Fundamentals of Accelerated Computing With CUDA Python

Fundamentals of Accelerated Computing With CUDA Python


USD 90.00
excl. VAT

This course explores how to use Numba—the just-in-time, type-specializing Python function compiler—to accelerate Python programs to run on massively parallel NVIDIA GPUs.

Course Prerequisites

  • Basic Python competency, including familiarity with variable types, loops, conditional statements, functions, and array manipulations.
  • Also, must have NumPy competency, including the use of ndarrays and ufuncs.

What you will learn

You’ll learn how to:

  • Use Numba to compile CUDA kernels from NumPy universal functions (ufuncs). Use Numba to create and launch custom CUDA kernels
  • Apply key GPU memory management techniques Upon completion, you’ll be able to use Numba to compile and launch CUDA kernels to accelerate your Python applications on NVIDIA GPUs.

Additional information

PLEASE NOTE: It may take 2-3 business days for your course access to be activated. You will receive an email from us with all necessary details.