| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 06003 | |
| Number of page(s) | 7 | |
| Section | Physics Analysis Tools | |
| DOI | https://doi.org/10.1051/epjconf/202429506003 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429506003
Awkward Just-In-Time (JIT) Compilation: A Developer’s Experience
Princeton University, Princeton, NJ 08544, USA
* e-mail: iosborne@princeton.edu
Published online: 6 May 2024
Awkward Array is a library for performing NumPy-like computations on nested, variable-sized data, enabling array-oriented programming on arbitrary data structures in Python. However, imperative (procedural) solutions can sometimes be easier to write or faster to run. Performant imperative programming requires compilation; JIT-compilation makes it convenient to compile in an interactive Python environment. Various functions in Awkward Arrays JIT-compile a user’s code into executable machine code. They use several different techniques, but reuse parts of each others’ implementations. We discuss the techniques used to achieve the Awkward Arrays acceleration with JITcompilation, focusing on RDataFrame, cppyy, and Numba, particularly Numba on GPUs: conversions of Awkward Arrays to and from RDataFrame; standalone cppyy; passing Awkward Arrays to and from Python functions compiled by Numba; passing Awkward Arrays to Python functions compiled for GPUs by Numba; and header-only libraries for populating Awkward Arrays from C++ without any Python dependencies
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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