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Towards policy and guidelines for the selection of computational engines

机译:制定用于选择计算引擎的政策和指南

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Much research has been performed that concentrates on providing processing throughput enhancements to existing algorithms. Many systems have performance requirements that constrain their volume and/or power consumption. For volume and power consumption constrained systems, throughput cannot be the only decision factor when selecting a computational engine. Typical studies can aid in the selection of computational engines that meet the throughput requirements of a system, but may be of little help with respect to the volume, power and thermal constraints. This paper takes a different approach to help provide a different perspective on the constrained design problem. The research performed in this paper emphasizes the cost due to the power, size and Non-Recurring Engineering (NRE) costs of various computational engines. The computational engines researched in this paper are: Central Processing Unit (CPU), mobile CPU, Digital Signal Processor (DSP), and mobile Graphics Processing Unit (GPU). The various architectures are compared against each other with respect to throughput, power, size and NRE costs. The authors hope that the process outlined in this paper may serve as a possible guideline for other Systems Engineers to perform similar Analysis of Alternatives of computational engines. Furthermore, the authors hope that the methods used for the relative performance evaluations will serve as a starting point to help shape policy in the selection of computational engines for future designs.
机译:已经进行了许多研究,集中于为现有算法提供处理吞吐量的增强。许多系统具有限制其体积和/或功耗的性能要求。对于体积和功耗受限的系统,吞吐量不是选择计算引擎时的唯一决定因素。典型的研究可以帮助选择满足系统吞吐量要求的计算引擎,但在体积,功率和热约束方面可能没有多大帮助。本文采用不同的方法来帮助提供有关受约束设计问题的不同观点。本文进行的研究强调了各种计算引擎的功耗,大小和非经常性工程(NRE)成本所引起的成本。本文研究的计算引擎是:中央处理器(CPU),移动CPU,数字信号处理器(DSP)和移动图形处理器(GPU)。在吞吐量,功耗,尺寸和NRE成本方面,将各种体系结构进行了比较。作者希望本文概述的过程可以作为其他系统工程师进行类似的计算引擎替代方案分析的可能指南。此外,作者希望用于相对性能评估的方法将作为一个起点,以帮助制定政策以选择未来设计的计算引擎。

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