Optimisation opportunities and evaluation for GPGPU applications on low-end mobile GPUs

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/106767

dc.contributor	Barcelona Supercomputing Center
dc.contributor.author	Trompouki, Matina M.
dc.contributor.author	Kosmidis, Leonidas
dc.date	2017-05-15
dc.identifier.citation	Trompouki, M. M.; Kosmidis, L. Optimisation opportunities and evaluation for GPGPU applications on low-end mobile GPUs. A: "Design, Automation Test in Europe Conference Exhibition (DATE), 2017". Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 950-953.
dc.identifier.citation	978-3-9815370-8-6
dc.identifier.citation	10.23919/DATE.2017.7927128
dc.identifier.uri	http://hdl.handle.net/2117/106767
dc.language.iso	eng
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation	http://ieeexplore.ieee.org/document/7927128/
dc.relation	info:eu-repo/grantAgreement/ES/1PE/TIN2015-65316-P
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Enginyeria electrònica
dc.subject	GPUs (Graphics processing units)
dc.subject	Optimization and computation series
dc.subject	Kernel
dc.subject	Graphics processing units
dc.subject	Optimization
dc.subject	Mobile communication
dc.subject	Benchmark testing
dc.subject	Memory management
dc.subject	Rendering (computer graphics)
dc.subject	Supercomputadors
dc.title	Optimisation opportunities and evaluation for GPGPU applications on low-end mobile GPUs
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	Previous works in the literature have shown the feasibility of general purpose computations for non-visual applications on low-end mobile graphics processors using graphics APIs. These works focused only on the functional aspects of the software, ignoring the implementation details and therefore their performance implications due to their particular micro-architecture. Since various steps in such applications can be implemented in multiple ways, we identify optimisation opportunities, explore the different options and evaluate them. We show that the implementation details can significantly affect the obtained performance with discrepancies up to 3 orders of magnitude and we demonstrate the effectiveness of our proposal on two embedded platforms, obtaining more than 16× speedup over benchmarks designed following OpenGL ES 2 best practices.
dc.description.abstract	This work has been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence.
dc.description.abstract	Peer Reviewed

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