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ABSTRACT
Partitioning an embedded system application among a microprocessor and custom hardware has been shown to improve the performance, power or energy of numerous examples. The advent of single-chip microprocessor/FPGA platforms makes such partitioning even more attractive. Previous partitioning approaches have partitioned sequential program source code, such as C or C++. We introduce a new approach that partitions at the software binary level. Although source code partitioning is preferable from a purely technical viewpoint, binary-level partitioning provides several very practical benefits for commercial acceptance. We demonstrate that binary-level partitioning yields competitive speedup results compared to source-level partitioning, achieving an average speedup of 1.4 compared to 1.5 for eight benchmarks partitioned on a single-chip microprocessor/FPGA device.
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CITED BY 20
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Gaurav Mittal , David C. Zaretsky , Xiaoyong Tang , P. Banerjee, Automatic translation of software binaries onto FPGAs, Proceedings of the 41st annual conference on Design automation, June 07-11, 2004, San Diego, CA, USA
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Greg Stitt , Zhi Guo , Walid Najjar , Frank Vahid, Techniques for synthesizing binaries to an advanced register/memory structure, Proceedings of the 2005 ACM/SIGDA 13th international symposium on Field-programmable gate arrays, February 20-22, 2005, Monterey, California, USA
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Greg Stitt , Frank Vahid , Gordon McGregor , Brian Einloth, Hardware/software partitioning of software binaries: a case study of H.264 decode, Proceedings of the 3rd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis, September 19-21, 2005, Jersey City, NJ, USA
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