When I run sampleMNIST which was built successfully on my notebook I got a core dumped as follows.
ERROR: createConstants (243) - Cask Error in ../builder/caskConvolutionTraits.cpp: 0 (initDeviceReservedSpace) ERROR: createConstants (243) - Cask Error in ../builder/caskConvolutionTraits.cpp: 0 (initDeviceReservedSpace) sample_mnist: sampleMNIST.cpp:64: void caffeToGIEModel(const string&, const string&, const std::vector<std::__cxx11::basic_string<char> >&, unsigned int, nvinfer1::IHostMemory*&): Assertion `engine' failed. Aborted (core dumped)
Unfortunately, I got the same core dumped when I run other samples.
However samples works on my GTX1070.
Is TensorRT incompatible with my notebook’s GPU?
My notebook’s GPU information:
Device 0: "GeForce 940MX" CUDA Driver Version / Runtime Version 9.1 / 9.0 CUDA Capability Major/Minor version number: 5.0 Total amount of global memory: 2004 MBytes (2101870592 bytes) ( 3) Multiprocessors, (128) CUDA Cores/MP: 384 CUDA Cores GPU Max Clock rate: 1189 MHz (1.19 GHz) Memory Clock rate: 2505 Mhz Memory Bus Width: 64-bit L2 Cache Size: 1048576 bytes Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096) Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 2048 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 1 copy engine(s) Run time limit on kernels: No Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Supports Cooperative Kernel Launch: No Supports MultiDevice Co-op Kernel Launch: No Device PCI Domain ID / Bus ID / location ID: 0 / 2 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.1, CUDA Runtime Version = 9.0, NumDevs = 1 Result = PASS