Optimal FPGA module placement with temporal precedence constraints
Proceedings of the conference on Design, automation and test in Europe
Hardware/Software CO-Design for Data Flow Dominated Embedded Systems
Hardware/Software CO-Design for Data Flow Dominated Embedded Systems
Fast Template Placement for Reconfigurable Computing Systems
IEEE Design & Test
Imagine: Media Processing with Streams
IEEE Micro
Temporal floorplanning using 3D-subTCG
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
Implementing and Evaluating Stream Applications on the Dynamically Reconfigurable Processor
FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
A Partitioning Methodology for Accelerating Applications in Hybrid Reconfigurable Platforms
Proceedings of the conference on Design, Automation and Test in Europe - Volume 3
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The multi-process execution in dynamically reconfigurable processors is a technique to enhance throughput by trying to exploit more inherent parallelism of applications. Basically, a total process for an application is divided into small processes, assigned into limited areas of a reconfigurable array, and concurrently executed in a pipelined manner. In order to improve the efficiency of the multi-process execution, a systematic method for mapping processes onto a reconfigurable array consisting of multiple hardware execution units is essential. This paper proposes and investigates a systematic method for mapping an application modeled as a Kahn Process Network onto a dynamically reconfigurable processing array. In order to execute streaming applications in a pipelined manner, the size of Tiles, which is a unit area of dynamically reconfigurable array, and the grouping of processes are adjusted. Using real applications such as DCT, JPEG encoder and Turbo encoder, the impact of different versions mapped onto the NEC Dynamically Reconfigurable Processor on performance is evaluated. Evaluation results show that our proposed mapping algorithm achieves the best performance in terms of the throughput and the execution time.