A Voltage-Controlled, Oscillation-Based ADC Design for Computation-in-Memory Architectures Using Emerging ReRAMs

Author:

Mayahinia Mahta1,Singh Abhairaj1,Bengel Christopher2,Wiefels Stefan2,Lebdeh Muath A.1,Menzel Stephan3,Wouters Dirk J.2,Gebregiorgis Anteneh1,Bishnoi Rajendra1,Joshi Rajiv4,Hamdioui Said1

Affiliation:

1. Delft University of Technology, Delft, Netherlands

2. RWTH Aachen University, Aachen, Germany

3. Forschungszentrum Juelich GmbH, Peter-Gruenberg Institut (PGI-7), Juelich, Germany

4. IBM Thomas J. Watson Research Center, Ossining, New York city, USA

Abstract

Conventional von Neumann architectures cannot successfully meet the demands of emerging computation and data-intensive applications. These shortcomings can be improved by embracing new architectural paradigms using emerging technologies. In particular, Computation-In-Memory (CiM) using emerging technologies such as Resistive Random Access Memory (ReRAM) is a promising approach to meet the computational demands of data-intensive applications such as neural networks and database queries. In CiM, computation is done in an analog manner; digitization of the results is costly in several aspects, such as area, energy, and performance, which hinders the potential of CiM. In this article, we propose an efficient Voltage-Controlled-Oscillator (VCO)–based analog-to-digital converter (ADC) design to improve the performance and energy efficiency of the CiM architecture. Due to its efficiency, the proposed ADC can be assigned in a per-column manner instead of sharing one ADC among multiple columns. This will boost the parallel execution and overall efficiency of the CiM crossbar array. The proposed ADC is evaluated using a Multiplication and Accumulation (MAC) operation implemented in ReRAM-based CiM crossbar arrays. Simulations results show that our proposed ADC can distinguish up to 32 levels within 10 ns while consuming less than 5.2 pJ of energy. In addition, our proposed ADC can tolerate ≈30% variability with a negligible impact on the performance of the ADC.

Funder

European Union’s Horizon 2020 research and innovation programme

Federal Ministry of Education and Research

Publisher

Association for Computing Machinery (ACM)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Energy-efficient Computation-In-Memory Architecture using Emerging Technologies;2023 International Conference on Microelectronics (ICM);2023-12-17

2. A 0.0025mm2 8-bit 70MS/s SAR ADC with a Linearity-Improved Bootstrapped Switch for Computation in Memory;2023 8th International Conference on Integrated Circuits and Microsystems (ICICM);2023-10-20

3. Time-domain Subtractive Readout Scheme for Scalable Capacitive Analog In-Memory Computing;2023 IEEE 36th International System-on-Chip Conference (SOCC);2023-09-05

4. Bit slicing approaches for variability aware ReRAM CIM macros;it - Information Technology;2023-04-21

5. Integration of Physics-Derived Memristor Models with Machine Learning Frameworks;2022 56th Asilomar Conference on Signals, Systems, and Computers;2022-10-31

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