TensorRT-4.0.0.3 samples cause core dumped

AI & Data Science Deep Learning (Training & Inference) TensorRT
1

Hi,

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
2

I have the same issue on a Laptop with a Quadro M2000M using the driver version 384.81. The same driver version works fine on a GeForce GTX 1080.

3

I too tried running TensorRT 4.0 samples on my Dell laptop(quadro M1200) and see the same error:

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:63: void caffeToGIEModel(const string&, const string&, const std::vector<std::__cxx11::basic_string >&, unsigned int, nvinfer1::IHostMemory*&): Assertion `engine’ failed.
Aborted (core dumped)

My laptop config:

Detected 1 CUDA Capable device(s)

Device 0: “Quadro M1200”
CUDA Driver Version / Runtime Version 9.1 / 9.0
CUDA Capability Major/Minor version number: 5.0
Total amount of global memory: 4044 MBytes (4240179200 bytes)
( 5) Multiprocessors, (128) CUDA Cores/MP: 640 CUDA Cores
GPU Max Clock rate: 1148 MHz (1.15 GHz)
Memory Clock rate: 2505 Mhz
Memory Bus Width: 128-bit
L2 Cache Size: 2097152 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: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yess
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 / 1 / 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

Anyone who knows the reason/ solution?