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

研究人员可以使用的数据集越来越多，既有专门的实验创建的，也有作为网络和推特文本档案从互联网上收集的。在这两种情况下，数据生产的增长速度都快于用标准的基于CPU的计算机分析它们所需的资源。基于GPU的新型计算机主要是由英特尔的NVIDIA和Xeon-Phi系统为游戏开发的，它们为计算机增加了协处理器功能，允许使用每个主板上的数百个专用处理器进行更快速的数据处理。使用这些硬件开发提供的新计算模型意味着提供了一种在集群中使用具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和对主机和协处理器的要求，资源允许集群调度器将这些计算机用作混合集群的一部分。有了这个调度器，扩展现有集群以使用主要基于协处理器的系统将是很容易的，如果问题是它们确实加速了。这将使希望处理超大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成本。

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.