Scheduling Proxy and Adaptive Algorithms for Irregular Applications on SMP Clusters

对称多处理器集群是实现高性能计算的最经济有效的方法之一.然而，充分发挥其潜力在很大程度上依赖于有效的集群范围的资源管理系统。这个项目的重点是SMP集群上的不规则应用程序的运行时调度技术。由于SNIP集群采用的是分层结构，因此，由于SNIP集群的存储器层次结构的深度以及每一层上不同的访问原语和开销，使得集群上的动态调度成为一个挑战，本项目的第一个目标是开发调度代理架构，以利用集群的分层结构。该体系结构静态或动态地指定每个SMP中的一个处理器，用于在节点之间进行调度。调度代理均衡了与网络容量成比例的工作负载，增强了通信的局部性.调度代理架构便于在节点之间使用分布式调度算法。这个项目的第二个目标是开发参数算法，基于现有的大规模并行计算机，以反映可能的异质性的节点和通信链路。主要任务是严格分析参数算法的自适应性。调度代理结构和自适应算法减轻了并行编程的负担，保证了集群计算的效率。

Clusters of symmetric multiprocessors (SMPs) are emerging as one of the most cost- effective ways for high performance computing. However, delivering their full potential heavily relies on efficient cluster-wide resource management systems. This project focuses on run-time scheduling techniques for irregular applications on SMP clusters. Since an SNIP cluster deploys a hierarchical organization, it is the depth of the memory hierarchy with its different access primitives and costs at each level that makes dynamic scheduling on the cluster challenge.The first objective of this project is to develop scheduling proxy architecture to take advantage of the hierarchical organization of the clusters. The architecture designates one of the processors in each SMP, either statically or dynamically, for scheduling among the nodes. The scheduling proxy balances the workload in proportional to the nodalcapacities and enhances the communication locality. The scheduling proxy architecture facilitates the use of distributed scheduling algorithms between the nodes. The second objective of this project is to develop parametric algorithms, based on existing ones for massively parallel computers, to reflect the possible heterogeneity of the nodes and the communication links. Major undertaking is a rigid analysis of the adaptivity of the parametric algorithms. The scheduling proxy architecture and adaptive algorithms ease the burden of parallel programming and ensure the efficiency of cluster computing.