Scheduler demonstrator for a parallel processor based computer cluster: STFC Global Challenges Concepts Fund

基于并行处理器的计算机集群的调度程序演示器：STFC 全球挑战概念基金

• 批准号: ST/M001458/1
• 负责人: David Hutchcroft
• 金额: $ 3.62万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FM001458%2F1
• 关键词: Scheduler; demonstrator; parallel; processor; based

There are increasingly large data sets available to researchers, both created by dedicated experiments and collected fromthe internet as web and twitter textual archives. In both cases the rate of increase of data production is growing faster thanthe resources to analyse them with standard CPU based computers. New computer models based on GPUs that weredeveloped for gaming primarily by NVidia and Xeon-phi systems from Intel add co-processor capabilities to computers thatallow much more rapid data processing using the hundreds of dedicated processors on each board.Using the new computing models provided by these hardware developments means providing a way to use the computerswith these co-processor cards in clusters. By demonstrating the code changes required and requirements for host and coprocessorresources allows a cluster scheduler to use these computers as part of a mixed cluster. With this scheduler inplace it will be simple to extend existing clusters to use predominately co-processor based systems if the problem is onethat they do accelerate. This will allow scientists and businesses looking to process very large data sets to optimise thecosts of the computing resources they must buy to achieve this.

研究人员可以使用越来越多的数据集，这些数据集既是通过专门的实验创建的，又是从互​​联网上收集的网络和推特文本档案。在这两种情况下，数据生成的增长率都快于使用基于标准 CPU 的计算机进行分析的资源的增长速度。基于 GPU 的新计算机模型主要由 NVidia 和英特尔的 Xeon-phi 系统开发用于游戏，为计算机添加了协处理器功能，可以使用每块主板上的数百个专用处理器进行更快速的数据处理。这些硬件的发展意味着提供一种在集群中使用带有这些协处理器卡的计算机的方法。通过演示所需的代码更改以及主机和协处理器资源的要求，允许集群调度程序将这些计算机用作混合集群的一部分。有了这个调度程序，如果问题确实需要加速，那么扩展现有集群以使用主要基于协处理器的系统将变得很简单。这将使希望处理非常大的数据集的科学家和企业能够优化他们为实现这一目标而必须购买的计算资源的成本。