skip to main content
10.1145/3489517.3530596acmconferencesArticle/Chapter ViewAbstractPublication PagesdacConference Proceedingsconference-collections
research-article
Public Access

PATH: evaluation of boolean logic using path-based in-memory computing

Published: 23 August 2022 Publication History

Abstract

Processing in-memory breaks von Neumann-based constructs to accelerate data-intensive applications. Noteworthy efforts have been devoted to executing Boolean logic using digital in-memory computing. The limitation of state-of-the-art paradigms is that they heavily rely on repeatedly switching the state of the non-volatile resistive devices using expensive WRITE operations. In this paper, we propose a new in-memory computing paradigm called path-based computing for evaluating Boolean logic. Computation within the paradigm is performed using a one-time expensive compile phase and a fast and efficient evaluation phase. The key property of the paradigm is that the execution phase only involves cheap READ operations. Moreover, a synthesis tool called PATH is proposed to automatically map computation to a single crossbar design. The PATH tool also supports the synthesis of path-based computing systems where the total number of crossbars and the number of inter-crossbar connections are minimized. We evaluate the proposed paradigm using 10 circuits from the RevLib benchmark suite. Compared with state-of-the-art digital in-memory computing paradigms, path-based computing improves energy and latency up to 4.7X and 8.5X, respectively.

References

[1]
[n. d.]. CPLEX optimizer. https://www.ibm.com/analytics/cplex-optimizer
[2]
Hiroyuki Akinaga and Hisashi Shima. 2010. Resistive random access memory (ReRAM) based on metal oxides. Proc. IEEE 98, 12 (2010), 2237--2251.
[3]
John Backus. 1978. Can programming be liberated from the von Neumann style? CACM 21, 8 (1978), 613--641.
[4]
Debjyoti Bhattacharjee et al. 2020. CONTRA: area-constrained technology mapping framework for memristive memory processing unit. In ICCAD'20. 1--9.
[5]
Alexandros Bousdekis et al. 2021. A Review of Data-Driven Decision-Making Methods for Industry 4.0 Maintenance Applications. Electronics 10, 7 (2021), 828.
[6]
Karl S Brace, Richard L Rudell, and Randal E Bryant. 1990. Efficient implementation of a BDD package. In DAC'90. IEEE, 40--45.
[7]
Geoffrey W Burr et al. 2010. Phase change memory technology. JVST B 28, 2 (2010), 223--262.
[8]
Miao Hu et al. 2018. Memristor-based analog computation and neural network classification with a dot product engine. Advanced Materials 30, 9 (2018), 1705914.
[9]
Yiming Huai et al. 2008. Spin-transfer torque MRAM (STT-MRAM): Challenges and prospects. AAPPS bulletin 18, 6 (2008), 33--40.
[10]
Shahar Kvatinsky et al. 2014. MAGIC---Memristor-aided logic. IEEE TCAS-II 61, 11 (2014), 895--899.
[11]
Eero Lehtonen, Jussi Poikonen, and Mika Laiho. 2012. Implication logic synthesis methods for memristors. In ISCAS'12. IEEE, 2441--2444.
[12]
Shin-ichi Minato et al. 1990. Shared binary decision diagram with attributed edges for efficient Boolean function manipulation. In DAC'90. IEEE, 52--57.
[13]
Mehdi Mohammadi et al. 2018. Deep learning for IoT big data and streaming analytics: A survey. COMST 20, 4 (2018), 2923--2960.
[14]
Giacomo Pedretti et al. 2020. A spiking recurrent neural network with phase-change memory neurons and synapses for the accelerated solution of constraint satisfaction problems. JXCDC 6, 1 (2020), 89--97.
[15]
Alexander Pisarev et al. 2021. Fabrication technology and electrophysical properties of a composite memristor-diode crossbar used as a basis for hardware implementation of a biomorphic neuroprocessor. Microelectronic Engineering 236 (2021), 111471.
[16]
David Reinsel-John Gantz-John Rydning. 2018. The digitization of the world from edge to core. Framingham: International Data Corporation (2018), 16.
[17]
Ali Shafiee et al. 2016. ISAAC: A convolutional neural network accelerator with in-situ analog arithmetic in crossbars. ACM SIGARCH 44, 3 (2016), 14--26.
[18]
Saeideh Shirinzadeh, Mathias Soeken, and Rolf Drechsler. 2016. Multi-objective BDD optimization for RRAM circuit design. In IEEE DDECS 2016. 1--6.
[19]
Fabio Somenzi. 2012. CUDD: CU decision diagram package-release 2.4. 0. University of Colorado at Boulder (2012).
[20]
Linghao Song et al. 2017. Pipelayer: A pipelined reram-based accelerator for deep learning. In HPCA. IEEE, 541--552.
[21]
Phrangboklang Lyngton Thangkhiew, Rahul Gharpinde, and Kamalika Datta. 2018. Efficient mapping of Boolean functions to memristor crossbar using MAGIC NOR gates. TCAS-I 65, 8 (2018), 2466--2476.
[22]
Sven Thijssen et al. 2021. COMPACT: Flow-Based Computing on Nanoscale Crossbars with Minimal Semiperimeter. In DATE. IEEE, 232--237.
[23]
Alvaro Velasquez and Sumit Jha. 2015. Automated synthesis of crossbars for nanoscale computing using formal methods. In NANOARCH'15. IEEE, 130--136.
[24]
Miao Wang et al. 2015. A selector device based on graphene-oxide heterostructures for memristor crossbar applications. Appl. Phys. A 120, 2 (2015), 403--407.
[25]
Robert Wille et al. 2008. RevLib: An online resource for reversible functions and reversible circuits. In ISMVL'08. IEEE, 220--225.
[26]
Cong Xu et al. 2015. Overcoming the challenges of crossbar resistive memory architectures. In HPCA'15. IEEE, 476--488.
[27]
Linlin Zhao et al. 2020. Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling. Drug discovery today (2020).

