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CLC number: TP302.1

On-line Access: 2020-10-14

Received: 2020-02-26

Revision Accepted: 2020-05-13

Crosschecked: 2020-09-29

Cited: 0

Clicked: 1588

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jing Wang

https://orcid.org/0000-0003-3653-7013

Wei-gong Zhang

https://orcid.org/0000-0003-3969-5607

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Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.10 P.1426-1441

http://doi.org/10.1631/FITEE.2000089


Multi-dimensional optimization for approximate near-threshold computing


Author(s):  Jing Wang, Wei-wei Liang, Yue-hua Niu, Lan Gao, Wei-gong Zhang

Affiliation(s):  College of Information Engineering, Capital Normal University, Beijing 100056, China; more

Corresponding email(s):   jwang@cnu.edu.cn, zwg771@cnu.edu.cn

Key Words:  Approximate computing, Near-threshold computing, Output quality predictor, Energy, Performance


Jing Wang, Wei-wei Liang, Yue-hua Niu, Lan Gao, Wei-gong Zhang. Multi-dimensional optimization for approximate near-threshold computing[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(10): 1426-1441.

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Abstract: 
The demise of Dennard’s scaling has created both power and utilization wall challenges for computer systems. As transistors operating in the near-threshold region are able to obtain flexible trade-offs between power and performance, it is regarded as an alternative solution to the scaling challenge. A reduction in supply voltage will nevertheless generate significant reliability challenges, while maintaining an error-free system that generates high costs in both performance and energy consumption. The main purpose of research on computer architecture has therefore shifted from performance improvement to complex multi-objective optimization. In this paper, we propose a three-dimensional optimization approach which can effectively identify the best system configuration to establish a balance among performance, energy, and reliability. We use a dynamic programming algorithm to determine the proper voltage and approximate level based on three predictors: system performance, energy consumption, and output quality. We propose an output quality predictor which uses a hardware/software co-design fault injection platform to evaluate the impact of the error on output quality under near-threshold computing (NTC). Evaluation results demonstrate that our approach can lead to a 28% improvement in output quality with a 10% drop in overall energy efficiency; this translates to an approximately 20% average improvement in accuracy, power, and performance.

支持近似计算的近阈值系统多目标优化

王晶1,梁伟伟1,牛跃华2,高岚1,张伟功3
1首都师范大学信息工程学院,中国北京市,100056
2中国空间技术研究院空间飞行器设计总体部,中国北京市,100094
3北京市成像理论与技术高精尖创新中心,中国北京市,100048

摘要:登纳德缩放定律的失效使计算机系统面临功耗和利用率双重挑战。让晶体管在近阈值电压附近工作,能够有效解决能耗墙问题。然而,电压降低会引发错误,导致可靠性问题。若在解决电压降低带来的副作用的同时确保系统完全正确,又会额外减损系统性能,增加能耗。由此可见,计算机系统设计的目标已从简单的性能优化发展到多目标综合优化。本文提出一种通过有效识别系统最佳配置实现性能、能耗和可靠性的综合优化方法。设计了输出精度预测器、性能预测器和功耗预测器,分别预测不同系统配置下的精度、性能和功耗。其中输出质量预测器采用软硬件协同的故障注入平台,分析近阈值电压导致的错误对输出精度的影响。采用多目标优化动态规划模型,基于所设计的输出精度预测器、性能预测器和功耗预测器,选择系统最佳的电压和近似级别。实验结果显示本文方案在能效性下降10%的情况下将输出精度提高28%,从而实现平均20%的精度、功耗和性能的综合优化。

关键词:近似计算;近阈值计算;输出精度预测器;能耗;性能

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