The AllScale API

P. Gschwandtner, Herbert Jordan, Peter Thoman, T. Fahringer
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引用次数: 2

Abstract

Effectively implementing scientific algorithms in distributed memory parallel applications is a difficult task for domain scientists, as evident by the large number of domain-specific languages and libraries available today attempting to facilitate the process. However, they usually provide a closed set of parallel patterns and are not open for extension without vast modifications to the underlying system. In this work, we present the AllScale API, a programming interface for developing distributed memory parallel applications with the ease of shared memory programming models. The AllScale API is closed for modification but open for extension, allowing new, user-defined parallel patterns and data structures to be implemented based on existing core primitives and therefore fully supported in the AllScale framework. Focusing on high-level functionality directly offered to application developers, we present the design advantages of such an API design, detail some of its specifications and evaluate it using three real-world use cases. Our results show that AllScale decreases the complexity of implementing scientific applications for distributed memory while attaining comparable or higher performance compared to MPI reference implementations.
对于领域科学家来说,在分布式内存并行应用程序中有效地实现科学算法是一项艰巨的任务,目前有大量的领域特定语言和库试图促进这一过程。然而,它们通常提供一组封闭的并行模式,如果不对底层系统进行大量修改,就不能对扩展开放。在这项工作中,我们提出了AllScale API,这是一个编程接口,用于开发具有共享内存编程模型的分布式内存并行应用程序。AllScale API对修改是封闭的,但对扩展是开放的,允许新的、用户定义的并行模式和数据结构基于现有的核心原语实现,因此在AllScale框架中完全支持。重点关注直接提供给应用程序开发人员的高级功能,我们展示了这种API设计的设计优势,详细介绍了它的一些规范,并使用三个实际用例对其进行了评估。我们的结果表明,与MPI参考实现相比,AllScale降低了为分布式内存实现科学应用程序的复杂性,同时获得了相当或更高的性能。
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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