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Processing-in-Memory Technology for Machine Learning: From Basic to ASIC

Publication ,  Journal Article
Taylor, B; Zheng, Q; Li, Z; Li, S; Chen, Y
Published in: IEEE Transactions on Circuits and Systems II: Express Briefs
June 1, 2022

Due to the need for computing models that can process large quantities of data efficiently and with high throughput in many state-of-the-art machine learning algorithms, the processing-in-memory (PIM) paradigm is emerging as a potential replacement for standard digital architectures on these workloads. In this tutorial, we review the progress of PIM technology in recent years, at both the circuit and architecture level. We further present an analysis of when and how PIM technology surpasses the performance of conventional architectures. Finally, we outline our vision for the future of PIM technology.

Duke Scholars

Published In

IEEE Transactions on Circuits and Systems II: Express Briefs

DOI

EISSN

1558-3791

ISSN

1549-7747

Publication Date

June 1, 2022

Volume

69

Issue

6

Start / End Page

2598 / 2603

Related Subject Headings

  • Electrical & Electronic Engineering
  • 4009 Electronics, sensors and digital hardware
  • 4006 Communications engineering
  • 0906 Electrical and Electronic Engineering
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Taylor, B., Zheng, Q., Li, Z., Li, S., & Chen, Y. (2022). Processing-in-Memory Technology for Machine Learning: From Basic to ASIC. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(6), 2598–2603. https://doi.org/10.1109/TCSII.2022.3168404
Taylor, B., Q. Zheng, Z. Li, S. Li, and Y. Chen. “Processing-in-Memory Technology for Machine Learning: From Basic to ASIC.” IEEE Transactions on Circuits and Systems II: Express Briefs 69, no. 6 (June 1, 2022): 2598–2603. https://doi.org/10.1109/TCSII.2022.3168404.
Taylor B, Zheng Q, Li Z, Li S, Chen Y. Processing-in-Memory Technology for Machine Learning: From Basic to ASIC. IEEE Transactions on Circuits and Systems II: Express Briefs. 2022 Jun 1;69(6):2598–603.
Taylor, B., et al. “Processing-in-Memory Technology for Machine Learning: From Basic to ASIC.” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 69, no. 6, June 2022, pp. 2598–603. Scopus, doi:10.1109/TCSII.2022.3168404.
Taylor B, Zheng Q, Li Z, Li S, Chen Y. Processing-in-Memory Technology for Machine Learning: From Basic to ASIC. IEEE Transactions on Circuits and Systems II: Express Briefs. 2022 Jun 1;69(6):2598–2603.

Published In

IEEE Transactions on Circuits and Systems II: Express Briefs

DOI

EISSN

1558-3791

ISSN

1549-7747

Publication Date

June 1, 2022

Volume

69

Issue

6

Start / End Page

2598 / 2603

Related Subject Headings

  • Electrical & Electronic Engineering
  • 4009 Electronics, sensors and digital hardware
  • 4006 Communications engineering
  • 0906 Electrical and Electronic Engineering