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authorpsychocrypt <psychocrypt@users.noreply.github.com>2017-11-14 21:18:30 +0100
committerpsychocrypt <psychocrypt@users.noreply.github.com>2017-11-15 16:26:58 +0100
commit0659458523671d53e4eddd940ade8ac9f72b1bbe (patch)
tree94156c9e10ed97cd80aeb39fa9e3439020b74394 /xmrstak/backend/nvidia
parent288363814fb091ccfc452f0408bfa53727fc30c0 (diff)
downloadxmr-stak-0659458523671d53e4eddd940ade8ac9f72b1bbe.zip
xmr-stak-0659458523671d53e4eddd940ade8ac9f72b1bbe.tar.gz
fix wrong memory detection
Free and total memory is only evaluated on the first device. To detect the gpu memory the gpu must be selected. - create context on the gpu before the memory is checked - add smx to the auto detection - change the result code of `cuda_get_deviceinfo()`
Diffstat (limited to 'xmrstak/backend/nvidia')
-rw-r--r--xmrstak/backend/nvidia/autoAdjust.hpp13
-rw-r--r--xmrstak/backend/nvidia/nvcc_code/cuda_extra.cu43
2 files changed, 43 insertions, 13 deletions
diff --git a/xmrstak/backend/nvidia/autoAdjust.hpp b/xmrstak/backend/nvidia/autoAdjust.hpp
index bf04518..d36a46a 100644
--- a/xmrstak/backend/nvidia/autoAdjust.hpp
+++ b/xmrstak/backend/nvidia/autoAdjust.hpp
@@ -60,17 +60,15 @@ public:
ctx.device_bfactor = 6;
ctx.device_bsleep = 25;
#endif
- if( cuda_get_deviceinfo(&ctx) != 1 )
- {
- printer::inst()->print_msg(L0, "Setup failed for GPU %d. Exitting.\n", i);
- std::exit(0);
- }
- nvidCtxVec.push_back(ctx);
+ if(cuda_get_deviceinfo(&ctx) == 0)
+ nvidCtxVec.push_back(ctx);
+ else
+ printer::inst()->print_msg(L0, "WARNING: NVIDIA setup failed for GPU %d.\n", i);
}
generateThreadConfig();
- return true;
+ return true;
}
@@ -94,6 +92,7 @@ private:
{
conf += std::string(" // gpu: ") + ctx.name + " architecture: " + std::to_string(ctx.device_arch[0] * 10 + ctx.device_arch[1]) + "\n";
conf += std::string(" // memory: ") + std::to_string(ctx.free_device_memory / byte2mib) + "/" + std::to_string(ctx.total_device_memory / byte2mib) + " MiB\n";
+ conf += std::string(" // smx: ") + std::to_string(ctx.device_mpcount) + "\n";
conf += std::string(" { \"index\" : ") + std::to_string(ctx.device_id) + ",\n" +
" \"threads\" : " + std::to_string(ctx.device_threads) + ", \"blocks\" : " + std::to_string(ctx.device_blocks) + ",\n" +
" \"bfactor\" : " + std::to_string(ctx.device_bfactor) + ", \"bsleep\" : " + std::to_string(ctx.device_bsleep) + ",\n" +
diff --git a/xmrstak/backend/nvidia/nvcc_code/cuda_extra.cu b/xmrstak/backend/nvidia/nvcc_code/cuda_extra.cu
index e18532f..61d45ed 100644
--- a/xmrstak/backend/nvidia/nvcc_code/cuda_extra.cu
+++ b/xmrstak/backend/nvidia/nvcc_code/cuda_extra.cu
@@ -270,6 +270,14 @@ extern "C" int cuda_get_devicecount( int* deviceCount)
return 1;
}
+/** get device information
+ *
+ * @return 0 = all OK,
+ * 1 = something went wrong,
+ * 2 = gpu cannot be selected,
+ * 3 = context cannot be created
+ * 4 = not enough memory
+ */
extern "C" int cuda_get_deviceinfo(nvid_ctx* ctx)
{
cudaError_t err;
@@ -279,25 +287,25 @@ extern "C" int cuda_get_deviceinfo(nvid_ctx* ctx)
if(err != cudaSuccess)
{
printf("Unable to query CUDA driver version! Is an nVidia driver installed?\n");
- return 0;
+ return 1;
}
if(version < CUDART_VERSION)
{
printf("Driver does not support CUDA %d.%d API! Update your nVidia driver!\n", CUDART_VERSION / 1000, (CUDART_VERSION % 1000) / 10);
- return 0;
+ return 1;
}
int GPU_N;
if(cuda_get_devicecount(&GPU_N) == 0)
{
- return 0;
+ return 1;
}
if(ctx->device_id >= GPU_N)
{
printf("Invalid device ID!\n");
- return 0;
+ return 1;
}
cudaDeviceProp props;
@@ -305,7 +313,7 @@ extern "C" int cuda_get_deviceinfo(nvid_ctx* ctx)
if(err != cudaSuccess)
{
printf("\nGPU %d: %s\n%s line %d\n", ctx->device_id, cudaGetErrorString(err), __FILE__, __LINE__);
- return 0;
+ return 1;
}
ctx->device_name = strdup(props.name);
@@ -347,9 +355,31 @@ extern "C" int cuda_get_deviceinfo(nvid_ctx* ctx)
maxMemUsage = size_t(1024u) * byteToMiB;
}
+ int* tmp;
+ cudaError_t err;
+ // a device must be selected to get the right memory usage later on
+ err = cudaSetDevice(ctx->device_id);
+ if(err != cudaSuccess)
+ {
+ printf("WARNING: NVIDIA GPU %d: cannot be selected.\n", ctx->device_id);
+ return 2;
+ }
+ // trigger that a context on the gpu will be allocated
+ err = cudaMalloc(&tmp, 256);
+ if(err != cudaSuccess)
+ {
+ printf("WARNING: NVIDIA GPU %d: context cannot be created.\n", ctx->device_id);
+ return 3;
+ }
+
+
size_t freeMemory = 0;
size_t totalMemory = 0;
CUDA_CHECK(ctx->device_id, cudaMemGetInfo(&freeMemory, &totalMemory));
+
+ cudaFree(tmp);
+ // delete created context on the gpu
+ cudaDeviceReset();
ctx->total_device_memory = totalMemory;
ctx->free_device_memory = freeMemory;
@@ -379,6 +409,7 @@ extern "C" int cuda_get_deviceinfo(nvid_ctx* ctx)
printf("WARNING: NVIDIA GPU %d: already %s MiB memory in use, skip GPU.\n",
ctx->device_id,
std::to_string(usedMem/byteToMiB).c_str());
+ return 4;
}
else
maxMemUsage -= usedMem;
@@ -404,5 +435,5 @@ extern "C" int cuda_get_deviceinfo(nvid_ctx* ctx)
}
- return 1;
+ return 0;
}
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