Multiple-tasks on multiple-devices (MTMD): exploiting concurrency in heterogeneous managed runtimes
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| Názov: | Multiple-tasks on multiple-devices (MTMD): exploiting concurrency in heterogeneous managed runtimes |
|---|---|
| Autori: | Michail Papadimitriou, Eleni Markou, Juan Fumero, Athanasios Stratikopoulos, Florin Blanaru, Christos Kotselidis |
| Informácie o vydavateľovi: | Zenodo |
| Rok vydania: | 2021 |
| Zbierka: | Zenodo |
| Predmety: | Software engineering, Software organisation and properties, Contextual software domains, Software infrastructure, Virtual machines |
| Popis: | Modern commodity devices are nowadays equipped with a plethora of heterogeneous devices serving different purposes. Being able to exploit such heterogeneous hardware accelerators to their full potential is of paramount importance in the pursuit of higher performance and energy efficiency. Towards these objectives, the reduction of idle time of each device as well as the concurrent program execution across different accelerators can lead to better scalability within the computing platform. In this work, we propose a novel approach for enabling a Java-based heterogeneous managed runtime to automatically and efficiently deploy multiple tasks on multiple devices. We extend TornadoVM with parallel execution of bytecode interpreters to dynamically and concurrently manage and execute arbitrary tasks across multiple OpenCL-compatible devices. In addition, in order to achieve an efficient device-task allocation, we employ a machine learning approach with a multiple-classification architecture of Extra-Trees-Classifiers. Our proposed solution has been evaluated over a suite of 12 applications split into three different groups. Our experimental results showcase performance improvements up 83% compared to all tasks running on the single best device, while reaching up to 91% of the oracle performance. |
| Druh dokumentu: | conference object |
| Jazyk: | unknown |
| Relation: | https://zenodo.org/communities/eu/; https://zenodo.org/records/7574514; oai:zenodo.org:7574514; https://doi.org/10.1145/3453933.3454019 |
| DOI: | 10.1145/3453933.3454019 |
| Dostupnosť: | https://doi.org/10.1145/3453933.3454019 https://zenodo.org/records/7574514 |
| Rights: | Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode |
| Prístupové číslo: | edsbas.C021D3DC |
| Databáza: | BASE |
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| Items | – Name: Title Label: Title Group: Ti Data: Multiple-tasks on multiple-devices (MTMD): exploiting concurrency in heterogeneous managed runtimes – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Michail+Papadimitriou%22">Michail Papadimitriou</searchLink><br /><searchLink fieldCode="AR" term="%22Eleni+Markou%22">Eleni Markou</searchLink><br /><searchLink fieldCode="AR" term="%22Juan+Fumero%22">Juan Fumero</searchLink><br /><searchLink fieldCode="AR" term="%22Athanasios+Stratikopoulos%22">Athanasios Stratikopoulos</searchLink><br /><searchLink fieldCode="AR" term="%22Florin+Blanaru%22">Florin Blanaru</searchLink><br /><searchLink fieldCode="AR" term="%22Christos+Kotselidis%22">Christos Kotselidis</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: Zenodo – Name: DatePubCY Label: Publication Year Group: Date Data: 2021 – Name: Subset Label: Collection Group: HoldingsInfo Data: Zenodo – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Software+engineering%22">Software engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Software+organisation+and+properties%22">Software organisation and properties</searchLink><br /><searchLink fieldCode="DE" term="%22Contextual+software+domains%22">Contextual software domains</searchLink><br /><searchLink fieldCode="DE" term="%22Software+infrastructure%22">Software infrastructure</searchLink><br /><searchLink fieldCode="DE" term="%22Virtual+machines%22">Virtual machines</searchLink> – Name: Abstract Label: Description Group: Ab Data: Modern commodity devices are nowadays equipped with a plethora of heterogeneous devices serving different purposes. Being able to exploit such heterogeneous hardware accelerators to their full potential is of paramount importance in the pursuit of higher performance and energy efficiency. Towards these objectives, the reduction of idle time of each device as well as the concurrent program execution across different accelerators can lead to better scalability within the computing platform. In this work, we propose a novel approach for enabling a Java-based heterogeneous managed runtime to automatically and efficiently deploy multiple tasks on multiple devices. We extend TornadoVM with parallel execution of bytecode interpreters to dynamically and concurrently manage and execute arbitrary tasks across multiple OpenCL-compatible devices. In addition, in order to achieve an efficient device-task allocation, we employ a machine learning approach with a multiple-classification architecture of Extra-Trees-Classifiers. Our proposed solution has been evaluated over a suite of 12 applications split into three different groups. Our experimental results showcase performance improvements up 83% compared to all tasks running on the single best device, while reaching up to 91% of the oracle performance. – Name: TypeDocument Label: Document Type Group: TypDoc Data: conference object – Name: Language Label: Language Group: Lang Data: unknown – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://zenodo.org/communities/eu/; https://zenodo.org/records/7574514; oai:zenodo.org:7574514; https://doi.org/10.1145/3453933.3454019 – Name: DOI Label: DOI Group: ID Data: 10.1145/3453933.3454019 – Name: URL Label: Availability Group: URL Data: https://doi.org/10.1145/3453933.3454019<br />https://zenodo.org/records/7574514 – Name: Copyright Label: Rights Group: Cpyrght Data: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode – Name: AN Label: Accession Number Group: ID Data: edsbas.C021D3DC |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1145/3453933.3454019 Languages: – Text: unknown Subjects: – SubjectFull: Software engineering Type: general – SubjectFull: Software organisation and properties Type: general – SubjectFull: Contextual software domains Type: general – SubjectFull: Software infrastructure Type: general – SubjectFull: Virtual machines Type: general Titles: – TitleFull: Multiple-tasks on multiple-devices (MTMD): exploiting concurrency in heterogeneous managed runtimes Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Michail Papadimitriou – PersonEntity: Name: NameFull: Eleni Markou – PersonEntity: Name: NameFull: Juan Fumero – PersonEntity: Name: NameFull: Athanasios Stratikopoulos – PersonEntity: Name: NameFull: Florin Blanaru – PersonEntity: Name: NameFull: Christos Kotselidis IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2021 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
| ResultId | 1 |