TransMap: Transformation Based Remapping and Parallelism for High Utilization and Energy Efficiency in CGRAs

• Published in: IEEE transactions on computers 2016-11, Vol.65 (11), p.3456-3469
• Main Authors: Jafri, Syed M. A. H., Daneshtalab, Masoud, Abbas, Naeem, Serrano Leon, Guillermo, Hemani, Ahmed
• Format: Article
• Language: English
• Subjects: energy aware systems; Energy management; Field programmable gate arrays; Memory management; MPEG 4 Standard; Parallel processing; Reconfigurable architecture; Reconfigurable architectures; run-time remapping; Wireless LAN
• ISSN: 0018-9340; 1557-9956; 1557-9956
• DOI: 10.1109/TC.2016.2525981

In the era of platforms hosting multiple applications with arbitrary inter application communication and computation patterns, compile time mapping decisions are neither optimal nor desirable. As a solution to this problem, recently proposed architectures offer run-time remapping. The run-time remapping techniques displace or parallelize/serialize an application to optimize different parameters (e.g., utilization and energy). To implement the dynamic remapping, reconfigurable architectures commonly store multiple (compile-time generated) implementations of an application. Each implementation represents a different platform location and/or degree of parallelism. The optimal implementation is selected at run-time. However, the compile-time binding either incurs excessive configuration memory overheads and/or is unable to map/parallelize an application even when sufficient resources are available. As a solution to this problem, we present Transformation based reMapping and parallelism (TransMap). TransMap stores only a single implementation and applies a series for transformations to the stored bitstream for remapping or parallelizing an application. Compared to state of the art, in addition to simple relocation in horizontal/vertical directions, TransMap also allows to rotate an application for mapping or parallelizing an application in resource constrained scenarios. By storing only a single implementation, TransMap offers significant reductions in configuration memory requirements (up to 73 percent for the tested applications), compared to state of the art compaction techniques. Simulation results reveal that the additional flexibility reduces the energy requirements by 33 percent and enhances the device utilization by 50 percent for the tested applications. Gate level analysis reveals that TransMap incurs negligible silicon (0.2 percent of the platform) and timing (6 additional cycles per application) penalty.