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Memory hierarchy reconfiguration for energy and performance in general-purpose processor architectures

Authors:

Rajeev Balasubramonian,

David Albonesi,

Alper Buyuktosunoglu,

Sandhya DwarkadasAuthors Info & Claims

MICRO 33: Proceedings of the 33rd annual ACM/IEEE international symposium on Microarchitecture

Pages 245 - 257

https://doi.org/10.1145/360128.360153

Published: 01 December 2000 Publication History

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Mehta SYue A(2024)Forward to the Past: An Alternative to Hybrid CPU Design2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)10.1109/ISPASS61541.2024.00030(230-240)Online publication date: 5-May-2024
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Memory hierarchy reconfiguration for energy and performance in general-purpose processor architectures

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Published In

MICRO 33: Proceedings of the 33rd annual ACM/IEEE international symposium on Microarchitecture

December 2000

357 pages

ISBN:1581131968

DOI:10.1145/360128

Chairmen:
Andrew Wolfe
S3 Incorporated
,
Michael Schlansker
Hewlett-Packard

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]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 December 2000

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MICRO00: 33rd Annual International Symposium on Microarchitecture

California, Monterey, USA

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MICRO 33 Paper Acceptance Rate 31 of 110 submissions, 28%;

Overall Acceptance Rate 484 of 2,242 submissions, 22%

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https://doi.org/10.1109/ISPASS61541.2024.00030
Weston KJanfaza VTaur AMungra DKansal AZahran MMuzahid A(2023)Post-Silicon Customization Using Deep Neural NetworksArchitecture of Computing Systems10.1007/978-3-031-42785-5_9(120-136)Online publication date: 26-Aug-2023
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https://doi.org/10.1109/TVCG.2020.3021048
Sanchez-Flores AAlvarez LAlorda-Ladaria B(2022)A review of CNN accelerators for embedded systems based on RISC-V2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)10.1109/COINS54846.2022.9855006(1-6)Online publication date: 1-Aug-2022
https://doi.org/10.1109/COINS54846.2022.9855006
Chen RWu JShi HLi YLiu XWang GLaure EMarkidis SVerbanescu ALofstead G(2021)DRLPartProceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing10.1145/3431379.3460648(175-188)Online publication date: 21-Jun-2021
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Cheng CTiw PCai YYan XYang YHuang R(2021)In-memory computing with emerging nonvolatile memory devicesScience China Information Sciences10.1007/s11432-021-3327-764:12Online publication date: 4-Nov-2021
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Kim JLee JKo HOh DHan SJeong GOh H(2019)AuthCropperACM Transactions on Embedded Computing Systems10.1145/335819518:5s(1-17)Online publication date: 8-Oct-2019
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