Colloquium 2025 Converting Python code with NumPy to run on the GPU

Python's NumPy library is one of the standard ways for researchers to perform mathematical computations. With the wider availability and power of GPU resources, the need arises to convert NumPy programs to run on the GPU to improve their performance, ideally with as little modification as possible. This seminar will discuss CuPy, a library highly compatible with NumPy, which offers drop-in replacement for most NumPy (and SciPy) functions. The seminar will discuss the basic techniques used to convert a NumPy program to CuPy, emphasizing the good practices required to obtain an efficient code. Another more recently developed approach is the cuPyNumeric library from NVIDIA, which allows running NumPy code on the GPU with no code changes. The seminar will discuss how to install and run it on HPC clusters.