This talk outlines how Dendra Systems leverage Ray and Anyscale to parallelize their workloads across a cluster containing dozens of GPUs in a single Python script. Richard will discuss how Dendra optimized their inference pipelines to saturate their clusters' network I/O limits using Ray Serve.
Richard will then describe how Anyscale makes it easy to run this Ray application in production: running seamlessly in their BitBucket CI and also supporting a microservice to launch jobs programmatically.
Richard Decal is a machine learning scientist on a mission to fight against climate change. He is the Lead ML Engineer at Dendra Systems, where he is working on scaling ecosystem-restoring drones to the planetary scale.