Platform independent software analysis for near memory computing

Stefano Corda; Gagandeep Singh; Ahsan Javed Awan; Roel Jordans; Henk Corporaal

doi:10.1109/DSD.2019.00093

Platform independent software analysis for near memory computing

Stefano Corda, Gagandeep Singh, Ahsan Javed Awan, Roel Jordans, Henk Corporaal

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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Near-memory Computing (NMC) promises improved performance for the applications that can exploit the features of emerging memory technologies such as 3D-stacked memory. However, it is not trivial to find such applications and specialized tools are needed to identify them. In this paper, we present PISA-NMC, which extends a state-of-the-art hardware agnostic profiling tool with metrics concerning memory and parallelism, which are relevant for NMC. The metrics include memory entropy, spatial locality, data-level, and basic-block-level parallelism. By profiling a set of representative applications and correlating the metrics with the application's performance on a simulated NMC system, we verify the importance of those metrics. Finally, we demonstrate which metrics are useful in identifying applications suitable for NMC architectures.

Originele taal-2	Engels
Titel	Proceedings of the 22nd Euromicro Conference on Digital System Design
Redacteuren	Nikos Konofaos, Paris Kitsos
Plaats van productie	Piscataway
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	606-609
Aantal pagina's	4
ISBN van elektronische versie	978-1-7281-2862-7
DOI's	https://doi.org/10.1109/DSD.2019.00093
Status	Gepubliceerd - 24 jun. 2019
Evenement	Euromicro Conference on Digital System Design - Kallithea, Kallithea, Chalkidiki, Griekenland Duur: 28 aug. 2019 → 30 aug. 2019 Congresnummer: 22 http://dsd-seaa2019.csd.auth.gr/

Congres

Congres	Euromicro Conference on Digital System Design
Verkorte titel	DSD 2019
Land/Regio	Griekenland
Stad	Kallithea, Chalkidiki
Periode	28/08/19 → 30/08/19
Internet adres	http://dsd-seaa2019.csd.auth.gr/

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10.1109/DSD.2019.00093

arXiv 1906.10037v1Finale auteursversie , 475 KB

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NeMeCo
Corporaal, H. (Project Manager), van Dalfsen, J. (Projectmedewerker), Singh, G. (Projectmedewerker), Chelini, L. (Projectmedewerker), Corda, S. (Projectmedewerker), Stuijk, S. (Projectmedewerker), Sánchez Martín, V. (Project Manager), Jordans, R. (Projectmedewerker), van der Hagen, D. (Project communicatie medewerker) & de Mol-Regels, M. (Project communicatie medewerker)
1/04/16 → 30/09/20
Project: Onderzoek direct

Citeer dit

@inproceedings{39593e33d64341609f795328ce3ac87f,

title = "Platform independent software analysis for near memory computing",

abstract = "Near-memory Computing (NMC) promises improved performance for the applications that can exploit the features of emerging memory technologies such as 3D-stacked memory. However, it is not trivial to find such applications and specialized tools are needed to identify them. In this paper, we present PISA-NMC, which extends a state-of-the-art hardware agnostic profiling tool with metrics concerning memory and parallelism, which are relevant for NMC. The metrics include memory entropy, spatial locality, data-level, and basic-block-level parallelism. By profiling a set of representative applications and correlating the metrics with the application's performance on a simulated NMC system, we verify the importance of those metrics. Finally, we demonstrate which metrics are useful in identifying applications suitable for NMC architectures. ",

keywords = "cs.PF, cs.ET, Memory Entropy, LLVM, NMC, Spatial Locality, Data-Level Parallelism",

author = "Stefano Corda and Gagandeep Singh and Awan, {Ahsan Javed} and Roel Jordans and Henk Corporaal",

year = "2019",

month = jun,

day = "24",

doi = "10.1109/DSD.2019.00093",

language = "English",

pages = "606--609",

editor = "Nikos Konofaos and Paris Kitsos",

booktitle = "Proceedings of the 22nd Euromicro Conference on Digital System Design",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "22nd Euromicro Conference on Digital System Design, DSD 2019, DSD 2019 ; Conference date: 28-08-2019 Through 30-08-2019",

url = "http://dsd-seaa2019.csd.auth.gr/",

}

Corda, S, Singh, G, Awan, AJ, Jordans, R & Corporaal, H 2019, Platform independent software analysis for near memory computing. in N Konofaos & P Kitsos (uitgave), Proceedings of the 22nd Euromicro Conference on Digital System Design., 8875040, Institute of Electrical and Electronics Engineers, Piscataway, blz. 606-609, Euromicro Conference on Digital System Design, Kallithea, Chalkidiki, Griekenland, 28/08/19. https://doi.org/10.1109/DSD.2019.00093

Platform independent software analysis for near memory computing. / Corda, Stefano; Singh, Gagandeep; Awan, Ahsan Javed et al.
Proceedings of the 22nd Euromicro Conference on Digital System Design. uitgave / Nikos Konofaos; Paris Kitsos. Piscataway: Institute of Electrical and Electronics Engineers, 2019. blz. 606-609 8875040.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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T1 - Platform independent software analysis for near memory computing

AU - Corda, Stefano

AU - Singh, Gagandeep

AU - Awan, Ahsan Javed

AU - Jordans, Roel

AU - Corporaal, Henk

N1 - Conference code: 22

PY - 2019/6/24

Y1 - 2019/6/24

N2 - Near-memory Computing (NMC) promises improved performance for the applications that can exploit the features of emerging memory technologies such as 3D-stacked memory. However, it is not trivial to find such applications and specialized tools are needed to identify them. In this paper, we present PISA-NMC, which extends a state-of-the-art hardware agnostic profiling tool with metrics concerning memory and parallelism, which are relevant for NMC. The metrics include memory entropy, spatial locality, data-level, and basic-block-level parallelism. By profiling a set of representative applications and correlating the metrics with the application's performance on a simulated NMC system, we verify the importance of those metrics. Finally, we demonstrate which metrics are useful in identifying applications suitable for NMC architectures.

AB - Near-memory Computing (NMC) promises improved performance for the applications that can exploit the features of emerging memory technologies such as 3D-stacked memory. However, it is not trivial to find such applications and specialized tools are needed to identify them. In this paper, we present PISA-NMC, which extends a state-of-the-art hardware agnostic profiling tool with metrics concerning memory and parallelism, which are relevant for NMC. The metrics include memory entropy, spatial locality, data-level, and basic-block-level parallelism. By profiling a set of representative applications and correlating the metrics with the application's performance on a simulated NMC system, we verify the importance of those metrics. Finally, we demonstrate which metrics are useful in identifying applications suitable for NMC architectures.

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BT - Proceedings of the 22nd Euromicro Conference on Digital System Design

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Platform independent software analysis for near memory computing

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