Machine learning and data processing applications continue to drive the need to develop scalable Python applications. Ray is a distributed execution engine that enables programmers to scale up their Python applications. This talk will cover some of the challenges we faced and key architectural changes we made to Ray over the past year to support a new set of large scale data processing workloads.
SangBin Cho is a software engineer at Anyscale and a committer of an open-source program Ray. He has contributed to various parts of Ray’s core distributed systems including scalable metrics infrastructure, new actor fault tolerance mechanism, placement group APIs, and stable memory management subsystems.