KAAPI: A thread scheduling runtime system for data flow computations on cluster of multi-processors
KAAPI: A thread scheduling runtime system for data flow computations on cluster of multi-processors
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KAAPI：用于多处理器集群上数据流计算的线程调度运行时系统
DOI：
10.1145/1278177.1278182
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
L. Pigeon
中科院分区：
文献类型：
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作者：
T. Gautier;Xavier Besseron;L. Pigeon
计算机科学的多处理器群集的可用性似乎对工程师非常有吸引力，因为在第一级，此类计算机汇总了高性能。然而，在计算机代数问题（例如计算机代数问题）上获得不规则应用程序的最高表现仍然是一个具有挑战性的问题。访问内存的延迟是不统一的，计算的不规则性需要使用调度算法，以便自动平衡处理器之间的工作负载。
本文着重于运行时支持实现，以极大地利用多处理器群集的计算资源。我们方法的独创性依赖于基于POSIX线程接口的次要扩展，用于实施有效的偷窃算法，以进行宏数据流计算。
The high availability of multiprocessor clusters for computer science seems to be very attractive to the engineer because,at a first level, such computers aggregate high performances. Nevertheless, obtaining peak performances on irregular applications such as computer algebra problems remains a challenging problem. The delay to access memory is non uniform and the irregularity of computations requires to use scheduling algorithms in order to automatically balance the workload among the processors.
This paper focuses on the runtime support implementation to exploit with great efficiency the computation resources of a multiprocessor cluster. The originality of our approach relies on the implementation of an efficient work-stealing algorithm for a macro data flow computation based on minor extension of POSIX thread interface.