Fundamentals of Accelerated Computing With CUDA Python

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.

• 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.

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.

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.