课题基金 / 基金详情

CSR-AES: Characterizing the Cooperative Parallel Behavior of GPUs and Multicore CPUs

CSR-AES: Characterizing the Cooperative Parallel Behavior of GPUs and Multicore CPUs
CSR-AES:表征 GPU 和多核 CPU 的协作并行行为
批准号:
0720848
负责人:
Michael Bailey
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-10-01 至 2009-09-30

项目摘要

项目成果

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中文摘要
翻译
通过提高时钟速度来提高微处理器的性能已不再实用。作为回应,微处理器制造商选择通过使用多处理来提高性能。通过用多个不太复杂的处理器填充单个芯片,制造商正在创造提供每瓦特和每平方毫米更高计算性能的CPU。与此同时,尽管GPU芯片解决了不同形式的计算问题,但它们使用相同的思想极大地提高了它们的综合性能。本项目将这两种互补资源作为一个单一的协作执行系统进行研究。它描述了如何最大限度地利用每一种优势,并确定?最佳点?根据正在计算的内容的性质和大小,将不同的计算功能分配给适当的处理单元。它不只是针对某一特定问题产生最优解,而是从数据计算的类型和大小、CPU和GPU的速度、CPU和GPU处理器的数量以及总线速度等方面对整个问题进行概括。用于解决计算密集型科学和渲染问题。由于它的多核CPU/GPU组合,它将拥有比任何台式机前身更强的组合计算能力,但它将把应用程序开发人员视为单一计算环境。最重要的是,它不会比用户无论如何都会购买的图形桌面系统有更多的成本和占用空间。
英文摘要
Improving the performance of microprocessors by increasing the clock speed is no longer practical. In response, microprocessor manufacturers have chosen to increase performance through the use of multiprocessing. By populating a single die with multiple, less complicated processors, manufacturers are creating CPUs that provide higher computational performance per watt and per square millimeter. At the same time, GPU chips have used the same ideas to vastly improve their aggregate performance, although they address different forms of computational problems.This project is examining these two complementary resources as a single cooperative execution system. It is characterizing how to best take advantage of each, and ascertain the ?sweet spot? of assigning different computational functions to the appropriate processing units based on the nature and size of what is being computed. It will not just produce an optimal point solution for one particular problem, but will generalize the overall problem in terms of: the type and size of the data computation, the speed of the CPUs and GPUs, the number of CPU and GPU processors, and the bus speed.The result of this research will be to create a desktop ?mini-supercomputer? for solving compute-intensive scientific and rendering problems. Because of its multicore CPU/GPU mix, it will have more combined compute power than any of its desktop predecessors, but it will look to an application developer as a single compute environment. Best of all, it will have no more cost and footprint than the graphical desktop system that the user would have bought anyway.
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会议论文
Data Corps Workshop
  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 负责人:
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TWC: TTP Option: Large: Collaborative: Internet-Wide Vulnerability Measurement, Assessment, and Notification
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