HyGain: High-performance, Energy-efficient Hybrid Gain Cell-based Cache Hierarchy

Author:

Singh Sarabjeet1ORCID,Surana Neelam2ORCID,Prasad Kailash3ORCID,Jain Pranjali4ORCID,Mekie Joycee3ORCID,Awasthi Manu5ORCID

Affiliation:

1. University of Utah, USA

2. NVIDIA Graphics, India

3. Department of Electrical Engineering, Indian Institute of Technology, Gandhinagar, India

4. University of California, Santa Barbara, USA

5. Ashoka University, India

Abstract

In this article, we propose a “full-stack” solution to designing high-apacity and low-latency on-chip cache hierarchies by starting at the circuit level of the hardware design stack. We propose a novel half V DD precharge 2T Gain Cell (GC) design for the cache hierarchy. The GC has several desirable characteristics, including ~50% higher storage density and ~50% lower dynamic energy as compared to the traditional 6T SRAM, even after accounting for peripheral circuit overheads. We also demonstrate data retention time of 350 us (~17.5× of eDRAM) at 28 nm technology with V DD = 0.9V and temperature = 27°C that, combined with optimizations like staggered refresh, makes it an ideal candidate to architect all levels of on-chip caches. We show that compared to 6T SRAM, for a given area budget, GC-based caches, on average, provide 30% and 36% increase in IPC for single- and multi-programmed workloads, respectively, on contemporary workloads, including SPEC CPU 2017. We also observe dynamic energy savings of 42% and 34% for single- and multi-programmed workloads, respectively. Finally, in a quest to utilize the best of all worlds, we combine GC with STT-RAM to create hybrid hierarchies. We show that a hybrid hierarchy with GC caches at L1 and L2 and an LLC split between GC and STT-RAM is able to provide a 46% benefit in energy-delay product (EDP) as compared to an all-SRAM design, and 13% as compared to an all-GC cache hierarchy, averaged across multi-programmed workloads.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Reference83 articles.

1. [n. d.]. 3D V-Cache. Retrieved from https://www.amd.com/en/campaigns/3d-v-cache.

2. [n. d.]. Micron Technical Note TN-41-01. Retrieved from http://www.micron.com/products/support/power-calc/.

3. James W. Adkisson Ramachandra Divakaruni Jeffrey P. Gambino and Jack A. Mandelman. 2002. Embedded DRAM on silicon-on-insulator substrate. US Patent 6 350 653.

4. Aditya Agrawal, Amin Ansari, and Josep Torrellas. 2014. Mosaic: Exploiting the spatial locality of process variation to reduce refresh energy in on-chip eDRAM modules. In Proceedings of the 20th International Symposium on High Performance Computer Architecture (HPCA).

5. Aditya Agrawal, Prabhat Jain, Amin Ansari, and Josep Torrellas. 2013. Refrint: Intelligent refresh to minimize power in on-chip multiprocessor cache hierarchies. In Proceedings of the 19th International Symposium on High Performance Computer Architecture (HPCA).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3