v[3], v[7], v[11], v[15], m); \
G(r, 4, v[0], v[5], v[10], v[15], m); \
G(r, 5, v[1], v[6], v[11], v[12], m); \
G(r, 6, v[2], v[7], v[ 8], v[13], m); \
G(r, 7, v[3], v[4], v[ 9], v[14], m);
// simplified for the last round
__device__ __forceinline__
static void H(const int r, const int i, uint64_t &a, uint64_t &b, uint64_t &c, uint64_t &d, uint64_t const m[16])
{
a = a + b + m[ blake2b_sigma[r][2*i] ];
((uint2*)&d)[0] = SWAPUINT2( ((uint2*)&d)[0] ^ ((uint2*)&a)[0] );
c = c + d;
((uint2*)&b)[0] = ROR24( ((uint2*)&b)[0] ^ ((uint2*)&c)[0] );
a = a + b + m[ blake2b_sigma[r][2*i+1] ];
((uint2*)&d)[0] = ROR16( ((uint2*)&d)[0] ^ ((uint2*)&a)[0] );
c = c + d;
}
// we only check v[0] and v[8]
#define ROUND_F(r) \
G(r, 0, v[0], v[4], v[ 8], v[12], m); \
G(r, 1, v[1], v[5], v[ 9], v[13], m); \
G(r, 2, v[2], v[6], v[10], v[14], m); \
G(r, 3, v[3], v[7], v[11], v[15], m); \
G(r, 4, v[0], v[5], v[10], v[15], m); \
G(r, 5, v[1], v[6], v[11], v[12], m); \
H(r, 6, v[2], v[7], v[ 8], v[13], m);
__global__
//__launch_bounds__(128, 8) /* to force 64 regs */
void blake2b_gpu_hash(const uint32_t threads, const uint32_t startNonce, uint32_t *resNonce, const uint2 target2)
{
const uint32_t nonce = (blockDim.x * blockIdx.x + threadIdx.x) + startNonce;
__shared__ uint64_t s_target;
if (!threadIdx.x) s_target = devectorize(target2);
uint64_t m[16];
m[0] = d_data[0];
m[1] = d_data[1];
m[2] = d_data[2];
m[3] = d_data[3];
m[4] = d_data[4] | nonce;
m[5] = d_data[5];
m[6] = d_data[6];
m[7] = d_data[7];
m[8] = d_data[8];
m[9] = d_data[9];
m[10] = m[11] = 0;
m[12] = m[13] = m[14] = m[15] = 0;
uint64_t v[16] = {
0x6a09e667f2bdc928, 0xbb67ae8584caa73b, 0x3c6ef372fe94f82b, 0xa54ff53a5f1d36f1,
0x510e527fade682d1, 0x9b05688c2b3e6c1f, 0x1f83d9abfb41bd6b, 0x5be0cd19137e2179,
0x6a09e667f3bcc908, 0xbb67ae8584caa73b, 0x3c6ef372fe94f82b, 0xa54ff53a5f1d36f1,
0x510e527fade68281, 0x9b05688c2b3e6c1f, 0xe07c265404be4294, 0x5be0cd19137e2179
};
ROUND( 0 );
ROUND( 1 );
ROUND( 2 );
ROUND( 3 );
ROUND( 4 );
ROUND( 5 );
ROUND( 6 );
ROUND( 7 );
ROUND( 8 );
ROUND( 9 );
ROUND( 10 );
ROUND_F( 11 );
uint64_t h64 = cuda_swab64(0x6a09e667f2bdc928 ^ v[0] ^ v[8]);
if (h64 <= s_target) {
resNonce[1] = resNonce[0];
resNonce[0] = nonce;
s_target = h64;
}
// if (!nonce) printf("%016lx ", s_target);
}
__host__
uint32_t blake2b_hash_cuda(const int thr_id, const uint32_t threads, const uint32_t startNonce, const uint2 target2, uint32_t &secNonce)
{
uint32_t resNonces[NBN] = { UINT32_MAX, UINT32_MAX };
uint32_t result = UINT32_MAX;
dim3 grid((threads + TPB-1)/TPB);
dim3 block(TPB);
/* Check error on Ctrl+C or kill to prevent segfaults on exit */
if (cudaMemset(d_resNonces[thr_id], 0xff, NBN*sizeof(uint32_t)) != cudaSuccess)
return result;
blake2b_gpu_hash <<<grid, block, 8>>> (threads, startNonce, d_resNonces[thr_id], target2);
cudaThreadSynchronize();
if (cudaSuccess == cudaMemcpy(resNonces, d_resNonces[thr_id], NBN*sizeof(uint32_t), cudaMemcpyDeviceToHost)) {
result = resNonces[0];
secNonce = resNonces[1];
if (secNonce == result) secNonce = UINT32_MAX;
