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Assessing Opportunities of SYCL for Biological Sequence Alignment on GPU-based Systems

dc.contributor.authorCostanzo, Manuel
dc.contributor.authorRucci, Enzo
dc.contributor.authorNaiouf, Marcelo
dc.contributor.authorGarcía Sánchez, Carlos
dc.contributor.authorPrieto Matías, Manuel
dc.date.accessioned2025-01-10T16:30:45Z
dc.date.available2025-01-10T16:30:45Z
dc.date.issued2024-02-19
dc.description.abstractBioinformatics and Computational Biology are two fields that have been exploiting GPUs for more than two decades, with being CUDA the most used programming language for them. However, as CUDA is an NVIDIA proprietary language, it implies a strong portability restriction to a wide range of heterogeneous architectures, like AMD or Intel GPUs. To face this issue, the Khronos Group has recently proposed the SYCL standard, which is an open, royalty-free, cross-platform abstraction layer, that enables the programming of a heterogeneous system to be written using standard, single-source C++ code. Over the past few years, several implementations of this SYCL standard have emerged, being oneAPI the one from Intel. This paper presents the migration process of the SW# suite, a biological sequence alignment tool developed in CUDA, to SYCL using Intel’s oneAPI ecosystem. The experimental results show that SW# was completely migrated with a small programmer intervention in terms of hand-coding. In addition, it was possible to port the migrated code between different architectures (considering multiple vendor GPUs and also CPUs), with no noticeable performance degradation on 5 different NVIDIA GPUs. Moreover, performance remained stable when switching to another SYCL implementation. As a consequence, SYCL and its implementations can offer attractive opportunities for the Bioinformatics community, especially considering the vast existence of CUDA-based legacy codes.
dc.description.departmentDepto. de Arquitectura de Computadores y Automática
dc.description.facultyFac. de Informática
dc.description.refereedTRUE
dc.description.statuspub
dc.identifier.officialurlhttps://doi.org/10.1007/s11227-024-05907-2
dc.identifier.urihttps://hdl.handle.net/20.500.14352/113792
dc.journal.titleThe Journal of Supercomputing
dc.language.isoeng
dc.rightsAttribution-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/
dc.subject.keywordSYCL
dc.subject.keywordoneAPI
dc.subject.keywordGPU
dc.subject.keywordCUDA
dc.subject.keywordSYCLomatic
dc.subject.keywordBioinformatics
dc.subject.keywordDNA
dc.subject.keywordProtein
dc.subject.keywordSequence alignment
dc.subject.ucmCiencias
dc.subject.unesco1203.17 Informática
dc.titleAssessing Opportunities of SYCL for Biological Sequence Alignment on GPU-based Systems
dc.typejournal article
dspace.entity.typePublication
relation.isAuthorOfPublicationd04764e1-9d18-42ae-a9e7-c55f9bd50934
relation.isAuthorOfPublication5d3f6717-1495-4217-853c-8c9c75d56620
relation.isAuthorOfPublication.latestForDiscoveryd04764e1-9d18-42ae-a9e7-c55f9bd50934

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