This workshop 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. 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.

Prerequisites: Basic Python competency including familiarity with variable types, loops, conditional statements, functions, and array manipulations. NumPy competency including the use of ndarrays and ufuncs.

Technologies: CUDA, Python, Numba, NumPy