Supercharging self-driving algor dev w/ Ray: scaling sim workloads and democratizing autotuning@Zoox

Autonomous driving software development heavily relies on algorithm parameter tuning at scale. Hand-tuning in simulation is a common practice, but it can be time-consuming, error-prone, and not scalable to various complex driving scenarios or large parameter search spaces. At Zoox, we have developed an autotuning platform that accelerates algorithm development by leveraging large-scale, distributed simulation and metrics evaluation. This talk will cover how we utilized Ray to scale simulation and metrics workloads at Zoox, and demonstrate our autotuning process that allows developers to improve autonomous driving without changing any code. Attendees will gain insights into how Ray's capabilities, such as scalability and fault tolerance, are used in our platform. We will also highlight some of the key lessons we learned while developing and deploying our autotuning platform, and provide a glimpse into the future of metrics-driven algorithm development.
Find the slide deck here: drive.google.c...
About Anyscale
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Anyscale is the AI Application Platform for developing, running, and scaling AI.
www.anyscale.com/
If you're interested in a managed Ray service, check out:
www.anyscale.c...
About Ray
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Ray is the most popular open source framework for scaling and productionizing AI workloads. From Generative AI and LLMs to computer vision, Ray powers the world’s most ambitious AI workloads.
docs.ray.io/en...
#llm #machinelearning #ray #deeplearning #distributedsystems #python #genai