Merge pull request #10 from turtlecoin/dev

Dev
This commit is contained in:
Haifa Bogdan Adnan 2019-09-06 20:47:14 +03:00 committed by GitHub
commit 4e9134d829
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GPG key ID: 4AEE18F83AFDEB23
6 changed files with 141 additions and 61 deletions

View file

@ -394,7 +394,13 @@ if(WITH_CUDA)
set(
CUDA_NVCC_FLAGS
${CUDA_NVCC_FLAGS};
-O3 -arch=compute_35 -std=c++11
-O3 -std=c++11 --ptxas-options=-v
-gencode=arch=compute_75,code="sm_75,compute_75"
-gencode=arch=compute_61,code="sm_61,compute_61"
-gencode=arch=compute_52,code="sm_52,compute_52"
-gencode=arch=compute_50,code="sm_50,compute_50"
-gencode=arch=compute_35,code="sm_35,compute_35"
-gencode=arch=compute_30,code="sm_30,compute_30"
)
cuda_add_library(cuda_hasher MODULE ${SOURCE_CUDA_HASHER})
set_target_properties(cuda_hasher

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@ -86,7 +86,7 @@ void xmrig::Config::getJSON(rapidjson::Document &doc) const
if(cpuOptimization().isNull() || cpuOptimization().isEmpty())
doc.AddMember("cpu-optimization", kNullType, allocator);
else
doc.AddMember("cpu-optimization", StringRef(cpuOptimization().data()), allocator);
doc.AddMember("cpu-optimization", cpuOptimization().toJSON(doc), allocator);
if (cpuAffinity() != -1L) {
snprintf(affinity_tmp, sizeof(affinity_tmp) - 1, "0x%" PRIX64, cpuAffinity());

View file

@ -53,6 +53,8 @@ bool CudaHasher::initialize(xmrig::Algo algorithm, xmrig::Variant variant) {
}
vector<CudaDeviceInfo *> CudaHasher::queryCudaDevices(cudaError_t &error, string &error_message) {
cudaSetDeviceFlags(cudaDeviceBlockingSync);
vector<CudaDeviceInfo *> devices;
int devCount = 0;
error = cudaGetDeviceCount(&devCount);

View file

@ -288,6 +288,8 @@ __device__ __forceinline__ void blake2b_final(uint32_t *out, int out_len, uint64
blake2b_compress(h, (uint64_t*)buf, 0xFFFFFFFFFFFFFFFF, thr_id);
__syncthreads();
uint32_t *cursor_in = (uint32_t *)h;
cursor_out = out;

