Parallel processing area extraction and data transfer number reduction for automatic GPU offloading of IoT applications

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Detalles Bibliográficos
Publicado en:	arXiv.org (Nov 9, 2018), p. n/a
Autor principal:	Yamato, Yoji
Otros Autores:	Noguchi, Hirofumi, Kataoka, Misao, Isoda, Takuma, Demizu, Tatsuya
Publicado:	Cornell University Library, arXiv.org
Materias:	Parallel processing Data transfer (computers) Performance enhancement Computation Reduction Graphics processing units Electronic devices Central processing units > CPUs
Acceso en línea:	Citation/Abstract Full text outside of ProQuest
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Descripción
Resumen:	For Open IoT, we have proposed Tacit Computing technology to discover the devices that have data users need on demand and use them dynamically and an automatic GPU offloading technology as an elementary technology of Tacit Computing. However, it can improve limited applications because it only optimizes parallelizable loop statements extraction. Thus, in this paper, to improve performances of more applications automatically, we propose an improved method with reduction of data transfer between CPU and GPU. We evaluate our proposed offloading method by applying it to Darknet and find that it can process it 3 times as quickly as only using CPU.
ISSN:	2331-8422
Fuente:	Engineering Database