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Communication Dans Un Congrès Année : 2023

High-Level Synthesis-Based On-board Payload Data Processing considering the Roofline Model

Résumé

On-board payload data processing can be performed by developing space-qualified heterogeneous Multiprocessor Systemon-Chips (MPSoCs). We present key compute-intensive payload algorithms, based on a survey with space science researchers, including the two-dimensional Fast Fourier Transform (2-D FFT). Also, we propose to perform design space exploration by combining the roofline performance model with High-Level Synthesis (HLS) for hardware accelerator architecture design. The roofline model visualizes the limits of a given architecture regarding Input/Output (I/O) bandwidth and computational performance, along with the achieved performance for different implementations. HLS is an interesting option in developing FPGA-based onboard processing applications for payload teams that need to adjust architecture specifications through design reviews and have limited expertise in Hardware Description Languages (HDLs). In this paper, we focus on an FPGA-based MPSoC thanks to recently released radiation-hardened heterogeneous embedded platforms.
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Dates et versions

hal-04294305 , version 1 (19-11-2023)

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  • HAL Id : hal-04294305 , version 1

Citer

Seungah Lee, Ruben Salvador, Angeliki Kritikakou, Olivier Sentieys, Julien Galizzi, et al.. High-Level Synthesis-Based On-board Payload Data Processing considering the Roofline Model. EDHPC 2023 - European Data Handling & Data Processing Conference, European Space Agency (ESA), Oct 2023, Juan-Les-Pins, France. pp.1-10. ⟨hal-04294305⟩
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