Litcius/Paper detail

Graphene-Based Interconnect Exploration for Large SRAM Caches for Ultrascaled Technology Nodes

Zhenlin Pei, Mahta Mayahinia, Hsiao-Hsuan Liu, Mehdi B. Tahoori, Francky Catthoor, Zsolt Tökei, Chenyun Pan

2022IEEE Transactions on Electron Devices17 citationsDOIOpen Access PDF

Abstract

Graphene-based interconnects are considered promising replacements for traditional copper (Cu) interconnect due to their great electric properties. In this article, an interconnect-memory co- design framework is developed to efficiently optimize various graphene-based interconnect technologies. Four interconnect materials and heterogeneous design schemes are benchmarked against their traditional Cu counterparts to optimize large cache-level SRAM performance in terms of delay and energy per access, energy-delay product (EDP), and energy-delay-area product (EDAP). A large design space exploration is performed based on realistic subarray design and device technology. Various interconnect- and array-level design parameters are studied to quantify the true potential of graphene-based wires for optimal memory performance.

Topics & Concepts

InterconnectionStatic random-access memoryComputer scienceElectronic engineeringMaterials scienceGrapheneEmbedded systemEngineeringNanotechnologyComputer networkGraphene research and applicationsLow-power high-performance VLSI designAdvancements in Battery Materials
Graphene-Based Interconnect Exploration for Large SRAM Caches for Ultrascaled Technology Nodes | Litcius