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Ray Summit 2024

09 . 30 . 2024 , 03:00 PM (PST)

Ray Summit 2023

09 . 18 . 2023 , 03:30 PM (PST)

Powering Open Data Hub with Ray

06 . 23 . 2021 , 08:35 PM (PST)

Introducing Amazon SageMaker Kubeflow Reinforcement Learning Pipelines for Robotics

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Software 2.0 Needs Data 2.0: A New Way of Storing and Managing Data for Efficient Deep Learning

06 . 23 . 2021 , 08:35 PM (PST)

Mars-on-Ray: Accelerating Large-scale Tensor and DataFrame Workloads

06 . 23 . 2021 , 08:35 PM (PST)

A Growing Ecosystem of Scalable ML Libraries on Ray

06 . 23 . 2021 , 08:35 PM (PST)

Using RLLib in an Enterprise Scale Reinforcement Learning Solution

06 . 23 . 2021 , 08:35 PM (PST)

The Journey from AI to Bedside: Translating Academic Research to Serving Patients Using Ray

06 . 23 . 2021 , 08:00 PM (PST)

A Deep Dive into Ray’s Scheduling Policy

06 . 23 . 2021 , 08:00 PM (PST)

Machine Learning and Microbiology in the Cloud Through Ray

06 . 23 . 2021 , 08:00 PM (PST)

Anomaly Detection on Remote Sensing with Ray + Horovod

06 . 23 . 2021 , 08:00 PM (PST)

Applying Ray and RLlib to Real-life Industrial Use Cases

06 . 23 . 2021 , 08:00 PM (PST)

Large Scale Data Loading and Data Preprocessing with Ray

06 . 23 . 2021 , 08:00 PM (PST)

Scaling and Unifying SciKit Learn and Spark Pipelines using Ray

06 . 23 . 2021 , 07:25 PM (PST)

Data Processing on Ray

Tuesday, June 22, 8:45PM UTC

SangBin Cho, Software Engineer, Anyscale

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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.

Speakers

SangBin Cho

Software Engineer, Anyscale

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.