Static Local Concurrency Errors Detection in MPI-RMA Programs

Emmanuelle Saillard, Marc Sergent, Célia Tassadit Ait Kaci, Denis Barthou
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引用次数: 4

Abstract

Communications are a critical part of HPC simulations, and one of the main focuses of application developers when scaling on supercomputers. While classical message passing (also called two-sided communications) is the dominant communication paradigm, one-sided communications are often praised to be efficient to overlap communications with computations, but challenging to program. Their usage is then generally abstracted through languages and memory abstractions to ease programming (e.g. PGAS). Therefore, little work has been done to help programmers use intermediate runtime layers, such as MPI-RMA, that is often reserved to expert programmers. Indeed, programming with MPI - RMA presents several challenges that require handling the asynchronous nature of one-sided communications to ensure the proper semantics of the program while ensuring its memory consistency. To help programmers detect memory errors such as race conditions as early as possible, this paper proposes a new static analysis of MPI - RMA codes that shows to the programmer the errors that can be detected at compile time. The detection is based on a novel local concurrency errors detection algorithm that tracks accesses through BFS searches on the Control Flow Graphs of a program. We show on several tests and an MPI-RMA variant of the GUPS benchmark that the static analysis allows to detect such errors on user codes. The error codes are integrated in the MPI Bugs Initiative open-source test suite.
MPI-RMA程序中的静态本地并发错误检测
通信是HPC模拟的关键部分,也是应用程序开发人员在超级计算机上扩展时的主要关注点之一。虽然经典的消息传递(也称为双边通信)是主要的通信范式,但单向通信通常被称赞为有效地将通信与计算重叠,但对编程具有挑战性。它们的用法通常通过语言和内存抽象进行抽象,以简化编程(例如PGAS)。因此,帮助程序员使用中间运行时层(如MPI-RMA)的工作很少,这通常是为专业程序员保留的。实际上,使用MPI - RMA编程带来了一些挑战,需要处理单向通信的异步特性,以确保程序的正确语义,同时确保其内存一致性。为了帮助程序员尽早发现内存错误,例如竞态条件,本文提出了一种新的MPI - RMA代码静态分析方法,它向程序员展示了在编译时可以检测到的错误。该检测基于一种新颖的局部并发错误检测算法,该算法通过BFS在程序控制流程图上的搜索来跟踪访问。我们在几个测试和GUPS基准的MPI-RMA变体中展示了静态分析允许检测用户代码上的此类错误。错误代码集成在MPI Bugs Initiative开源测试套件中。
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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