The main role of the project: CUDA 8.0/TensorRT's usage(each test code gives the implementation of C ++ and CUDA, respectively, and gives the calculation time for each method)
Note: Clone this repository to E:/GitCode/

• CUDA 8.0 test code
  • simple
    • vector add: C = A + B
    • matrix multiplication: C = A * B
    • dot product
    • Julia
    • ripple
    • green ball
    • ray tracking
    • heat conduction
    • calculate histogram
    • streams' usage
  • layer(approximate)
    • channel normalize(mean/standard deviation)
    • reverse
    • prior_vbox
  • image process
    • bgr to gray
    • bgr to bgr565
    • gray image histogram equalization(only C++ implementation)
    • gray image edge detection: Laplacian(only C++ implementation)
• TensorRT 2.1.2 test code
  • MNIST
  • MNIST API(use api produce network)
  • GoogleNet
  • CharRNN
  • Plugin(add a custom layer)
  • MNIST Infer(serialize TensorRT model)

The project support platform:

• windows10 64 bits: It can be directly build with VS2013 in windows10 64bits.
• Linux:
  • CUDA supports cmake build(file position: prj/linux_cuda_cmake)
  • TensorRT support cmake build(file position: prj/linux_tensorrt_cmake)

Screenshot:

Blog: fengbingchun