Numba is a game-changing compiler for high-performance computing with Python. It produces machine code that runs outside of the single-threaded Python interpreter and that fully utilizes the resources of modern CPUs. This means support for parallel multithreading and auto vectorization if available, as with compiled languages such as C++ or Fortran. In this article we document our experience developing PyExaFMM, a multithreaded Numba implementation of the Fast Multipole Method, an algorithm with a non-linear data structure and a large amount of data organization. We find that designing performant Numba code for complex algorithms can be as challenging as writing in a compiled language.
翻译：Numba 是一种用于高性能计算的编译器，可与 Python 配合使用。它产生的机器代码可以在单线程 Python 解释器外运行，并充分利用现代 CPU 的资源。这意味着支持并行多线程和自动向量化（如果有可用），就像使用编译语言（例如 C++ 或 Fortran）一样。在本文中，我们记录了开发 PyExaFMM 的经验：一种基于 Numba 的快速多极子方法（Fast Multipole Method）并行实现，该算法具有非线性数据结构和大量数据组织。我们发现，设计复杂算法的 Numba 代码的性能与编译语言的写作一样具有挑战性。
相关内容
微信扫码咨询专知VIP会员