Speaker
Bernardo Abreu Figueiredo
(Karlsruhe University of Applied Sciences (DE))
Description
In scientific environments, Python has become prevalent. At the same time, GPUs have dominated code acceleration use cases in the past years and are used where a large amount of data is processed. This lecture introduces the CuPy library as an easy way to start writing code for GPUs in Python and to accelerate existing applications. The focus is on the capabilities of CuPy through two real-life examples, which demonstrate the versatility of CuPy and its performance improvements for scientific calculations.
Author
Bernardo Abreu Figueiredo
(Karlsruhe University of Applied Sciences (DE))
Co-author
Konstantinos Iliakis
(CERN)
