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A fast task-to-processor assignment heuristic for real-time multiprocessor DSP applications

机译:针对实时多处理器DSP应用的快速任务到处理器分配启发式

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The optimal assignment of the tasks to the processors to minimize total delay in a multiprocessor digital signal processing (DSP) architecture is extremely difficult, particularly for systems of many (e.g. 100) tasks. Two factors especially complicate the problem: (1) the multiprocessor architecture affects the inter-processor communication times, and (2) the specific assignment of tasks to processors affects the inter-task communication times. We develop a fast heuristic for assigning tasks to processors. There are two main ingredients in our method: (ⅰ) the choice of a useful general-purpose multiprocessor architecture for DSP applications, and (ⅱ) an adaptive list-ordering heuristic which takes advantage of knowledge of the inter-processor communication characteristics of the chosen architecture. Examples are given, including comparisons to exact branch-and-bound methods, and a large sonar example. Scope and purpose: General digital signal processing system architectures consist of an arrangement of signal processing units connected by communication links. The tasks to be carried out by the signal processing units are specified via a task graph similar to a PERT diagram. The challenge is to assign the tasks in the task graph to the signal processing units in the architecture in an optimal manner. In this paper, we are interested in task-to-processor assignments that minimize the total delay, which is the lag between the first appearance of a signal at the input port and the production of a processed signal at the output port. The assignment process is complicated by the need to consider the inter-task communication delays, which are themselves greatly affected by the assignment. The task-to-processor assignment problem is NP-complete, hence heuristics must be used. We develop a fast and effective heuristic for a specific general-purpose digital signal processing architecture.
机译:将任务最佳地分配给处理器以最小化多处理器数字信号处理(DSP)架构中的总延迟是非常困难的,尤其是对于许多任务(例如100个)的系统而言。有两个因素使问题特别复杂:(1)多处理器体系结构影响处理器间的通信时间,(2)任务对处理器的特定分配影响任务间的通信时间。我们为将任务分配给处理器开发了一种快速的启发式方法。我们的方法有两个主要成分:(ⅰ)为DSP应用选择有用的通用多处理器体系结构,以及(ⅱ)利用列表处理器的处理器间通信特性的知识的自适应列表排序启发式方法选择的架构。给出了示例,包括与精确的分支定界方法的比较,以及一个大型声纳示例。范围和目的:通用数字信号处理系统体系结构由通过通信链路连接的信号处理单元组成。信号处理单元要执行的任务是通过类似于PERT图的任务图指定的。挑战在于以最佳方式将任务图中的任务分配给体系结构中的信号处理单元。在本文中,我们对任务到处理器的分配感兴趣,这些分配可以最大程度地减少总延迟,总延迟是指在输入端口首次出现信号与在输出端口产生经过处理的信号之间的延迟。分配过程因需要考虑任务间通信延迟而变得很复杂,而任务间通信延迟本身受分配的影响很大。任务到处理器的分配问题是NP完全的,因此必须使用试探法。我们针对特定的通用数字信号处理体系结构开发了一种快速有效的启发式方法。

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