100 DAYS OF GPU Course preview

MODULE 09 / Days 81-90

Libraries, Python and the ML bridge

All lessons
  1. 81
    cuBLAS and cuBLASLtHow do I call cuBLAS from C++ when my matrices are row major?
    run logged
  2. 82
    cuFFT, cuRAND, cuSPARSE and cuSOLVERWhich CUDA math library replaces the kernel I was about to write?
    run logged
  3. 83
    cuDNN with the graph APIHow do I call cuDNN's graph API for a Conv2D forward?
    run logged
  4. 84
    CUTLASS and CuTe layoutsWhat is CuTe, and does CUTLASS need an Ampere GPU?
    run logged
  5. 85
    CUDA from Python: cuda.core, CuPy, Numba and PyCUDAHow do I launch a CUDA kernel from Python?
    run logged
  6. 86
    Writing kernels in TritonHow do I write a CUDA kernel in Triton, and will it run on my GPU?
    lesson
  7. 87
    Custom PyTorch operatorsHow do I call my own CUDA kernel from PyTorch with a backward pass?
    run logged
  8. 88
    Profiling a PyTorch model down to the kernelHow do I profile a PyTorch model and find the slowest CUDA kernel?
    run logged
  9. 89
    CUDA, Triton, cuTile, CUTLASS, Mojo, HIP, Metal and WebGPU: what to learnShould I learn Triton, cuTile, CUTLASS, HIP or Mojo after CUDA?
    lesson
  10. 90
    Checkpoint: library or kernel?When should I write a custom CUDA kernel instead of calling a library?
    run logged