View file

@ -19,57 +19,95 @@
#include "blake2b.cu"
#define COMPUTE \
asm ("{" \
".reg .u32 s1, s2, s3, s4;\n\t" \
"mul.lo.u32 s3, %0, %2;\n\t" \
"mul.hi.u32 s4, %0, %2;\n\t" \
"add.cc.u32 s3, s3, s3;\n\t" \
"addc.u32 s4, s4, s4;\n\t" \
"add.cc.u32 s1, %0, %2;\n\t" \
"addc.u32 s2, %1, %3;\n\t" \
"add.cc.u32 %0, s1, s3;\n\t" \
"addc.u32 %1, s2, s4;\n\t" \
"xor.b32 s1, %0, %6;\n\t" \
"xor.b32 %6, %1, %7;\n\t" \
"mov.b32 %7, s1;\n\t" \
"mul.lo.u32 s3, %4, %6;\n\t" \
"mul.hi.u32 s4, %4, %6;\n\t" \
"add.cc.u32 s3, s3, s3;\n\t" \
"addc.u32 s4, s4, s4;\n\t" \
"add.cc.u32 s1, %4, %6;\n\t" \
"addc.u32 s2, %5, %7;\n\t" \
"add.cc.u32 %4, s1, s3;\n\t" \
"addc.u32 %5, s2, s4;\n\t" \
"xor.b32 s3, %2, %4;\n\t" \
"xor.b32 s4, %3, %5;\n\t" \
"shf.r.wrap.b32 %3, s4, s3, 24;\n\t" \
"shf.r.wrap.b32 %2, s3, s4, 24;\n\t" \
"mul.lo.u32 s3, %0, %2;\n\t" \
"mul.hi.u32 s4, %0, %2;\n\t" \
"add.cc.u32 s3, s3, s3;\n\t" \
"addc.u32 s4, s4, s4;\n\t" \
"add.cc.u32 s1, %0, %2;\n\t" \
"addc.u32 s2, %1, %3;\n\t" \
"add.cc.u32 %0, s1, s3;\n\t" \
"addc.u32 %1, s2, s4;\n\t" \
"xor.b32 s3, %0, %6;\n\t" \
"xor.b32 s4, %1, %7;\n\t" \
"shf.r.wrap.b32 %7, s4, s3, 16;\n\t" \
"shf.r.wrap.b32 %6, s3, s4, 16;\n\t" \
"mul.lo.u32 s3, %4, %6;\n\t" \
"mul.hi.u32 s4, %4, %6;\n\t" \
"add.cc.u32 s3, s3, s3;\n\t" \
"addc.u32 s4, s4, s4;\n\t" \
"add.cc.u32 s1, %4, %6;\n\t" \
"addc.u32 s2, %5, %7;\n\t" \
"add.cc.u32 %4, s1, s3;\n\t" \
"addc.u32 %5, s2, s4;\n\t" \
"xor.b32 s3, %2, %4;\n\t" \
"xor.b32 s4, %3, %5;\n\t" \
"shf.r.wrap.b32 %3, s3, s4, 31;\n\t" \
"shf.r.wrap.b32 %2, s4, s3, 31;\n\t" \
"}" : "+r"(tmp_a.x), "+r"(tmp_a.y), "+r"(tmp_a.z), "+r"(tmp_a.w), "+r"(tmp_b.x), "+r"(tmp_b.y), "+r"(tmp_b.z), "+r"(tmp_b.w));
#ifndef __CUDA_ARCH__
#define __CUDA_ARCH__ 0
#endif
#if (__CUDA_ARCH__ >= 350)
#define COMPUTE \
asm ("{" \
".reg .u32 s1, s2, s3, s4;\n\t" \
"mul.lo.u32 s3, %0, %2;\n\t" \
"mul.hi.u32 s4, %0, %2;\n\t" \
"add.cc.u32 s3, s3, s3;\n\t" \
"addc.u32 s4, s4, s4;\n\t" \
"add.cc.u32 s1, %0, %2;\n\t" \
"addc.u32 s2, %1, %3;\n\t" \
"add.cc.u32 %0, s1, s3;\n\t" \
"addc.u32 %1, s2, s4;\n\t" \
"xor.b32 s1, %0, %6;\n\t" \
"xor.b32 %6, %1, %7;\n\t" \
"mov.b32 %7, s1;\n\t" \
"mul.lo.u32 s3, %4, %6;\n\t" \
"mul.hi.u32 s4, %4, %6;\n\t" \
"add.cc.u32 s3, s3, s3;\n\t" \
"addc.u32 s4, s4, s4;\n\t" \
"add.cc.u32 s1, %4, %6;\n\t" \
"addc.u32 s2, %5, %7;\n\t" \
"add.cc.u32 %4, s1, s3;\n\t" \
"addc.u32 %5, s2, s4;\n\t" \
"xor.b32 s3, %2, %4;\n\t" \
"xor.b32 s4, %3, %5;\n\t" \
"shf.r.wrap.b32 %3, s4, s3, 24;\n\t" \
"shf.r.wrap.b32 %2, s3, s4, 24;\n\t" \
"mul.lo.u32 s3, %0, %2;\n\t" \
"mul.hi.u32 s4, %0, %2;\n\t" \
"add.cc.u32 s3, s3, s3;\n\t" \
"addc.u32 s4, s4, s4;\n\t" \
"add.cc.u32 s1, %0, %2;\n\t" \
"addc.u32 s2, %1, %3;\n\t" \
"add.cc.u32 %0, s1, s3;\n\t" \
"addc.u32 %1, s2, s4;\n\t" \
"xor.b32 s3, %0, %6;\n\t" \
"xor.b32 s4, %1, %7;\n\t" \
"shf.r.wrap.b32 %7, s4, s3, 16;\n\t" \
"shf.r.wrap.b32 %6, s3, s4, 16;\n\t" \
"mul.lo.u32 s3, %4, %6;\n\t" \
"mul.hi.u32 s4, %4, %6;\n\t" \
"add.cc.u32 s3, s3, s3;\n\t" \
"addc.u32 s4, s4, s4;\n\t" \
"add.cc.u32 s1, %4, %6;\n\t" \
"addc.u32 s2, %5, %7;\n\t" \
"add.cc.u32 %4, s1, s3;\n\t" \
"addc.u32 %5, s2, s4;\n\t" \
"xor.b32 s3, %2, %4;\n\t" \
"xor.b32 s4, %3, %5;\n\t" \
"shf.r.wrap.b32 %3, s3, s4, 31;\n\t" \
"shf.r.wrap.b32 %2, s4, s3, 31;\n\t" \
"}" : "+r"(tmp_a.x), "+r"(tmp_a.y), "+r"(tmp_a.z), "+r"(tmp_a.w), "+r"(tmp_b.x), "+r"(tmp_b.y), "+r"(tmp_b.z), "+r"(tmp_b.w));
#else
#define downsample(x, lo, hi) \
{ \
lo = (uint32_t)x; \
hi = (uint32_t)(x >> 32); \
}
#define upsample(lo, hi) (((uint64_t)(hi) << 32) | (uint64_t)(lo))
#define rotate(x, n) (((x) >> (64-n)) | ((x) << n))
