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Evaluation of Java for General Purpose GPU Computing

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Bibliographic Details
Title: Evaluation of Java for General Purpose GPU Computing
Authors: Jorge Docampo, Sabela Ramos, Guillermo L. Taboada, Roberto R. Expósito
Contributors: The Pennsylvania State University CiteSeerX Archives
Source: http://www.des.udc.es/%7Ejuan/papers/eoops2013.pdf.
Collection: CiteSeerX
Description: —The presence of many-core units as accelerators has been increasing due to their ability to improve the per-formance of highly parallel workloads. General Purpose GPU (GPGPU) computing has allowed the graphical units to emerge as successful co-processors that can be employed to improve the performance of many different non-graphical applications with high parallel requirements, which make them suitable for many High Performance Computing workloads. While the main libraries developed to exploit the massive parallel capacity of GPUs are oriented to C/C++ programmers, there have been several efforts to extend this support to other languages. Among them, Java stands out for being one of the most extended languages and there are multiple projects that try to enable Java to take advantage of GPGPU computing. In this scenario, this paper presents an evaluation of the most relevant among the current solutions that exploit GPGPU computing in Java. Keywords-Java; General Purpose GPU computing (GPGPU); jCuda; Aparapi; High Performance Computing; I.
Document Type: text
File Description: application/pdf
Language: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.9804; http://www.des.udc.es/%7Ejuan/papers/eoops2013.pdf
Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.9804
http://www.des.udc.es/%7Ejuan/papers/eoops2013.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Accession Number: edsbas.5E9C9D84
Database: BASE
Description
Abstract:—The presence of many-core units as accelerators has been increasing due to their ability to improve the per-formance of highly parallel workloads. General Purpose GPU (GPGPU) computing has allowed the graphical units to emerge as successful co-processors that can be employed to improve the performance of many different non-graphical applications with high parallel requirements, which make them suitable for many High Performance Computing workloads. While the main libraries developed to exploit the massive parallel capacity of GPUs are oriented to C/C++ programmers, there have been several efforts to extend this support to other languages. Among them, Java stands out for being one of the most extended languages and there are multiple projects that try to enable Java to take advantage of GPGPU computing. In this scenario, this paper presents an evaluation of the most relevant among the current solutions that exploit GPGPU computing in Java. Keywords-Java; General Purpose GPU computing (GPGPU); jCuda; Aparapi; High Performance Computing; I.