Numerical computing on the web: benchmarking for the future

D. Herrera, Hanfeng Chen, Erick Lavoie, L. Hendren
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引用次数: 23

Abstract

Recent advances in execution environments for JavaScript and WebAssembly that run on a broad range of devices, from workstations and mobile phones to IoT devices, provide new opportunities for portable and web-based numerical computing. Indeed, numerous numerical libraries and applications are emerging on the web, including Tensorflow.js, JSMapReduce, and the NLG Protein Viewer. This paper evaluates the current performance of numerical computing on the web, including both JavaScript and WebAssembly, over a wide range of devices from workstations to IoT devices. We developed a new benchmarking approach, which allowed us to perform centralized benchmarking, including benchmarking on mobile and IoT devices. Using this approach we performed four performance studies using the Ostrich benchmark suite, a collection of numerical programs representing the numerical dwarf categories identified by Colella. We studied the performance evolution of JavaScript, the relative performance of WebAssembly, the performance of server-side Node.js, and a comprehensive performance showdown for a wide range of devices.
网络上的数值计算:未来的基准
JavaScript和WebAssembly的执行环境的最新进展可以在各种设备上运行,从工作站和移动电话到物联网设备,为便携式和基于web的数字计算提供了新的机会。事实上,许多数字库和应用程序正在网络上出现,包括Tensorflow.js, JSMapReduce和NLG蛋白质查看器。本文在从工作站到物联网设备的广泛设备上评估了网络上数字计算的当前性能,包括JavaScript和WebAssembly。我们开发了一种新的基准测试方法,使我们能够执行集中基准测试,包括在移动和物联网设备上进行基准测试。使用这种方法,我们使用鸵鸟基准套件进行了四项性能研究,鸵鸟基准套件是一组代表Colella确定的数值侏儒类别的数值程序。我们研究了JavaScript的性能演变,WebAssembly的相对性能,服务器端Node.js的性能,以及各种设备的综合性能对决。
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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