|
Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2020 Vol.21 No.10 P.1426-1441
Multi-dimensional optimization for approximate near-threshold computing
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.
Key words: Approximate computing, Near-threshold computing, Output quality predictor, Energy, Performance
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。
关键词组:
References:
Open peer comments: Debate/Discuss/Question/Opinion
<1>
DOI:
10.1631/FITEE.2000089
CLC number:
TP302.1
Download Full Text:
Downloaded:
2931
Clicked:
5493
Cited:
0
On-line Access:
2024-08-27
Received:
2023-10-17
Revision Accepted:
2024-05-08
Crosschecked:
2020-09-29