Igor Sfiligoi from SDSC gave this talk at the ECSS Symposium. “I have recently helped IceCube expand their resource pool by a few orders of magnitude, first to 380 PFLOP32s for a few hours and later to 170 PFLOP32s for a whole workday. In this session I will explain what was done and how, alongside an overview of why IceCube needs so much compute.”
CUDA-Python and RAPIDS for blazing fast scientific computing
Abe Stern from NVIDIA gave this talk at the ECSS Symposium. “We will introduce Numba and RAPIDS for GPU programming in Python. Numba allows us to write just-in-time compiled CUDA code in Python, giving us easy access to the power of GPUs from a powerful high-level language. RAPIDS is a suite of tools with a Python interface for machine learning and dataframe operations. Together, Numba and RAPIDS represent a potent set of tools for rapid prototyping, development, and analysis for scientific computing. We will cover the basics of each library and go over simple examples to get users started.”