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RDMS: A hardware task scheduling algorithm for Reconfigurable Computing

机译:RDMS:用于可重构计算的硬件任务调度算法

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Reconfigurable computers (RC) can provide significant performance improvement for domain applications. However, wide acceptance of today's RCs among domain scientist is hindered by the complexity of design tools and the required hardware design experience. Recent developments in HW/SW co-design methodologies for these systems provide the ease of use, but they are not comparable in performance to manual co-design. This paper aims at improving the overall performance of hardware tasks assigned to FPGA devices by minimizing both the communication overhead and configuration overhead, which are introduced by using FPGA devices. The proposed reduced data movement scheduling (RDMS) algorithm takes data dependency among tasks, hardware task resource utilization, and inter-task communication into account during the scheduling process and adopts a dynamic programming approach to reduce the communication between muP and FPGA co-processor and the number of FPGA configurations to a minimum. Compared to two other approaches that consider data dependency and hardware resource utilization only, RDMS algorithm can reduce inter-configuration communication time by 11% and 44% respectively based on simulation using randomly generated data flow graphs. The implementation of RDMS on a real-life application, N-body simulation, verifies the efficiency of RDMS algorithm against other approaches.
机译:可重新配置的计算机(RC)可以为域应用程序提供显着的性能改进。但是,设计工具的复杂性和所需的硬件设计经验阻碍了领域科学家对当今RC的广泛接受。这些系统的硬件/软件协同设计方法的最新发展提供了易用性,但在性能上无法与手动协同设计相提并论。本文旨在通过最小化使用FPGA器件引入的通信开销和配置开销来提高分配给FPGA器件的硬件任务的整体性能。所提出的减少数据移动调度(RDMS)算法在调度过程中考虑了任务之间的数据依赖性,硬件任务资源利用率以及任务间通信,并采用了动态编程方法来减少muP与FPGA协处理器之间的通信。 FPGA配置数量最少。与仅考虑数据依赖性和硬件资源利用率的其他两种方法相比,基于使用随机生成的数据流图进行的仿真,RDMS算法可以将配置间通信时间分别减少11%和44%。 RDMS在实际应用中的实现(N体仿真)可验证RDMS算法相对于其他方法的效率。

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