Applying the multi-agent paradigm to reconfigurable hardware: a sensor fusion example
Second international workshop on Intelligent systems design and application
Mapping deep nested do-loop DSP algorithms to large scale FPGA array structures
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Applying multi agent techniques to reconfigurable systems
Advances in Engineering Software
Creating an adaptive embedded system by applying multi-agent techniques to reconfigurable hardware
Future Generation Computer Systems - Special issue: Computational science of lattice Boltzmann modelling
Low-complex dynamic programming algorithm for hardware/software partitioning
Information Processing Letters
An incremental temporal partitioning method for real-time reconfigurable systems
EHAC'06 Proceedings of the 5th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications
Mapping of Discrete Cosine Transforms onto Distributed Hardware Architectures
Journal of Signal Processing Systems
WSEAS Transactions on Computers
International Journal of Computer Applications in Technology
A parallel partitioning algorithm for parallel reconfigurable computing
CSS '07 Proceedings of the Fifth IASTED International Conference on Circuits, Signals and Systems
Low-complex dynamic programming algorithm for hardware/software partitioning
Information Processing Letters
Journal of Real-Time Image Processing
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Reconfigurable computers (RCs) host multiple field programmable gate arrays (FPGAs) and one or more physical memories that communicate through an interconnection fabric. State-of-the-art RCs provide abundant hardware and storage resources, but have tight constraints on FPGA pin-out and inter-FPGA interconnection resources. These stringent constraints are the primary impediment for multi-FPGA partitioning tools to generate high-quality designs, in this paper, we present two integrated partitioning and synthesis approaches for RCs. The first approach involves fine-grained partitioning of a scheduled data-flow graph (DFG, or an operation graph), and the second involves a coarse-grained partitioning of an unscheduled control data flow graph (CDFG, or a block graph). A hardware design space exploration engine is integrated with the block graph partitioner that dynamically contemplates multiple schedules during partitioning. The novel feature in the partitioning approaches is that the physical memory in the RC is effectively used to alleviate the FPGA pin-out and inter-FPGA interconnection bottle-neck. Several experiments have been conducted, targeting commercial multi-FPGA boards, to compare the two partitioning approaches, and detailed summaries are presented.