![]() Model name: Intel(R) Xeon(R) Platinum 8259CL CPU 2. usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.7.0Īddress sizes: 46 bits physical, 48 bits virtual Targets Created: CUDA::cudart CUDA::cudartstatic CUDA Driver Library The CUDA Driver library (cuda) are used by applications that use calls such as cuMemAlloc, and cuMemFree. usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.7.0 The CUDA Runtime library (cudart) are what most applications will typically need to link against to make any calls such as cudaMalloc, and cudaFree. GPU models and configuration: GPU 0: Tesla T4ĬuDNN version: Probably one of the following: : ai.: ai.: CUDA error: an illegal memory access was encounteredĬUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.įor debugging consider passing CUDA_LAUNCH_BLOCKING=1.Ĭompile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.Īt .report(FutureTask.java:122) ~Īt .get(FutureTask.java:191) ~Īt ai.(MultithreadedBenchmark.java:110) Īt ai.(AbstractBenchmark.java:125) Īt ai.(Benchmark.java:56) Ĭaused by: ai.: ai.: CUDA error: an illegal memory access was encounteredĪt ai.(Predictor.java:191) ~Īt ai.(Predictor.java:128) ~Īt ai.$PredictorCallable.call(MultithreadedBenchmark.java:179) ~Īt ai.$PredictorCallable.call(MultithreadedBenchmark.java:140) ~Īt .run(FutureTask.java:264) ~Īt .runWorker(ThreadPoolExecutor.java:1128) ~Īt $n(ThreadPoolExecutor.java:628) ~Īt (Thread.java:829) ~Ĭaused by: ai.: CUDA error: an illegal memory access was encounteredĪt ai.torchTo(Native Method) ~Īt ai.to(JniUtils.java:324) ~Īt ai.toDevice(PtNDArray.java:165) ~Īt ai.getByteBuffer(JniUtils.java:1635) ~Īt ai.toByteBuffer(PtNDArray.java:221) ~Īt ai.$BenchmarkTranslator.processOutput(AbstractBenchmark.java:316) ~Īt ai.$BenchmarkTranslator.processOutput(AbstractBenchmark.java:293) ~Īt ai.(Predictor.java:172) ~ Model traced_resnet18 loaded in: 2015.853 ms. ![]() Multithreading inference with 20 threads. PyTorch graph executor optimizer is enabled, this may impact your inference latency and throughput. Note: The enable_language() and project() command's languages apply to all CMake directories below them, so there is no need to call enable_language() again in sub-directories.Export export export. It seems like it can find CUDA alright, but it cannot locate CUBLAS. Project(cmake_and_cuda LANGUAGES CXX CUDA) CUDA Quantum provides CMake configuration files that allow downstream application developers to create hybrid quantum-classical source code and build it. Problem with using Cmake with CUDA Accelerated Computing GPU-Accelerated Libraries quang-ha March 12, 2020, 5:45pm 1 I am having some weird problems with CMake and CUDA. Or, simply enable all the languages your CMake project needs in the project() command itself: cmake_minimum_required(VERSION 3.8 FATAL_ERROR) cmake_minimum_required(VERSION 3.8 FATAL_ERROR) ![]() So, you should re-arrange your CMake file to place the enable_language() call after the project() call, so that CMake has initialized its internal variables properly. The enable_language() is a light-weight call, typically used to enable further languages later on in the CMake project. You should typically place the first project() command directly after the cmake_minimum_required() call, to avoid such errors. Without specifying any language in the project() command, the defaults ( C and CXX) are enabled: # Initialize for C and C++ languages. As such, it sets the languages that your CMake project will be using. Following upon how to perform code linking between CUDA and C++ (here at. The project() command will initialize many CMake variables concerning your system and compiler. I guess this is due to a cudart problem, so I added set(CMAKE_CXX_FLAGS "$ -lcudart") but I could not resolve this issue. in the build folder in the project, the following error message are printed: CMake Error: Error required internal CMake variable not set, cmake may not be built correctly.ĬMake Error: Error required internal CMake variable not set, cmake may not be built correctly. PROPERTIES CUDA_SEPARABLE_COMPILATION ON) Target_compile_features(kernels PUBLIC cxx_std_11) # PROPERTY CUDA_SEPARABLE_COMPILATION ON) I am trying to add CUDA functions in existing C++ project which uses CMake.įor example, main.cpp looks like this: #include Īnd kernels/test.cu looks like: #include "test.cuh"Īnd kernels/test.cuh looks like: #ifndef TEST_CUH_Īnd I use following codes for CMakeLists.txt: =Ĭmake_minimum_required(VERSION 3.8 FATAL_ERROR)
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