This title appears in the Scientific Report :
2023
High-Performance Computing with Python
High-Performance Computing with Python
Python is increasingly used in high-performance computing projects. It can be used either as a high-level interface to existing HPC applications and libraries, as embedded interpreter, or directly.This course combines lectures and hands-on sessions. We will show how Python can be used on parallel ar...
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Personal Name(s): | Meinke, Jan (Corresponding author) |
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Zimmermann, Olav (Corresponding author) | |
Contributing Institute: |
Jülich Supercomputing Center; JSC |
Imprint: |
2023
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Conference: | JSC - as part of the Training Programme of Forschungszentrum Jülich, Jülich / online (Germany), 2023-06-12 - 2023-06-16 |
Document Type: |
Lecture |
Research Program: |
Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups |
Publikationsportal JuSER |
Python is increasingly used in high-performance computing projects. It can be used either as a high-level interface to existing HPC applications and libraries, as embedded interpreter, or directly.This course combines lectures and hands-on sessions. We will show how Python can be used on parallel architectures and how to optimize critical parts of the kernel using various tools.The following topics will be covered: Interactive parallel programming with IPython Profiling and optimization High-performance NumPy Just-in-time compilation with numba Distributed-memory parallel programming with Python and MPI Bindings to other programming languages and HPC libraries Interfaces to GPUsThis course is aimed at scientists who wish to explore the productivity gains made possible by Python for HPC. |