Cited By

View all
  • (2025)Implication logic synthesis and optimization methods for memristor-based logic circuitsMicroelectronics Journal10.1016/j.mejo.2025.106553157(106553)Online publication date: Mar-2025
  • (2024)Designing Energy-Efficient PATH-based Decision Tree Memristor Crossbar Circuits2024 IEEE 24th International Conference on Nanotechnology (NANO)10.1109/NANO61778.2024.10628690(209-213)Online publication date: 8-Jul-2024
  • (2024)Design and Analysis of Low Power Differential Amplifier in SRAM Memory Using Sleepy-Keeper Leakage Control Technique2024 9th International Conference on Communication and Electronics Systems (ICCES)10.1109/ICCES63552.2024.10859810(301-308)Online publication date: 16-Dec-2024
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference
July 2022
1462 pages
ISBN:9781450391429
DOI:10.1145/3489517
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 ACM 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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 August 2022

Permissions

Request permissions for this article.

Check for updates

Qualifiers

  • Research-article

Funding Sources

Conference

DAC '22
Sponsor:
DAC '22: 59th ACM/IEEE Design Automation Conference
July 10 - 14, 2022
California, San Francisco

Acceptance Rates

Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

Upcoming Conference

DAC '25
62nd ACM/IEEE Design Automation Conference
June 22 - 26, 2025
San Francisco , CA , USA

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)244
  • Downloads (Last 6 weeks)30
Reflects downloads up to 05 Mar 2025

Other Metrics

Citations

Cited By

View all
  • (2025)Implication logic synthesis and optimization methods for memristor-based logic circuitsMicroelectronics Journal10.1016/j.mejo.2025.106553157(106553)Online publication date: Mar-2025
  • (2024)Designing Energy-Efficient PATH-based Decision Tree Memristor Crossbar Circuits2024 IEEE 24th International Conference on Nanotechnology (NANO)10.1109/NANO61778.2024.10628690(209-213)Online publication date: 8-Jul-2024
  • (2024)Design and Analysis of Low Power Differential Amplifier in SRAM Memory Using Sleepy-Keeper Leakage Control Technique2024 9th International Conference on Communication and Electronics Systems (ICCES)10.1109/ICCES63552.2024.10859810(301-308)Online publication date: 16-Dec-2024
  • (2024)Memristive Logic-in-Memory Implementation with Area Efficiency and Parallelism2024 IEEE 42nd International Conference on Computer Design (ICCD)10.1109/ICCD63220.2024.00013(9-15)Online publication date: 18-Nov-2024
  • (2024)READ-Based In-Memory Computing Using Sentential Decision DiagramsProceedings of the 29th Asia and South Pacific Design Automation Conference10.1109/ASP-DAC58780.2024.10473963(818-823)Online publication date: 22-Jan-2024
  • (2024)Towards Area-Efficient Path-Based In-Memory Computing Using Graph IsomorphismsProceedings of the 29th Asia and South Pacific Design Automation Conference10.1109/ASP-DAC58780.2024.10473850(812-817)Online publication date: 22-Jan-2024
  • (2023)STREAM: Toward READ-Based In-Memory Computing for Streaming-Based Processing for Data-Intensive ApplicationsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.326372342:11(3854-3867)Online publication date: 31-Mar-2023
  • (2023)An Area-Efficient In-Memory Implementation Method of Arbitrary Boolean Function Based on SRAM ArrayIEEE Transactions on Computers10.1109/TC.2023.330115672:12(3416-3430)Online publication date: 2-Aug-2023
  • (2023)Path-Based Processing using In-Memory Systolic Arrays for Accelerating Data-Intensive Applications2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323622(1-9)Online publication date: 28-Oct-2023
  • (2022)Equivalence Checking for Flow-Based Computing2022 IEEE 40th International Conference on Computer Design (ICCD)10.1109/ICCD56317.2022.00101(656-663)Online publication date: Oct-2022

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media