The approximation scheme for peak power driven voltage partitioning

Jia Wang, Xiaodao Chen, Chen Liao, Shiyan Hu
{"title":"The approximation scheme for peak power driven voltage partitioning","authors":"Jia Wang, Xiaodao Chen, Chen Liao, Shiyan Hu","doi":"10.1109/ICCAD.2011.6105411","DOIUrl":null,"url":null,"abstract":"With advancing technology, large dynamic power consumption has significantly limited circuit miniaturization. Minimizing peak power consumption, which is defined as the maximum power consumption among all voltage partitions, is important since it enables energy saving from the voltage island shutdown mechanism. In this paper, we prove that the peak power driven voltage partitioning problem is NP-complete and propose an efficient provably good fully polynomial time approximation scheme for it. The new algorithm can approximate the optimal peak power driven voltage partitioning solution in O(m2 (mn/∊4)) time within a factor of (1 + ∊) for sufficiently small positive e, where n is the number of circuit blocks and m is the number of partitions which is a small constant in practice. Our experimental results demonstrate that the dynamic programming cannot finish for even 20 blocks while our new approximation algorithm runs fast. In particular, varying e, orders of magnitude speedup can be obtained with only 0.6% power increase. The tradeoff between the peak power minimization and the total power minimization is also investigated. We demonstrate that the total power minimization algorithm obtains good results in total power but with quite large peak power, while our peak power optimization algorithm can achieve on average 26.5% reduction in peak power with only 0.46% increase in total power. Moreover, our peak power driven voltage partitioning algorithm is integrated into a simulated annealing based floorplanning technique. Experimental results demonstrate that compared to total power driven floorplanning, the peak power driven floorplanning can significantly reduce peak power with only little impact in total power, HPWL, estimated power ground routing cost, level shifter cost and runtime. Further, when the voltage island shutdown is performed, peak power driven voltage partitioning can lead to over 10% more energy saving than a greedy frequency based voltage partitioning when multiple idle block sequences are considered.","PeriodicalId":6357,"journal":{"name":"2011 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAD.2011.6105411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

With advancing technology, large dynamic power consumption has significantly limited circuit miniaturization. Minimizing peak power consumption, which is defined as the maximum power consumption among all voltage partitions, is important since it enables energy saving from the voltage island shutdown mechanism. In this paper, we prove that the peak power driven voltage partitioning problem is NP-complete and propose an efficient provably good fully polynomial time approximation scheme for it. The new algorithm can approximate the optimal peak power driven voltage partitioning solution in O(m2 (mn/∊4)) time within a factor of (1 + ∊) for sufficiently small positive e, where n is the number of circuit blocks and m is the number of partitions which is a small constant in practice. Our experimental results demonstrate that the dynamic programming cannot finish for even 20 blocks while our new approximation algorithm runs fast. In particular, varying e, orders of magnitude speedup can be obtained with only 0.6% power increase. The tradeoff between the peak power minimization and the total power minimization is also investigated. We demonstrate that the total power minimization algorithm obtains good results in total power but with quite large peak power, while our peak power optimization algorithm can achieve on average 26.5% reduction in peak power with only 0.46% increase in total power. Moreover, our peak power driven voltage partitioning algorithm is integrated into a simulated annealing based floorplanning technique. Experimental results demonstrate that compared to total power driven floorplanning, the peak power driven floorplanning can significantly reduce peak power with only little impact in total power, HPWL, estimated power ground routing cost, level shifter cost and runtime. Further, when the voltage island shutdown is performed, peak power driven voltage partitioning can lead to over 10% more energy saving than a greedy frequency based voltage partitioning when multiple idle block sequences are considered.
峰值功率驱动电压分配的近似方案
随着技术的进步,巨大的动态功耗极大地限制了电路的小型化。最小化峰值功耗(定义为所有电压分区中的最大功耗)非常重要,因为它可以通过电压岛关闭机制节省能源。在本文中,我们证明了峰值功率驱动的电压分配问题是np完全的,并提出了一个有效且可证明良好的全多项式时间逼近方案。对于足够小的正e,新算法可以在O(m2 (mn/ 4))时间内在因子(1 +)范围内逼近最优峰值功率驱动电压划分解,其中n为电路块数,m为划分数,这在实际中是一个很小的常数。实验结果表明,动态规划甚至不能完成20个块,而新的近似算法运行速度很快。特别是,改变e,仅增加0.6%的功率就可以获得数量级的加速。对峰值功率最小化和总功率最小化之间的权衡进行了研究。我们证明了总功率最小化算法在总功率上取得了良好的效果,但峰值功率相当大,而我们的峰值功率优化算法在总功率仅增加0.46%的情况下,峰值功率平均降低了26.5%。此外,我们的峰值功率驱动的电压分配算法集成到一个基于模拟退火的地板规划技术。实验结果表明,与总功率驱动布局相比,峰值功率驱动布局可以显著降低峰值功率,而对总功率、HPWL、估计功率地路由成本、电平移位器成本和运行时间的影响很小。此外,当执行电压岛关闭时,考虑多个空闲块序列时,峰值功率驱动的电压分区比基于贪婪频率的电压分区节能10%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信