Optimization of a line detection algorithm for autonomous vehicles on a RISC-V with accelerator





Autonomous vehicles, image processing, RISC-V, FireSim, Matrix accelerator


In recent years, autonomous vehicles have attracted the
attention of many research groups, both in academia
and business, including researchers from leading com-
panies such as Google, Uber and Tesla. This type of
vehicles are equipped with systems that are subject
to very strict requirements, essentially aimed at per-
forming safe operations –both for potential passengers
and pedestrians– as well as carrying out the process-
ing needed for decision making in real time. In many
instances, general-purpose processors alone cannot
ensure that these safety, reliability and real-time re-
quirements are met, so it is common to implement
heterogeneous systems by including accelerators. This
paper explores the acceleration of a line detection ap-
plication in the autonomous car environment using a
heterogeneous system consisting of a general-purpose
RISC-V core and a domain-specific accelerator. In par-
ticular, the application is analyzed to identify the most
computationally intensive parts of the code and it is
adapted accordingly for more efficient processing. Fur-
thermore, the code is executed on the aforementioned
hardware platform to verify that the execution effec-
tively meets the existing requirements in autonomous
vehicles, experiencing a 3.7x speedup with respect to
running without accelerator.


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How to Cite

Belda, M. J., Olcoz, K., Castro, F., & Tirado, F. (2022). Optimization of a line detection algorithm for autonomous vehicles on a RISC-V with accelerator. Journal of Computer Science and Technology, 22(2), e10. https://doi.org/10.24215/16666038.22.e10



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