Awkward Just-In-Time (JIT) Compilation: A Developer's Experience

被引：0
|
作者：
Osborne, Ianna [1 ]
Pivarski, Jim [1 ]
Ifrim, Ioana [1 ]
Hollands, Angus [1 ]
Schreiner, Henry [1 ]
机构：
[1] Princeton Univ, Princeton, NJ 08544 USA
来源：
26TH INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS, CHEP 2023 | 2024年 / 295卷
关键词：
D O I：
10.1051/epjconf/202429506003
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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 JIT-compilation, 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
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页数：7
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