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author | psychocrypt <psychocrypt@users.noreply.github.com> | 2017-11-14 21:18:30 +0100 |
---|---|---|
committer | psychocrypt <psychocrypt@users.noreply.github.com> | 2017-11-15 16:26:58 +0100 |
commit | 0659458523671d53e4eddd940ade8ac9f72b1bbe (patch) | |
tree | 94156c9e10ed97cd80aeb39fa9e3439020b74394 /xmrstak/backend/nvidia | |
parent | 288363814fb091ccfc452f0408bfa53727fc30c0 (diff) | |
download | xmr-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.hpp | 13 | ||||
-rw-r--r-- | xmrstak/backend/nvidia/nvcc_code/cuda_extra.cu | 43 |
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; } |