XPS: CLCCA: Scalable Parallelism for Irregular and Graph Applications

不规则应用程序对计算机行业的重要性日益增加。长期以来，它们一直支撑着联邦政府国家安全部门的利益计算。但现在，它们支撑着诸如社交网络中的广告位置，以及医学和科学中复杂数据集的分析等问题。例如，开发定制药物疗法需要分析细胞途径、已知药物/患者结果以及特定患者的DNA如何相互作用。这些复杂的大数据问题需要新的计算模型，以便在商用硬件上有效地执行。这些应用程序的定义特征是局部性差和大量可用并行性。关键思想是使用可用的并发性来容忍内存延迟，而不是依赖于局域性。使用高度优化的运行时系统，并针对商用处理器和网络硬件进行了调优，结果表明，这些应用程序的可伸缩性能可以超过定制的超级计算机级硬件。目前正在进行的研究是继续探索和开发这种容忍延迟的横向扩展运行时系统。提出的研究方向包括探索减轻磁盘（SSD）访问延迟的方法，以便在小型商用硬件集群上解决pb级问题。此外，该研究还将研究可编程路由器硬件，以便将网络聚合扩展到千个节点以上的集群范围。最后，研究工作将集中在增强的语言语义和编译器技术上，使其更容易实现科学、商业、医疗和政府社区感兴趣的分析类型和图形算法。

Irregular applications are increasing in importance to the computing industry. For a long time they have underpinned computations of interest to the national security arm of the federal government. But now, they underpin such questions as ad placement in social networks, and analysis of complex data-sets in medicine and science. For example, developing custom drug therapies involves analysis of how cellular pathways, known drug/patient outcomes, and a particular patient's DNA interact. These complex big-data problems require new computational models in order to execute effectively on commodity hardware. The defining characteristic of these applications is poor locality and massive available parallelism. The key idea is use the available concurrency to tolerate memory latency, instead of relying on locality. Using a highly optimized runtime system, tuned for use on commodity processors and networking hardware it has been shown that scalable performance on these applications can exceed custom supercomputer-class hardware.The research currently being undertaken is to continue exploring and developing this latency tolerant scale-out runtime system. The proposed research directions include exploring ways to mitigate latency for disk (SSD) access, in order to tackle petabyte-scale problems on small clusters of commodity hardware. In addition the research will examine programmable router hardware in order to scale network aggregation into the thousand-node-plus cluster range. Finally the research effort will focus on enhanced language semantics and compiler techniques that make it easier to implement the types of analyses and graph algorithms of interest to the scientific, business, medical, and government communities.