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Power, Area, and Performance Optimization of Standard Cell Memory Arrays Through Controlled Placement

Published: 27 May 2016 Publication History

Abstract

Embedded memory remains a major bottleneck in current integrated circuit design in terms of silicon area, power dissipation, and performance; however, static random access memories (SRAMs) are almost exclusively supplied by a small number of vendors through memory generators, targeted at rather generic design specifications. As an alternative, standard cell memories (SCMs) can be defined, synthesized, and placed and routed as an integral part of a given digital system, providing complete design flexibility, good energy efficiency, low-voltage operation, and even area efficiency for small memory blocks. Yet implementing an SCM block with a standard digital flow often fails to exploit the distinct and regular structure of such an array, leaving room for optimization. In this article, we present a design methodology for optimizing the physical implementation of SCM macros as part of the standard design flow. This methodology introduces controlled placement, leading to a structured, noncongested layout with close to 100% placement utilization, resulting in a smaller silicon footprint, reduced wire length, and lower power consumption compared to SCMs without controlled placement. This methodology is demonstrated on SCM macros of various sizes and aspect ratios in a state-of-the-art 28nm fully depleted silicon-on-insulator technology, and compared with equivalent macros designed with the noncontrolled, standard flow, as well as with foundry-supplied SRAM macros. The controlled SCMs provide an average 25% reduction in area as compared to noncontrolled implementations while achieving a smaller size than SRAM macros of up to 1Kbyte. Power and performance comparisons of controlled SCM blocks of a commonly found 256 × 32 (1 Kbyte) memory with foundry-provided SRAMs show greater than 65% and 10% reduction in read and write power, respectively, while providing faster access than their SRAM counterparts, despite being of an aspect ratio that is typically unfavorable for SCMs. In addition, the SCM blocks function correctly with a supply voltage as low as 0.3V, well below the lower limit of even the SRAM macros optimized for low-voltage operation. The controlled placement methodology is applied within a full-chip physical implementation flow of an OpenRISC-based test chip, providing more than 50% power reduction compared to equivalently sized compiled SRAMs under a benchmark application.

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Information

Published In

cover image ACM Transactions on Design Automation of Electronic Systems
ACM Transactions on Design Automation of Electronic Systems  Volume 21, Issue 4
September 2016
423 pages
ISSN:1084-4309
EISSN:1557-7309
DOI:10.1145/2939671
  • Editor:
  • Naehyuck Chang
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 27 May 2016
Accepted: 01 January 2016
Revised: 01 January 2016
Received: 01 August 2015
Published in TODAES Volume 21, Issue 4

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Author Tags

  1. Standard cell memories
  2. controlled placement
  3. low power
  4. power-area-performance trade-off
  5. subthreshold operation

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  • Research-article
  • Research
  • Refereed

Funding Sources

  • Swiss Government Excellence Scholarship
  • HiPer Consortium under the “Magnet” program of the office of the chief scientist in the Israeli Ministry of Economy
  • FP7 project PHIDIAS
  • Nano-Tera.ch with Swiss Confederation financing under the IcySoC project

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  • (2024)Energy and Bandwidth Efficient Sparse Programmable Dataflow AcceleratorIEEE Transactions on Circuits and Systems I: Regular Papers10.1109/TCSI.2024.342589571:9(4092-4105)Online publication date: Sep-2024
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