A Survey of Techniques for Architecting Processor Components Using Domain-Wall Memory

Author:

Mittal Sparsh1ORCID

Affiliation:

1. Oak Ridge National Laboratory

Abstract

Recent trends of increasing core-count and bandwidth/memory wall have motivated researchers to explore novel memory technologies for designing processor components such as cache, register file, shared memory, and so on. Domain-wall memory (DWM), also known as racetrack memory, is a promising emerging technology due to its non-volatility and very high density. However, use of DWM presents challenges due to characteristics of both DWM itself (e.g., requirement of shift operations, variable latency) and processor components. Recently, several techniques have been proposed to address these challenges. This article presents a survey of architectural techniques for using DWM for designing components in both CPU and GPU. We discuss techniques related to performance, energy, and reliability and also discuss works that compare DWM with other memory technologies. We also highlight the opportunities and obstacles in using DWM for designing processor components. This survey is expected to spark further research in this area and be useful for researchers, chip designers, and computer architects.

Funder

U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research

Publisher

Association for Computing Machinery (ACM)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Cited by 27 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. Magnetic domain walls: types, processes and applications;Journal of Physics D: Applied Physics;2023-11-10

2. DownShift: Tuning Shift Reduction With Reliability for Racetrack Memories;IEEE Transactions on Computers;2023-09-01

3. ERMES: Efficient Racetrack Memory Emulation System based on FPGA;2022 32nd International Conference on Field-Programmable Logic and Applications (FPL);2022-08

4. Spintronic devices: a promising alternative to CMOS devices;Journal of Computational Electronics;2021-01-19

5. Concatenated LDPC/2-D-Marker Codes and Non-Iterative Detection/Decoding for Recovering Position Errors in Racetrack Memories;IEEE Transactions on Magnetics;2020-09

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