Simultaneous multiprocessing in a software-defined heterogeneous FPGA

Jose Nunez-Yanez, Sam Amiri*, Mohammad Hosseinabady, Andrés Rodríguez, Rafael Asenjo, Angeles Navarro, Dario Suarez, Ruben Gran

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

9 Citations (Scopus)
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Heterogeneous chips that combine CPUs and FPGAs can distribute processing so that the algorithm tasks are mapped onto the most suitable processing element. New software-defined high-level design environments for these chips use general purpose languages such as C++ and OpenCL for hardware and interface generation without the need for register transfer language expertise. These advances in hardware compilers have resulted in significant increases in FPGA design productivity. In this paper, we investigate how to enhance an existing software-defined framework to reduce overheads and enable the utilization of all the available CPU cores in parallel with the FPGA hardware accelerators. Instead of selecting the best processing element for a task and simply offloading onto it, we introduce two schedulers, Dynamic and LogFit, which distribute the tasks among all the resources in an optimal manner. A new platform is created based on interrupts that removes spin-locks and allows the processing cores to sleep when not performing useful work. For a compute-intensive application, we obtained up to 45.56% more throughput and 17.89% less energy consumption when all devices of a Zynq-7000 SoC collaborate in the computation compared against FPGA-only execution.

Original languageEnglish
Number of pages18
JournalJournal of Supercomputing
Early online date16 Apr 2018
Publication statusE-pub ahead of print - 16 Apr 2018


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  • Correction to: Simultaneous multiprocessing in a software-defined heterogeneous FPGA

    Nunez-Yanez, J., Amiri, S., Hosseinabady, M., Rodríguez, A., Asenjo, R., Navarro, A., Suarez, D. & Gran, R., 25 May 2018, In: Journal of Supercomputing. p. 1-2 2 p.

    Research output: Contribution to journalComment/debate (Academic Journal)peer-review

    Open Access
    258 Downloads (Pure)
  • Simultaneous Multiprocessing on a FPGA+CPU Heterogeneous System-On-Chip

    Nunez-Yanez, J., Hosseinabady, M., Rodríguez, A., Asenjo, R., Navarro, A., Gran-Tejero, R. & Suárez-Gracia, D., 7 Mar 2018, Parallel Computing is Everywhere. IOS Press, p. 677-686 10 p. (Advances in Parallel Computing; vol. 32).

    Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

    Open Access
    90 Downloads (Pure)

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