文章基本信息

标题：Hardware and Software Solutions for Energy-Efficient Computing in Scientific Programming
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作者：Daniele D’Agostino ; Ivan Merelli ; Marco Aldinucci 等
期刊名称：Scientific Programming
印刷版ISSN：1058-9244
出版年度：2021
卷号：2021
页码：1-9
DOI：10.1155/2021/5514284
出版社：Hindawi Publishing Corporation
摘要：Energy consumption is one of the major issues in today’s computer science, and an increasing number of scientific communities are interested in evaluating the tradeoff between time-to-solution and energy-to-solution. Despite, in the last two decades, computing which revolved around centralized computing infrastructures, such as supercomputing and data centers, the wide adoption of the Internet of Things (IoT) paradigm is currently inverting this trend due to the huge amount of data it generates, pushing computing power back to places where the data are generated—the so-called fog/edge computing. This shift towards a decentralized model requires an equivalent change in the software engineering paradigms, development environments, hardware tools, languages, and computation models for scientific programming because the local computational capabilities are typically limited and require a careful evaluation of power consumption. This paper aims to present how these concepts can be actually implemented in scientific software by presenting the state of the art of powerful, less power-hungry processors from one side and energy-aware tools and techniques from the other one.