Optimizing Data Allocation and Memory Configuration for Non-Volatile Memory based Hybrid SPM on Embedded CMPs

Jingtong Hu; Qingfeng Zhuge; Chun Jason Xue; Wei-Che Tseng; Edwin H.M. Sha

doi:10.1109/IPDPSW.2012.120

Optimizing Data Allocation and Memory Configuration for Non-Volatile Memory based Hybrid SPM on Embedded CMPs

Jingtong Hu
, Qingfeng Zhuge
, Chun Jason Xue
, Wei-Che Tseng
, Edwin H.M. Sha

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

10 Citations (Scopus)

Abstract

The recent emergence of various Non-Volatile Memories (NVMs), with many attractive characteristics such as low leakage power and high-density, provides us with a new way of addressing the memory power consumption problem. In this paper, we target embedded CMPs, and propose a novel Hybrid Scratch Pad Memory (HSPM) architecture which consists of SRAM and NVM to take advantage of the ultra-low leakage power, high density of NVM and fast read of SRAM. A novel data allocation algorithm as well as an algorithm to determine NVM/SRAM ratio for the novel HSPM architecture are proposed. The experimental results show that the data allocation algorithm can reduce the memory access time by 31.22% and the dynamic energy consumption by 15.35% on average for the HSPM architecture when compared with a greedy algorithm. © 2012 IEEE.

Original language	English
Title of host publication	Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012
Pages	982-989
ISBN (Electronic)	978-0-7695-4676-6
DOIs	https://doi.org/10.1109/IPDPSW.2012.120
Publication status	Published - May 2012
Event	2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012 - Shanghai, China Duration: 21 May 2012 → 25 May 2012

Conference

Conference	2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012
Place	China
City	Shanghai
Period	21/05/12 → 25/05/12

Funding

This work is partially supported by NSF CNS-1015802, Texas NHARP 009741-0020-2009, NSFC 61173014, NSFC 61133005, China’s Thousand-Talent Program, and Research Grants Council of the Hong Kong Special Administrative Region, China [Project No. CityU 123609][Project No. CityU 123210].

Research Keywords

Data allocation
energy
MRAM
NVM
on-chip memory
PCM
SPM

RGC Funding Information

RGC-funded

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10.1109/IPDPSW.2012.120

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Hu, J., Zhuge, Q., Xue, C. J., Tseng, W.-C., & Sha, E. H. M. (2012). Optimizing Data Allocation and Memory Configuration for Non-Volatile Memory based Hybrid SPM on Embedded CMPs. In Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012 (pp. 982-989). Article 6270745 https://doi.org/10.1109/IPDPSW.2012.120

@inproceedings{09ac48ebc6284b52adbb21fb57955719,

title = "Optimizing Data Allocation and Memory Configuration for Non-Volatile Memory based Hybrid SPM on Embedded CMPs",

abstract = "The recent emergence of various Non-Volatile Memories (NVMs), with many attractive characteristics such as low leakage power and high-density, provides us with a new way of addressing the memory power consumption problem. In this paper, we target embedded CMPs, and propose a novel Hybrid Scratch Pad Memory (HSPM) architecture which consists of SRAM and NVM to take advantage of the ultra-low leakage power, high density of NVM and fast read of SRAM. A novel data allocation algorithm as well as an algorithm to determine NVM/SRAM ratio for the novel HSPM architecture are proposed. The experimental results show that the data allocation algorithm can reduce the memory access time by 31.22\% and the dynamic energy consumption by 15.35\% on average for the HSPM architecture when compared with a greedy algorithm. {\textcopyright} 2012 IEEE.",

keywords = "Data allocation, energy, MRAM, NVM, on-chip memory, PCM, SPM",

author = "Jingtong Hu and Qingfeng Zhuge and Xue, \{Chun Jason\} and Wei-Che Tseng and Sha, \{Edwin H.M.\}",

year = "2012",

month = may,

doi = "10.1109/IPDPSW.2012.120",

language = "English",

isbn = "978-1-4673-0974-5",

pages = "982--989",

booktitle = "Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012",

note = "2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012 ; Conference date: 21-05-2012 Through 25-05-2012",

}

Hu, J, Zhuge, Q, Xue, CJ, Tseng, W-C & Sha, EHM 2012, Optimizing Data Allocation and Memory Configuration for Non-Volatile Memory based Hybrid SPM on Embedded CMPs. in Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012., 6270745, pp. 982-989, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012, Shanghai, China, 21/05/12. https://doi.org/10.1109/IPDPSW.2012.120

Optimizing Data Allocation and Memory Configuration for Non-Volatile Memory based Hybrid SPM on Embedded CMPs. / Hu, Jingtong; Zhuge, Qingfeng; Xue, Chun Jason et al.
Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012. 2012. p. 982-989 6270745.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Optimizing Data Allocation and Memory Configuration for Non-Volatile Memory based Hybrid SPM on Embedded CMPs

AU - Hu, Jingtong

AU - Zhuge, Qingfeng

AU - Xue, Chun Jason

AU - Tseng, Wei-Che

AU - Sha, Edwin H.M.

PY - 2012/5

Y1 - 2012/5

N2 - The recent emergence of various Non-Volatile Memories (NVMs), with many attractive characteristics such as low leakage power and high-density, provides us with a new way of addressing the memory power consumption problem. In this paper, we target embedded CMPs, and propose a novel Hybrid Scratch Pad Memory (HSPM) architecture which consists of SRAM and NVM to take advantage of the ultra-low leakage power, high density of NVM and fast read of SRAM. A novel data allocation algorithm as well as an algorithm to determine NVM/SRAM ratio for the novel HSPM architecture are proposed. The experimental results show that the data allocation algorithm can reduce the memory access time by 31.22% and the dynamic energy consumption by 15.35% on average for the HSPM architecture when compared with a greedy algorithm. © 2012 IEEE.

AB - The recent emergence of various Non-Volatile Memories (NVMs), with many attractive characteristics such as low leakage power and high-density, provides us with a new way of addressing the memory power consumption problem. In this paper, we target embedded CMPs, and propose a novel Hybrid Scratch Pad Memory (HSPM) architecture which consists of SRAM and NVM to take advantage of the ultra-low leakage power, high density of NVM and fast read of SRAM. A novel data allocation algorithm as well as an algorithm to determine NVM/SRAM ratio for the novel HSPM architecture are proposed. The experimental results show that the data allocation algorithm can reduce the memory access time by 31.22% and the dynamic energy consumption by 15.35% on average for the HSPM architecture when compared with a greedy algorithm. © 2012 IEEE.

KW - Data allocation

KW - energy

KW - MRAM

KW - NVM

KW - on-chip memory

KW - PCM

KW - SPM

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DO - 10.1109/IPDPSW.2012.120

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-4673-0974-5

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EP - 989

BT - Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012

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ER -

Optimizing Data Allocation and Memory Configuration for Non-Volatile Memory based Hybrid SPM on Embedded CMPs

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Research Keywords

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