Reliability Evaluation of LU Decomposition on GPU-Accelerated System-on-Chip Under Proton Irradiation
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Otros documentos de la autoría: Badía, José; León, Germán; BELLOCH, JOSE A.; LINDOSO, ALMUDENA; García Valderas, Mario; Morilla, Yolanda; Entrena, Luis
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Título
Reliability Evaluation of LU Decomposition on GPU-Accelerated System-on-Chip Under Proton IrradiationAutoría
Fecha de publicación
2022-03-22Editor
IEEECita bibliográfica
J. M. Badia et al., "Reliability Evaluation of LU Decomposition on GPU-Accelerated System-on-Chip Under Proton Irradiation," in IEEE Transactions on Nuclear Science, vol. 69, no. 7, pp. 1467-1474, July 2022, doi: 10.1109/TNS.2022.3155820.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://ieeexplore.ieee.org/document/9724279Versión
info:eu-repo/semantics/acceptedVersionPalabras clave / Materias
Resumen
Graphic processing units (GPUs) have become a basic accelerator both in high-performance nodes and low-power system-on-chip (SoC). They provide massive data parallelism and very high performance per watt. However, ... [+]
Graphic processing units (GPUs) have become a basic accelerator both in high-performance nodes and low-power system-on-chip (SoC). They provide massive data parallelism and very high performance per watt. However, their reliability in harsh environments is an important issue to take into account, especially for safety-critical applications. In this article, we evaluate the influence of the parallelization strategy on the reliability of lower–upper (LU) decomposition on a GPU-accelerated SoC under proton irradiation. Specifically, we compare a memory bound and a compute bound implementation of the decomposition on a K20A GPU embedded on a Tegra K1 (TK1) SoC. We leverage the GPU and CPU clock frequencies both to highlight the radiation sensitivity of the GPU where we are running the benchmark and also to apply both algorithms to solve problems with the same size when exposed to the same radiation dose. Results show that more intensive use of the resources of the GPU increases the cross section. We also observed that most of the radiation-induced errors hang the operating system and even the rebooting process. Finally, we present a preliminary study of the error propagation of the LU decomposition algorithms. [-]
Publicado en
IEEE Transactions on Nuclear Science. Volume: 69, Issue: 7, July 2022Entidad financiadora
Universitat Jaume I | Generalitat Valenciana | Gobierno Regional de Madrid | Ministerio de Ciencia, Innovación y Universidades (Spain)
Código del proyecto o subvención
UJIB2019-36 | PROMETEO/2019/109 | MIMACUHSPACECM-UC3M (2022/00024/001) | PID2019-106455GB-C21 | PID2020-113656RB-C21
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