Abstract
Recent advances in High-Level Synthesis (HLS) allow software developers to offload compute kernels to FPGAs without deep knowledge about low-level hardware description languages. However, this abstraction comes at the cost of control over the bitstream and thus complicates features like partial reconfiguration. We introduce a vendor-agnostic high-level approach for time and space multiplexing on OpenCL-programmed FPGAs. It dynamically adjusts the FPGA’s configuration to provide load balancing between multiple kernels on the same device. Our method uses several configurations, each with a different amount of FPGA resources dedicated to the respective kernel. We introduce a model to decide which configuration is selected based on the projected runtime of the enqueued tasks. Our model and the implementation Forecast are demonstrated with an online scheduler on a current high-end FPGA. We find that Forecast makes automatic handling of configurations in HLS-applications possible.
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Jungblut, P., Kranzlmüller, D. (2021). Dynamic Spatial Multiplexing on FPGAs with OpenCL. In: Derrien, S., Hannig, F., Diniz, P.C., Chillet, D. (eds) Applied Reconfigurable Computing. Architectures, Tools, and Applications. ARC 2021. Lecture Notes in Computer Science(), vol 12700. Springer, Cham. https://doi.org/10.1007/978-3-030-79025-7_19
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DOI: https://doi.org/10.1007/978-3-030-79025-7_19
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