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Synthesizing distributed pipelining systems with timing constraints via optimal functional unit assignment and communication selection

机译:通过优化功能单元分配和通信选择来合成具有时序约束的分布式流水线系统

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摘要

The design of efficient optimization techniques is important to synthesize application-specific distributed systems with timing constraints. In many applications, represented by task graphs, the consecutive executions of a task graph can be overlapped in a pipelined fashion with a proper buffer placement. The performance of such a system is closely related to the behavior of pipelining. Given a timing (throughput) constraint, however, using the fastest functional units or communication protocols may incur unacceptable high cost. In the design of such distributed pipelining systems with timing constraint, several problems need to be solved: how to properly place buffers, assign functional unit types for each task, and select communication protocols for each pair of tasks. This paper presents efficient optimization algorithms by integrally considering the above problems, such that the resultant systems can satisfy the timing constraints with the minimum total cost. In this paper, we first study the properties of distributed pipelining systems by using a rigorous model, called self-timed model, and then we present theorems to accurately compute the system throughput. Based on these understandings, we devise efficient algorithms to obtain the optimal solutions. Experiments show that the typical greedy approaches cannot find a feasible solution for the tight timing requirements while our algorithms can. For the few cases that greedy approaches may find solutions, our algorithms can achieve significant reductions in total cost. (C) 2017 Elsevier B.V. All rights reserved.
机译:有效的优化技术的设计对于合成具有时序约束的专用分布式系统非常重要。在由任务图表示的许多应用中,任务图的连续执行可以以流水线方式与适当的缓冲区放置重叠。这种系统的性能与流水线行为密切相关。但是,给定时间(吞吐量)限制,使用最快的功能单元或通信协议可能会导致无法接受的高成本。在这种具有时序约束的分布式流水线系统的设计中,需要解决几个问题:如何正确放置缓冲区,为每个任务分配功能单元类型以及为每对任务选择通信协议。本文综合考虑了上述问题,提出了高效的优化算法,以使最终的系统能够以最小的总成本满足时序约束。在本文中,我们首先使用严格的模型(称为自定时模型)研究分布式流水线系统的属性,然后提出定理以准确计算系统吞吐量。基于这些理解,我们设计了有效的算法来获得最佳解。实验表明,典型的贪婪方法无法针对严格的时序要求找到可行的解决方案,而我们的算法却可以。对于贪婪的方法可能会找到解决方案的少数情况,我们的算法可以显着降低总成本。 (C)2017 Elsevier B.V.保留所有权利。

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