Viability study of SYCL as a unified programming model for heterogeneous systems based on GPUs in bioinformatics

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Bioinformatics and Computational Biology are disciplines that have used GPUs for over two decades to accelerate data processing in computational applications, where CUD A has been the most utilized programming language. However, the exclusive use of CUDA presents a portability issue, as it is only c...

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Autor principal: Costanzo, Manuel
Formato: Articulo Contribucion a revista
Lenguaje:Inglés
Publicado: 2024
Materias:
Ciencias Informáticas
SYCL
bioinformatics
heterogeneous systems
GPU
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/173749
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SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-173749
record_format dspace
spelling I19-R120-10915-1737492024-11-27T20:05:47Z http://sedici.unlp.edu.ar/handle/10915/173749 Viability study of SYCL as a unified programming model for heterogeneous systems based on GPUs in bioinformatics Estudio de viabilidad de SYCL como modelo de programación unificado para sistemas heterogéneos basados en GPUs en bioinformática Costanzo, Manuel 2024-10 2024-11-27T14:40:19Z en Ciencias Informáticas SYCL bioinformatics heterogeneous systems GPU Bioinformatics and Computational Biology are disciplines that have used GPUs for over two decades to accelerate data processing in computational applications, where CUD A has been the most utilized programming language. However, the exclusive use of CUDA presents a portability issue, as it is only compatible with NVIDIA GPUs and not with other heterogeneous architectures, such as AMD or Intel GPUs, or any other type of accelerator. To address this portability challenge, the Khronos Group recently introduced the SYCL standard, a multi-platform programming model that offers a high-level programming interface. This standard facilitates the development of portable applications that can efficiently leverage the capabilities of different hardware devices, such as NVIDIA, Intel, and AMD GPUs, without needing significant modifications to the source code. Therefore, this thesis set out as its general objective to evaluate the feasibility of SYCL as a unified, portable, and efficient heterogeneous programming model for the design and development of computationally demanding applications on heterogeneous GPU-based systems, specifically in the field of bioinformatics. Initially, a detailed investigation was conducted about heterogeneous programming models, performance metrics, and bioinformatics concepts, in order to establish the theoretical foundations of this thesis. Then, the SW# suite was chosen as the case study, as it represents a clear example of a CUDA-based bioinformatics application for biological sequence alignment. Using the SYCLomatic tool, a complete migration of the CUDA code to SYCL was carried out, which involved modifying the generated code and solving runtime errors. Additionally, the functionality was verified, optimizations were applied, and the resulting SYCL code was standardized to be compatible with other SYCL implementations. Subsequently, multiple experiments were conducted to evaluate the functionality and performance portability of the software migrated to SYCL. These experiments involved running the application on a wide variety of HPC platforms, including different CPUs and GPUs from various manufacturers. The results obtained demonstrated performance comparable to CUDA in most configurations, confirming the effectiveness of SY CL. Moreover, good performance portability across platforms was observed due to SYCL's ability to run on various hardware combinations. Furthermore, performance remained consistent when switching SYCL implementations. In conclusion, this study demonstrates that SYCL is a viable alternative as a unified, portable, and efficient programming model in the context of heterogeneous computing with GPUs for bioinformatics applications. The findings of this study lay the groundwork for the transition of legacy applications and the development of new solutions leveraging the capabilities of SYCL. En "Documentos relacionados" se encuentra el enlace al texto completo de la tesis. Facultad de Informática Articulo Contribucion a revista http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 193-194
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
SYCL
bioinformatics
heterogeneous systems
GPU
spellingShingle Ciencias Informáticas
SYCL
bioinformatics
heterogeneous systems
GPU
Costanzo, Manuel
Viability study of SYCL as a unified programming model for heterogeneous systems based on GPUs in bioinformatics
topic_facet Ciencias Informáticas
SYCL
bioinformatics
heterogeneous systems
GPU
description Bioinformatics and Computational Biology are disciplines that have used GPUs for over two decades to accelerate data processing in computational applications, where CUD A has been the most utilized programming language. However, the exclusive use of CUDA presents a portability issue, as it is only compatible with NVIDIA GPUs and not with other heterogeneous architectures, such as AMD or Intel GPUs, or any other type of accelerator. To address this portability challenge, the Khronos Group recently introduced the SYCL standard, a multi-platform programming model that offers a high-level programming interface. This standard facilitates the development of portable applications that can efficiently leverage the capabilities of different hardware devices, such as NVIDIA, Intel, and AMD GPUs, without needing significant modifications to the source code. Therefore, this thesis set out as its general objective to evaluate the feasibility of SYCL as a unified, portable, and efficient heterogeneous programming model for the design and development of computationally demanding applications on heterogeneous GPU-based systems, specifically in the field of bioinformatics. Initially, a detailed investigation was conducted about heterogeneous programming models, performance metrics, and bioinformatics concepts, in order to establish the theoretical foundations of this thesis. Then, the SW# suite was chosen as the case study, as it represents a clear example of a CUDA-based bioinformatics application for biological sequence alignment. Using the SYCLomatic tool, a complete migration of the CUDA code to SYCL was carried out, which involved modifying the generated code and solving runtime errors. Additionally, the functionality was verified, optimizations were applied, and the resulting SYCL code was standardized to be compatible with other SYCL implementations. Subsequently, multiple experiments were conducted to evaluate the functionality and performance portability of the software migrated to SYCL. These experiments involved running the application on a wide variety of HPC platforms, including different CPUs and GPUs from various manufacturers. The results obtained demonstrated performance comparable to CUDA in most configurations, confirming the effectiveness of SY CL. Moreover, good performance portability across platforms was observed due to SYCL's ability to run on various hardware combinations. Furthermore, performance remained consistent when switching SYCL implementations. In conclusion, this study demonstrates that SYCL is a viable alternative as a unified, portable, and efficient programming model in the context of heterogeneous computing with GPUs for bioinformatics applications. The findings of this study lay the groundwork for the transition of legacy applications and the development of new solutions leveraging the capabilities of SYCL.
format Articulo
Contribucion a revista
author Costanzo, Manuel
author_facet Costanzo, Manuel
author_sort Costanzo, Manuel
title Viability study of SYCL as a unified programming model for heterogeneous systems based on GPUs in bioinformatics
title_short Viability study of SYCL as a unified programming model for heterogeneous systems based on GPUs in bioinformatics
title_full Viability study of SYCL as a unified programming model for heterogeneous systems based on GPUs in bioinformatics
title_fullStr Viability study of SYCL as a unified programming model for heterogeneous systems based on GPUs in bioinformatics
title_full_unstemmed Viability study of SYCL as a unified programming model for heterogeneous systems based on GPUs in bioinformatics
title_sort viability study of sycl as a unified programming model for heterogeneous systems based on gpus in bioinformatics
publishDate 2024
url http://sedici.unlp.edu.ar/handle/10915/173749
work_keys_str_mv AT costanzomanuel viabilitystudyofsyclasaunifiedprogrammingmodelforheterogeneoussystemsbasedongpusinbioinformatics
AT costanzomanuel estudiodeviabilidaddesyclcomomodelodeprogramacionunificadoparasistemasheterogeneosbasadosengpusenbioinformatica
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