Towards universal MPI bindings for enhanced new language support

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Computational Science Pub Date : 2025-03-13 DOI:10.1016/j.jocs.2025.102557

César Piñeiro , Álvaro Vázquez , Juan C. Pichel

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引用次数: 0

Abstract

In the field of High Performance Computing (HPC), Message Passing Interface (MPI) is the most widely used and prevalent programming model. Only the low-level programming languages C, C++, and Fortran have bindings available in the standard. Although there are attempts to provide MPI bindings for other programming languages, these may be limited, which could lead to incompatibilities, performance overhead, and functional gaps. To address those problems, we present MPI4All, a brand-new tool designed to make the process of developing effective MPI bindings for any programming language more straightforward. Support for additional languages can be added with little difficulty, and MPI4All is independent of the MPI implementation. Programming language binding generators for Go and Java are included in the most recent version of MPI4All. We demonstrate their good performance results with respect to other state-of-the-art approaches. This work is an extended version of the ICCS-2024 conference paper (Piñeiro et al., 2024).

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在高性能计算（HPC）领域，消息传递接口（MPI）是应用最广泛、最流行的编程模型。目前只有 C、C++ 和 Fortran 等低级编程语言有标准绑定。虽然有人尝试为其他编程语言提供 MPI 绑定，但这些绑定可能很有限，可能导致不兼容、性能开销和功能差距。为了解决这些问题，我们推出了 MPI4All，这是一种全新的工具，旨在使为任何编程语言开发有效 MPI 绑定的过程变得更加简单。MPI4All 不依赖于 MPI 实现，支持其他语言的难度很小。最新版本的 MPI4All 包含 Go 和 Java 的编程语言绑定生成器。与其他最先进的方法相比，我们展示了它们的良好性能。这项工作是 ICCS-2024 会议论文（Piñeiro 等人，2024 年）的扩展版本。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

5.50

自引率

3.00%

发文量

227

审稿时长

41 days

期刊介绍： Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).