}
return result;
}
__host__
void blake2b_setBlock(uint32_t *data)
{
CUDA_SAFE_CALL(cudaMemcpyToSymbol(d_data, data, 80, 0, cudaMemcpyHostToDevice));
}
static bool init[MAX_GPUS] = { 0 };
int scanhash_sia(int thr_id, struct work *work, uint32_t max_nonce, unsigned long *hashes_done)
{
uint32_t _ALIGN(A) hash[8];
uint32_t _ALIGN(A) vhashcpu[8];
uint32_t _ALIGN(A) inputdata[20];
uint32_t *pdata = work->data;
uint32_t *ptarget = work->target;
const uint32_t Htarg = ptarget[7];
const uint32_t first_nonce = pdata[8];
int dev_id = device_map[thr_id];
int intensity = (device_sm[dev_id] >= 500 && !is_windows()) ? 28 : 25;
if (device_sm[dev_id] >= 520 && is_windows()) intensity = 26;
if (device_sm[dev_id] < 350) intensity = 22;
uint32_t throughput = cuda_default_throughput(thr_id, 1U << intensity);
if (init[thr_id]) throughput = min(throughput, max_nonce - first_nonce);
if (!init[thr_id])
{
cudaSetDevice(dev_id);
if (opt_cudaschedule == -1 && gpu_threads == 1) {
cudaDeviceReset();
// reduce cpu usage (linux)
cudaSetDeviceFlags(cudaDeviceScheduleBlockingSync);
CUDA_LOG_ERROR();
}
gpulog(LOG_INFO, thr_id, "Intensity set to %g, %u cuda threads", throughput2intensity(throughput), throughput);
CUDA_CALL_OR_RET_X(cudaMalloc(&d_resNonces[thr_id], NBN * sizeof(uint32_t)), -1);
init[thr_id] = true;
}
memcpy(inputdata, pdata, 80);
inputdata[11] = 0; // nbits
const uint2 target = make_uint2(ptarget[6], ptarget[7]);
blake2b_setBlock(inputdata);
do {
work->nonces[0] = blake2b_hash_cuda(thr_id, throughput, pdata[8], target, work->nonces[1]);
*hashes_done = pdata[8] - first_nonce + throughput;
if (work->nonces[0] != UINT32_MAX)
{
work->valid_nonces = 0;
inputdata[8] = work->nonces[0];
blake2b_hash(hash, inputdata);
if (swab32(hash[0]) <= Htarg) {
// sia hash target is reversed (start of hash)
swab256(vhashcpu, hash);
if (fulltest(vhashcpu, ptarget)) {
work_set_target_ratio(work, vhashcpu);
work->valid_nonces++;
pdata[8] = work->nonces[0] + 1;
}
} else {
gpu_increment_reject(thr_id);
}
if (work->nonces[1] != UINT32_MAX) {
inputdata[8] = work->nonces[1];
blake2b_hash(hash, inputdata);
if (swab32(hash[0]) <= Htarg) {
swab256(vhashcpu, hash);
if (fulltest(vhashcpu, ptarget)) {
if (bn_hash_target_ratio(vhashcpu, ptarget) > work->shareratio[0]) {
work->sharediff[1] = work->sharediff[0];
work->shareratio[1] = work->shareratio[0];
xchg(work->nonces[1], work->nonces[0]);
work_set_target_ratio(work, vhashcpu);
} else {
bn_set_target_ratio(work, vhashcpu, 1);
}
work->valid_nonces++;
pdata[8] = work->nonces[1] + 1;
}
} else {
gpu_increment_reject(thr_id);
}
}
if (work->valid_nonces) {
return work->valid_nonces;
}
}
if ((uint64_t) throughput + pdata[8] >= max_nonce) {
pdata[8] = max_nonce;
break;
}
pdata[8] += throughput;
} while (!work_restart[thr_id].restart);
*hashes_done = pdata[8] - first_nonce;
return 0;
}
// cleanup
extern "C" void free_sia(int thr_id)
{
if (!init[thr_id])
return;
cudaThreadSynchronize();
cudaFree(d_resNonces[thr_id]);
init[thr_id] = false;
cudaDeviceSynchronize();
}