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ccminer/sia.cu
Tanguy Pruvot 9eead77027 diff: show by default, rework shares diff storage
This will allow later more gpu candidates.

Note: This is an unfinished work, we keep the previous behavior for now
To finish this, all algos solutions should be migrated and submitted nonces attributes stored.
Its required to handle the different share diff per nonce and fix the possible solved count error (if 1/2 nonces is solved).
2016-09-27 09:03:24 +02:00

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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);
//cudaDeviceSetCacheConfig(cudaFuncCachePreferL1);
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 {
uint32_t secNonce = UINT32_MAX;
uint32_t foundNonce = blake2b_hash_cuda(thr_id, throughput, pdata[8], target, secNonce);
*hashes_done = pdata[8] - first_nonce + throughput;
if (foundNonce != UINT32_MAX)
{
int res = 0;
inputdata[8] = foundNonce;
blake2b_hash(hash, inputdata);
if (swab32(hash[0]) <= Htarg) {
// sia hash target is reversed (start of hash)
swab256(vhashcpu, hash);
// applog_hex(vhashcpu, 32);
if (fulltest(vhashcpu, ptarget)) {
work_set_target_ratio(work, vhashcpu);
work->nonces[0] = foundNonce;
res ++;
}
}
if (secNonce != UINT32_MAX) {
inputdata[8] = secNonce;
blake2b_hash(hash, inputdata);
if (swab32(hash[0]) <= Htarg) {
if (opt_debug)
gpulog(LOG_BLUE, thr_id, "found second nonce %08x", secNonce);
swab256(vhashcpu, hash);
if (fulltest(vhashcpu, ptarget)) {
work->nonces[1] = secNonce;
if (bn_hash_target_ratio(vhashcpu, ptarget) > work->shareratio[0]) {
work_set_target_ratio(work, vhashcpu);
xchg(work->nonces[0], work->nonces[1]);
}
res++;
}
}
}
if (res) {
pdata[8] = max_nonce;
return res;
}
}
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();
}