Evaluation of the Global Address Space Programming Interface (GASPI)

Jens Breitbart, Mareike Schmidtobreick, V. Heuveline
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引用次数: 8

Abstract

The first exascale supercomputers are expected by the end of this decade and will presumably feature an increase in core count, but a decrease in the amount of memory available per core. As of now, it is still unclear if the current programming models will provide high performance on exascale systems. One programming model considered to be an alternative to MPI is the so-called partitioned global address space (PGAS) model. Within this paper we evaluate a relatively new PGAS API: the Global Address Space Programming Interface (GASPI) and compare it to MPI on the basis of microbenchmarks. These benchmarks show that GASPI provides about the same level of performance for single-threaded communication, but is up to an order of magnitude faster than both Intel and IBM MPI for multi-threaded communication. Hereafter, we discuss the different features of GASPI in comparison to two main PGAS languages, namely UPC and CAF. In addition, we present a basic numerical algorithm, a dense matrix-matrix multiplication, as an example on how an implementation can make efficient use of GASPI's features, especially the asynchronous and one-sided communication mechanisms.
全局地址空间编程接口(GASPI)的评价
第一批百亿亿次超级计算机预计将在本十年末问世,其核心数量可能会增加,但每个核心的可用内存数量会减少。到目前为止,还不清楚当前的编程模型是否能在百亿亿级系统上提供高性能。一种被认为可以替代MPI的编程模型是所谓的分区全局地址空间(PGAS)模型。在本文中,我们评估了一个相对较新的PGAS API:全局地址空间编程接口(GASPI),并在微基准测试的基础上将其与MPI进行了比较。这些基准测试表明,GASPI为单线程通信提供了大致相同的性能水平,但在多线程通信方面比Intel和IBM MPI快了一个数量级。接下来,我们将讨论GASPI与两种主要的PGAS语言(即UPC和CAF)的不同特性。此外,我们还提供了一个基本的数值算法,即密集矩阵-矩阵乘法,作为如何有效利用GASPI特性的示例,特别是异步和单向通信机制。
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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