Programming GPU Clusters with Shared Memory Abstraction in Software

Karantasis, Konstantinos I.; Polychronopoulos, Eleftherios D.

doi:10.1109/pdp.2011.91

Cited by 9 publications

(5 citation statements)

References 24 publications

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“…Thus, many solutions have attempted to simplify the development efforts required for such approaches. For instance, Karantasis and Polychronopoulos, presented an extension of the Pleiad middleware, used by Java developers to work with a local GPU abstraction over several nodes with between one and four GPU boards each. Distributed Storage: Many middleware systems implement user‐typed object storage, but few of them implement distributed data structures as part of a unified Application Programming Interface (API) . Developers typically implement distributed storage using a specific framework or middleware such as HBase , Cassandra , Apache Pig , ScyllaDB , or MongoDB .…”

Section: Gpdc Middleware Requirementsmentioning

confidence: 99%

“…Programming GPU clusters via a DSM abstraction offered by a middleware layer is a promising solution for some specific problems, eg, SIMD problems. An extension of the Pleiad middleware was implemented in the work of Karantasis and Polychronopoulos, enabling Java developers to work with a local GPU abstraction over several nodes equipped with between one and four GPU boards each.…”

Section: Related Workmentioning

confidence: 99%

“…problems. An extension of the Pleiad middleware 24 was implemented in the work of Karantasis and Polychronopoulos, 23 enabling Java developers to work with a local GPU abstraction over several nodes equipped with between one and four GPU boards each.…”

Section: Apachementioning

confidence: 99%

Section: Gpdc Middleware Requirementsmentioning

confidence: 99%

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A general‐purpose distributed computing Java middleware

Almeida

Cimino

Resende

et al. 2018

Concurrency and Computation

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Summary The middleware solutions for General‐Purpose Distributed Computing (GPDC) have distinct requirements, such as task scheduling, processing/storage fault tolerance, code portability for parallel or distributed environments, simple deployment (including over grid or multi‐cluster environments), collaborative development, low code refactoring, native support for distributed data structures, asynchronous task execution, and support for distributed global variables. These solutions do not integrate these requirements into a single deployment with a unique API exposing most of these requirements to users. The consequence is the utilization of several solutions with their particularities, thus requiring different user skills. Besides that, the users have to solve the integration and all heterogeneity issues. To reduce this integration gap, in this paper, we present Java Cá&Lá (JCL), a distributed‐shared‐memory and task‐oriented lightweight middleware for the Java community that separates business logic from distribution issues during the development process and incorporates several requirements that were presented separately in the GPDC middleware literature over the last few decades. JCL allows building distributed or parallel applications with only a few portable API calls, thus reducing the integration problems. Finally, it also runs on different platforms, including small single‐board computers. This work compares and contrasts JCL with other Java middleware systems and reports experimental evaluations of JCL applications in several distinct scenarios.

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Section: Gpdc Middleware Requirementsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Apachementioning

confidence: 99%

Section: Gpdc Middleware Requirementsmentioning

confidence: 99%

See 2 more Smart Citations

A general‐purpose distributed computing Java middleware

Almeida

Cimino

Resende

et al. 2018

Concurrency and Computation

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show abstract

“…Single Instruction Multiple Data (SIMD) solutions. In (Karantasis and Polychronopoulos, 2011), an extension of Pleiad middleware (Karantasis and Polychronopoulos, 2009) is implemented enabling Java developers to work with a local GPU abstraction over several machines with one-four GPU devices each.…”

Section: Related Workmentioning

confidence: 99%

An Evaluation of the Challenges of Multilingualism in Data Warehouse Development

Dediź

Stanier

2016

Proceedings of the 18th International Conference on Enterprise Information Systems

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ICEIS 2016 received 257 paper submissions from 42 countries in all continents, which makes it one of the largest conferences in the World in the area of Information Systems, thus demonstrating the success and global dimension of this conference. From these, 42 papers were selected for publication and presentation at the Conference as full papers. These numbers, leading to a full-paper acceptance ratio of 16%, show the intention of preserving a high quality forum for this conference, a quality that we intend to maintain in the future, for the next editions of this conference.The high number and high quality of the received papers imposed difficult choices in the selection process. To evaluate each submission, a double blind paper review was performed by the Program Committee, whose members are highly qualified researchers in ICEIS topic areas.All presented papers will be available at the SCITEPRESS Digital Library and will be submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), INSPEC, DBLP, EI (Elsevier Index) and Scopus.Additionally, a short list of presented papers will be selected to be expanded into a forthcoming book of ICEIS 2016 Selected Papers to be published by Springer in the LNBIP Series.The technical program of the conference included a panel and 4 invited talks delivered by internationally distinguished speakers, namely: Claudia Loebbecke (University of Cologne, Germany), Sergio Gusmeroli (TXT e-solutions SPA, Italy), Wil Van Der Aalst (Technische Universiteit Eindhoven, Netherlands) and Jan Vom Brocke (University of Liechtenstein, Liechtenstein). Their participation positively contributes to reinforce the overall quality of the Conference and to provide a deeper understanding of the fields addressed by the conference.Moreover, ICEIS 2016 had a Doctoral Consortium on Enterprise Information Systems and 1 tutorial. We are thankful to the Conference Co-chairs (Olivier Camp and José Cordeiro) and Program Co-chairs (Slimane Hammoudi, Leszek Maciaszek and Michele M. Missikoff) for their dedication and hard work in organizing these events.We sincerely thank all the authors for their submissions and participation in ICEIS 2016. Furthermore, we would like to thank all the members of the program committee and reviewers, who helped us with their expertise, dedication and time. We would also like to thank the invited speakers for their excellent contribution in sharing their knowledge and vision and the workshop/special session chairs whose collaboration with ICEIS 2015 was much appreciated. Finally, we gratefully acknowledge the professional support of the ICEIS 2016 team for all organizational processes. XIIIWe hope that all colleagues find this a fruitful and inspiring conference. We hope to contribute to the development of the Enterprise Information Systems community and look forward to having additional research results presented at the next edition of ICEIS, details of which are available at http://www.iceis.org. Slimane Hammoudi University of Cologne, GermanyAbstract:...

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Enabling Highly Efficient k-Means Computations on the SW26010 Many-Core Processor of Sunway TaihuLight

Yang

Sun

et al. 2019

J. Comput. Sci. Technol.

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Programming GPU Clusters with Shared Memory Abstraction in Software

Cited by 9 publications

References 24 publications

A general‐purpose distributed computing Java middleware

A general‐purpose distributed computing Java middleware

An Evaluation of the Challenges of Multilingualism in Data Warehouse Development

Enabling Highly Efficient k-Means Computations on the SW26010 Many-Core Processor of Sunway TaihuLight

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