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x12: apply echo512 optimised kernel on recent cards

pull/5/head
Tanguy Pruvot 7 years ago
parent
commit
16ebe53b72
  1. 18
      x12/x12.cu
  2. 2
      x16/x16r.cu
  3. 2
      x16/x16s.cu

18
x12/x12.cu

@ -22,6 +22,8 @@ extern "C" { @@ -22,6 +22,8 @@ extern "C" {
static uint32_t *d_hash[MAX_GPUS];
extern void x16_echo512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t *d_hash);
extern void x13_hamsi512_cpu_init(int thr_id, uint32_t threads);
extern void x13_hamsi512_cpu_hash_64(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *d_nonceVector, uint32_t *d_hash, int order);
@ -96,13 +98,15 @@ extern "C" void x12hash(void *output, const void *input) @@ -96,13 +98,15 @@ extern "C" void x12hash(void *output, const void *input)
}
static bool init[MAX_GPUS] = { 0 };
static bool use_compat_kernels[MAX_GPUS] = { 0 };
extern "C" int scanhash_x12(int thr_id, struct work* work, uint32_t max_nonce, unsigned long *hashes_done)
{
uint32_t *pdata = work->data;
uint32_t *ptarget = work->target;
const uint32_t first_nonce = pdata[19];
int intensity = (device_sm[device_map[thr_id]] > 500 && !is_windows()) ? 20 : 19;
const int dev_id = device_map[thr_id];
int intensity = (device_sm[dev_id] > 500 && !is_windows()) ? 20 : 19;
uint32_t throughput = cuda_default_throughput(thr_id, 1 << intensity); // 19=256*256*8;
//if (init[thr_id]) throughput = min(throughput, max_nonce - first_nonce);
@ -111,7 +115,7 @@ extern "C" int scanhash_x12(int thr_id, struct work* work, uint32_t max_nonce, u @@ -111,7 +115,7 @@ extern "C" int scanhash_x12(int thr_id, struct work* work, uint32_t max_nonce, u
if (!init[thr_id])
{
cudaSetDevice(device_map[thr_id]);
cudaSetDevice(dev_id);
if (opt_cudaschedule == -1 && gpu_threads == 1) {
cudaDeviceReset();
// reduce cpu usage
@ -120,13 +124,17 @@ extern "C" int scanhash_x12(int thr_id, struct work* work, uint32_t max_nonce, u @@ -120,13 +124,17 @@ extern "C" int scanhash_x12(int thr_id, struct work* work, uint32_t max_nonce, u
}
gpulog(LOG_INFO, thr_id, "Intensity set to %g, %u cuda threads", throughput2intensity(throughput), throughput);
cuda_get_arch(thr_id);
use_compat_kernels[thr_id] = (cuda_arch[dev_id] < 500);
if (use_compat_kernels[thr_id])
x11_echo512_cpu_init(thr_id, throughput);
quark_blake512_cpu_init(thr_id, throughput);
x11_luffaCubehash512_cpu_init(thr_id, throughput);
x11_shavite512_cpu_init(thr_id, throughput);
if (x11_simd512_cpu_init(thr_id, throughput) != 0) {
return 0;
}
x11_echo512_cpu_init(thr_id, throughput);
quark_groestl512_cpu_init(thr_id, throughput);
quark_skein512_cpu_init(thr_id, throughput);
quark_bmw512_cpu_init(thr_id, throughput);
@ -156,7 +164,11 @@ extern "C" int scanhash_x12(int thr_id, struct work* work, uint32_t max_nonce, u @@ -156,7 +164,11 @@ extern "C" int scanhash_x12(int thr_id, struct work* work, uint32_t max_nonce, u
x11_luffaCubehash512_cpu_hash_64(thr_id, throughput, d_hash[thr_id], order++);
x11_shavite512_cpu_hash_64(thr_id, throughput, pdata[19], NULL, d_hash[thr_id], order++);
x11_simd512_cpu_hash_64(thr_id, throughput, pdata[19], NULL, d_hash[thr_id], order++);
if (use_compat_kernels[thr_id])
x11_echo512_cpu_hash_64(thr_id, throughput, pdata[19], NULL, d_hash[thr_id], order++);
else {
x16_echo512_cpu_hash_64(thr_id, throughput, d_hash[thr_id]); order++;
}
quark_groestl512_cpu_hash_64(thr_id, throughput, pdata[19], NULL, d_hash[thr_id], order++);
quark_skein512_cpu_hash_64(thr_id, throughput, pdata[19], NULL, d_hash[thr_id], order++);
quark_jh512_cpu_hash_64(thr_id, throughput, pdata[19], NULL, d_hash[thr_id], order++);

2
x16/x16r.cu

@ -250,7 +250,7 @@ extern "C" int scanhash_x16r(int thr_id, struct work* work, uint32_t max_nonce, @@ -250,7 +250,7 @@ extern "C" int scanhash_x16r(int thr_id, struct work* work, uint32_t max_nonce,
if (!init[thr_id])
{
cudaSetDevice(device_map[thr_id]);
cudaSetDevice(dev_id);
if (opt_cudaschedule == -1 && gpu_threads == 1) {
cudaDeviceReset();
// reduce cpu usage

2
x16/x16s.cu

@ -248,7 +248,7 @@ extern "C" int scanhash_x16s(int thr_id, struct work* work, uint32_t max_nonce, @@ -248,7 +248,7 @@ extern "C" int scanhash_x16s(int thr_id, struct work* work, uint32_t max_nonce,
if (!init[thr_id])
{
cudaSetDevice(device_map[thr_id]);
cudaSetDevice(dev_id);
if (opt_cudaschedule == -1 && gpu_threads == 1) {
cudaDeviceReset();
// reduce cpu usage

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