In Abstracts of the 2024 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS/PERFORMANCE Abstracts ’24), June 10–14, 2024, Venice, Italy. ACM, New York, NY, USA.
Mohammad Bakhshalipour, Phillip B. Gibbons
Carnegie Mellon University
As robots increasingly permeate modern society, it is crucial for the system and hardware research community to bridge its long-standing gap with robotics. This divide has persisted due to the lack of (i) a systematic performance evaluation of robotics on different computing platforms and (ii) a comprehensive, open-source, cross- platform benchmark suite.
To address these gaps, we present a systematic performance study of robotics on modern hardware and introduce RoWild, an open-source benchmark suite for robotics that is comprehensive and cross-platform. Our workloads encompass a broad range of robots, including driverless vehicles, pilotless drones, and stationary robotic arms, and we evaluate their performance on a spectrum of modern computing platforms, from low-end embedded CPUs to high-end server-grade GPUs.
Our findings reveal that current architectures experience significant inefficiencies when executing robotic workloads, highlighting the need for architectural advancements. We discuss approaches for meeting these requirements, offering insights for improving the performance of robotics. The full version of the paper is available in [11], and the source code of the benchmark suite is available in [2].
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