English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 56859/90577 (63%)
造访人次 : 12301765      在线人数 : 80
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/92163


    题名: Enhancing Cloud-based Servers by GPU/CPU Virtualization Management
    作者: Wu, Tin-Yu;Lee, Wei-Tsong;Duan, Chien-Yu
    贡献者: 淡江大學電機工程學系
    关键词: Virtual Machine (VM);Multithreading;GPU;CUDA;Mapreduce
    日期: 2012-11-07
    上传时间: 2013-09-12 12:49:24 (UTC+8)
    摘要: This paper proposes to add the multithreaded Graphic Processing Units (GPUs) to some virtual machines (VMs) in the existing cloud-based VM groups. To handle the multidimensional or multithreaded computing that a CPU cannot process quickly by a GPU that has hundreds of Arithmetic Logic Units (ALUs), and to regulate the time for initiating physical servers by real-time thermal migration, our proposed scheme can enhance the system performance and reduce the energy consumption of long-term computing. Four major techniques in this paper include: (1) GPU virtualization, (2) Hypervisor for GPU, (3) Thermal migration implementation, and (4) Estimation of multithreaded tasks. In no matter quantum mechanics, astronomy, fluid mechanics, or atmospheric simulation and prediction, a GPU suits not only parallel multithreaded computing for its tens of times performance than a CPU, but also multidimensional array operations for its excellent efficiency. Therefore, how to distribute the computing performance of CPUs and GPUs appropriately becomes a significant issue. In general cloud computing applications, it is rarely seen that GPUs can outperform CPUs. Furthermore, for groups of virtual servers, many tasks actually can be completed by CPUs without the support of GPUs. Thus, it is a waste of resources to implement GPUs to all physical servers. For this reason, by integrating with the migration characteristic of VMs, our proposed scheme can estimate whether to compute tasks by physical machines with GPUs or not. In estimating tasks, we use Amdahl’s law to estimate the overall performance include communication delays, Synchronization over head and me possible additional burden.
    關聯: Proceedings of the International Computer Symposium ICS 2012, 5p.
    DOI: 10.1007/978-3-642-35473-1_20
    显示于类别:[電機工程學系暨研究所] 會議論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    Enhancing Cloud-based Servers by GPU_CPU Virtualization Management.pdf452KbAdobe PDF480检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