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Program Graph Structuring for Execution in Dynamic SMP Clusters Using Moldable Tasks

机译:使用可模件任务的动态SMP集群中执行用于执行的程序图

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The paper concerns task scheduling in dynamic SMP clusters based on the notion of moldable computational tasks. Such tasks have been used as atomic elements in program scheduling algorithms with warranty of schedule length. For program execution, a special shared memory system architecture is used. It is based on dynamic processor clusters, organized around shared memory modules by switching of processors between memory module busses. Fast shared data transfers between processors inside such clusters can be performed through data reads on the fly. The dynamic SMP clusters are implemented inside system on chip (SoC) modules additionally connected by a central global network. A task scheduling algorithm is presented for program macro dataflow graphs for execution in the assumed architecture. The algorithm first identifies a set mold-able tasks in a given program graph. Next, this set is scheduled using a 2-phase algorithm including allotment of resources to moldable tasks and final list scheduling, with a warranty of schedule length. The complete algorithm has been implemented as a program package and examined using simulated execution of scheduled program graphs.
机译:本文涉及基于可模塑计算任务的概念的动态SMP集群中的任务调度。这些任务已被用作程序调度算法中的原子元素,并具有计划长度保证。对于程序执行,使用特殊的共享内存系统架构。它基于动态处理器集群,通过在内存模块总线之间切换处理器来组织周围共享内存模块。可以通过速度读取此类集群内部的处理器之间的快速共享数据传输。动态SMP集群在芯片(SOC)模块的系统内实现,另外由中央全局网络连接。呈现任务调度算法用于假定架构中的用于执行的程序宏数据流图。该算法首先在给定的节目图中识别集合模具任务。接下来,使用2阶段算法调度该集合,包括将资源分配给模制任务和最终列表调度,并保证计划长度。完整的算法已被实现为程序包,并使用计划的程序图的模拟执行检查。

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