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- Publisher
- Association for Computing Machinery
- Copyright
- Copyright © 2010 by ACM Inc.
- ISSN
- 1936-7406
- DOI
- 10.1145/1862648.1862650
- Publisher site
- See Article on Publisher Site
Abstract
Recon guration and Communication-Aware Task Scheduling for High-Performance Recon gurable Computing MIAOQING HUANG, VIKRAM K. NARAYANA, HARALD SIMMLER, OLIVIER SERRES, and TAREK EL-GHAZAWI NSF Center for High-Performance Recon gurable Computing (CHREC), The George Washington University High-performance recon gurable computing involves acceleration of signi cant portions of an application using recon gurable hardware. When the hardware tasks of an application cannot simultaneously t in an FPGA, the task graph needs to be partitioned and scheduled into multiple FPGA con gurations, in a way that minimizes the total execution time. This article proposes the Reduced Data Movement Scheduling (RDMS) algorithm that aims to improve the overall performance of hardware tasks by taking into account the recon guration time, data dependency between tasks, intertask communication as well as task resource utilization. The proposed algorithm uses the dynamic programming method. A mathematical analysis of the algorithm shows that the execution time would at most exceed the optimal solution by a factor of around 1.6, in the worst-case. Simulations on randomly generated task graphs indicate that RDMS algorithm can reduce intercon guration communication time by 11% and 44% respectively, compared with two other approaches that consider data dependency and hardware resource utilization only.
Journal
ACM Transactions on Reconfigurable Technology and Systems (TRETS) – Association for Computing Machinery
Published: Nov 1, 2010