A 2-to-10-b Output Precision Reconfigurable Compute-In-Memory Macro Leveraging Input Conditioning Using Residue Amplification

IF 2.2 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Balaji Vijayakumar;Ashwin Balagopal Sundar;Janakiraman Viraraghavan;Varchas Bharadwaj
{"title":"A 2-to-10-b Output Precision Reconfigurable Compute-In-Memory Macro Leveraging Input Conditioning Using Residue Amplification","authors":"Balaji Vijayakumar;Ashwin Balagopal Sundar;Janakiraman Viraraghavan;Varchas Bharadwaj","doi":"10.1109/LSSC.2024.3415476","DOIUrl":null,"url":null,"abstract":"Artificial intelligence workloads demand a wide range of multiply and accumulate (MAC) precision. Pitch-matching constraints in compute-in-memory (CIM) engines limit the analog-to-digital converter (ADC) precision to about 8 bits. This letter demonstrates a method of mapping a suitable input conditioned MAC range to the input dynamic range of the on-chip 7-b ADC, thereby achieving up to 10 bits of output MAC precision. A 424 Kb SRAM CIM macro was fabricated in TSMC 28 nm, which computes 72 MACs in parallel per cycle. Measurement results at nominal supply voltage show an energy efficiency of 196.6–102 TOPS/W/b for a 2–10 bit output MAC precision. Inference results on MNIST, CIFAR10, and CIFAR100 are shown with \n<inline-formula> <tex-math>$\\leq 1\\%$ </tex-math></inline-formula>\n accuracy loss from the software baseline.","PeriodicalId":13032,"journal":{"name":"IEEE Solid-State Circuits Letters","volume":"7 ","pages":"219-222"},"PeriodicalIF":2.2000,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Solid-State Circuits Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10559382/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial intelligence workloads demand a wide range of multiply and accumulate (MAC) precision. Pitch-matching constraints in compute-in-memory (CIM) engines limit the analog-to-digital converter (ADC) precision to about 8 bits. This letter demonstrates a method of mapping a suitable input conditioned MAC range to the input dynamic range of the on-chip 7-b ADC, thereby achieving up to 10 bits of output MAC precision. A 424 Kb SRAM CIM macro was fabricated in TSMC 28 nm, which computes 72 MACs in parallel per cycle. Measurement results at nominal supply voltage show an energy efficiency of 196.6–102 TOPS/W/b for a 2–10 bit output MAC precision. Inference results on MNIST, CIFAR10, and CIFAR100 are shown with $\leq 1\%$ accuracy loss from the software baseline.
利用残差放大进行输入调节的 2-10-b 输出精度可重构内存计算巨集
人工智能工作负载需要大范围的乘法和累加(MAC)精度。内存计算 (CIM) 引擎中的节距匹配限制将模数转换器 (ADC) 的精度限制在 8 位左右。这封信展示了一种将合适的输入条件 MAC 范围映射到片上 7-b ADC 输入动态范围的方法,从而实现高达 10 位的输出 MAC 精度。在 TSMC 28 纳米工艺中制造了 424 Kb SRAM CIM 宏,每个周期并行计算 72 个 MAC。在标称电源电压下的测量结果显示,2-10 位输出 MAC 精度的能效为 196.6-102 TOPS/W/b。在MNIST、CIFAR10和CIFAR100上的推理结果显示,与软件基线相比,精度损失为$\leq 1\%$。
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
IEEE Solid-State Circuits Letters
IEEE Solid-State Circuits Letters Engineering-Electrical and Electronic Engineering
CiteScore
4.30
自引率
3.70%
发文量
52
×
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