Exploiting GPUs in Virtual Machine for BioCloud.

Recently, biological applications start to be reimplemented into the applications which exploit many cores of GPUs for better computation performance. Therefore, by providing virtualized GPUs to VMs in cloud computing environment, many biological applications will willingly move into cloud environme...

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Detalles Bibliográficos
Publicado en:BioMed Research International Vol. 2013; pp. 939460 - 939461
Autores principales: Jo, Heeseung, Jeong, Jinkyu, Lee, Myoungho, Choi, Dong Hoon
Formato: Journal Article
Publicado: Wiley-Blackwell 2013
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Wiley-Blackwell
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        atl: Exploiting GPUs in Virtual Machine for BioCloud.
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          Jo, Heeseung
          Jeong, Jinkyu
          Lee, Myoungho
          Choi, Dong Hoon
        affil: Department of Information Technology, Chonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si, Jeollabuk-do 561-756, Republic of Korea.
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          Computers and Computerization
          Software
          Algorithms
      ab: Recently, biological applications start to be reimplemented into the applications which exploit many cores of GPUs for better computation performance. Therefore, by providing virtualized GPUs to VMs in cloud computing environment, many biological applications will willingly move into cloud environment to enhance their computation performance and utilize infinite cloud computing resource while reducing expenses for computations. In this paper, we propose a BioCloud system architecture that enables VMs to use GPUs in cloud environment. Because much of the previous research has focused on the sharing mechanism of GPUs among VMs, they cannot achieve enough performance for biological applications of which computation throughput is more crucial rather than sharing. The proposed system exploits the pass-through mode of PCI express (PCI-E) channel. By making each VM be able to access underlying GPUs directly, applications can show almost the same performance as when those are in native environment. In addition, our scheme multiplexes GPUs by using hot plug-in/out device features of PCI-E channel. By adding or removing GPUs in each VM in on-demand manner, VMs in the same physical host can time-share their GPUs. We implemented the proposed system using the Xen VMM and NVIDIA GPUs and showed that our prototype is highly effective for biological GPU applications in cloud environment.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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