#define fBlaMka(x, y) ((x) + (y) + 2 * upsample((uint32_t)(x) * (uint32_t)y, __umulhi((uint32_t)(x), (uint32_t)(y))))
#define COMPUTE \
{ \
uint64_t a64 = upsample(tmp_a.x, tmp_a.y); \
uint64_t b64 = upsample(tmp_a.z, tmp_a.w); \
uint64_t c64 = upsample(tmp_b.x, tmp_b.y); \
uint64_t d64 = upsample(tmp_b.z, tmp_b.w); \
a64 = fBlaMka(a64, b64); \
d64 = rotate(d64 ^ a64, 32); \
c64 = fBlaMka(c64, d64); \
b64 = rotate(b64 ^ c64, 40); \
a64 = fBlaMka(a64, b64); \
d64 = rotate(d64 ^ a64, 48); \
c64 = fBlaMka(c64, d64); \
b64 = rotate(b64 ^ c64, 1); \
downsample(a64, tmp_a.x, tmp_a.y); \
downsample(b64, tmp_a.z, tmp_a.w); \
downsample(c64, tmp_b.x, tmp_b.y); \
downsample(d64, tmp_b.z, tmp_b.w); \
}
#endif // __CUDA_ARCH__
#define G1(data) \
{ \
@ -1039,6 +1077,18 @@ void cuda_free(CudaDeviceInfo *device) {
cudaDeviceReset();
}
inline bool cudaCheckError(cudaError &err, string &errStr)
{
err = cudaGetLastError();
if ( cudaSuccess != err )
{
errStr = string("CUDA error: ") + cudaGetErrorString( err );
return false;
}
return true;
}
bool cuda_kernel_prehasher(void *memory, int threads, Argon2Profile *profile, void *user_data) {
CudaGpuMgmtThreadData *gpumgmt_thread = (CudaGpuMgmtThreadData *)user_data;
CudaDeviceInfo *device = gpumgmt_thread->device;
@ -1069,6 +1119,12 @@ bool cuda_kernel_prehasher(void *memory, int threads, Argon2Profile *profile, vo
profile->saltLen,
threads);
bool success = cudaCheckError(device->error, device->errorMessage);
if(!success) {
gpumgmt_thread->unlock();
return false;
}
return true;
}
@ -1098,7 +1154,13 @@ void *cuda_kernel_filler(int threads, Argon2Profile *profile, void *user_data) {
device->profileInfo.threads_per_chunk,
gpumgmt_thread->threadsIdx);
return (void *)1;
bool success = cudaCheckError(device->error, device->errorMessage);
if(!success) {
gpumgmt_thread->unlock();
return NULL;
}
return (void *)1;
}
bool cuda_kernel_posthasher(void *memory, int threads, Argon2Profile *profile, void *user_data) {
@ -1113,6 +1175,11 @@ bool cuda_kernel_posthasher(void *memory, int threads, Argon2Profile *profile, v
device->arguments.outMemory[gpumgmt_thread->threadId],
device->arguments.preseedMemory[gpumgmt_thread->threadId]);
if(!cudaCheckError(device->error, device->errorMessage)) {
gpumgmt_thread->unlock();
return false;
}
device->error = cudaMemcpyAsync(device->arguments.hostSeedMemory[gpumgmt_thread->threadId], device->arguments.hashMemory[gpumgmt_thread->threadId], threads * (xmrig::ARGON2_HASHLEN + 4), cudaMemcpyDeviceToHost, stream);
if (device->error != cudaSuccess) {
device->errorMessage = "Error reading gpu memory.";
@ -1120,13 +1187,16 @@ bool cuda_kernel_posthasher(void *memory, int threads, Argon2Profile *profile, v
return false;
}
while(cudaStreamQuery(stream) != cudaSuccess) {
this_thread::sleep_for(chrono::milliseconds(10));
continue;
}
cudaStreamSynchronize(stream);
bool success = cudaCheckError(device->error, device->errorMessage);
if(!success) {
gpumgmt_thread->unlock();
return false;
}
memcpy(memory, device->arguments.hostSeedMemory[gpumgmt_thread->threadId], threads * (xmrig::ARGON2_HASHLEN + 4));
gpumgmt_thread->unlock();
return memory;
return true;
}

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@ -28,7 +28,7 @@
#define APP_ID "ninjarig"
#define APP_NAME "NinjaRig"
#define APP_DESC "NinjaRig CPU/GPU miner"
#define APP_VERSION "1.0.1"
#define APP_VERSION "1.0.2"
//#define APP_DOMAIN "xmrig.com"
//#define APP_SITE "www.xmrig.com"
#define APP_COPYRIGHT "Copyright (C) 2019 Haifa Bogdan Adnan"
@ -36,7 +36,7 @@
#define APP_VER_MAJOR 1
#define APP_VER_MINOR 0
#define APP_VER_PATCH 1
#define APP_VER_PATCH 2
#ifdef _MSC_VER
# if (_MSC_VER >= 1920)