Ultra-Scaled E-Tree-Based SRAM Design and Optimization With Interconnect Focus
SRAM performance is highly dominated by interconnects as technology scales down because of the significant parasitic resistance and capacitance in the interconnect. This paper introduces a framework for the co-design of technology, interconnect, and cache memory with tag array overhead, to optimize the performance of cache memory using a variety of emerging interconnect technologies. In addition, we introduce an innovative E-Tree interconnect aimed at further decreasing the average interconnect length with the consideration of realistic workloads and benchmark against its traditional H-Tree counterparts in terms of various performance metrics, such as energy-delay-area product (EDAP) or energy-delay product (EDP) in the SRAM cache memory system. A comprehensive investigation of design space is conducted, employing realistic, deeply scaled subarray designs across a range of cutting-edge technology nodes. Furthermore, the case study examines various cache memory system design parameters to assess the true potential of emerging interconnect technologies in achieving optimal performance at the cache memory system.
Authors
- James P. Myers
- Francky Catthoor (ORCID: https://orcid.org/0000-0002-3599-8515)
- Mahta Mayahinia (ORCID: https://orcid.org/0000-0002-6084-9810)
- Dawit Burusie Abdi
- Mehdi B. Tahoori (ORCID: https://orcid.org/0000-0002-8829-5610)
- Chenyun Pan (ORCID: https://orcid.org/0000-0001-9161-1728)
- Hsiao-Hsuan Liu (ORCID: https://orcid.org/0000-0003-2305-4258)
- Zhenlin Pei (ORCID: https://orcid.org/0000-0002-0926-2838)
- Zsolt Tökei (ORCID: https://orcid.org/0000-0003-3545-3424)
Institutions
- Karlsruhe Institute of Technology (DE)
- The University of Texas at Arlington (US)
- IMEC (BE)
Publication Details
- Journal
- IEEE Transactions on Circuits and Systems I Regular Papers
- Published
- 2024-08-19
- DOI
- https://doi.org/10.1109/tcsi.2024.3438164
- Citations
- 3
- Primary Topic
- VLSI and FPGA Design Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.63
Funders
- National Science Foundation
- U.S. Department of Energy
- Advanced Scientific Computing Research