Fundamentals of Accelerated Computing with CUDA Python (FACCP) – Contenuti

Contenuti dettagliati del Corso

Introduction

  • Meet the instructor.
  • Create an account at https://learn.nvidia.com/join

Introduction to CUDA Python with Numba

  • Begin working with the Numba compiler and CUDA programming in Python.
  • Use Numba decorators to GPU-accelerate numerical Python functions.
  • Optimize host-to-device and device-to-host memory transfers.

Custom CUDA Kernels in Python with Numba

  • Learn CUDA’s parallel thread hierarchy and how to extend parallel program possibilities.
  • Launch massively parallel custom CUDA kernels on the GPU.
  • Utilize CUDA atomic operations to avoid race conditions during parallel execution.

Multidimensional Grids, and Shared Memory for CUDA Python with Numba

  • Learn multidimensional grid creation and how to work in parallel on 2D matrices.
  • Leverage on-device shared memory to promote memory coalescing while reshaping 2D matrices.

Final Review

  • Review key learnings and wrap up questions.
  • Complete the assessment to earn a certificate.
  • Take the workshop survey.