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GTC ON-DEMAND

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Abstract:
The Krylov Project is the key component in eBay's AI Platform initiative that provides an easy to use, open, and fast AI orchestration engine that is deployed as managed services in eBay cloud. The main goals of the project are: Every AI and machine learning algorithm should be shareable and easily implementable with possible options of frameworks; enable machine learning engineers to do end-to-end training pipelines that distribute and parallelize over many machines; training models should be automated and allow easy access to vast eBay datasets; engineers should be able to search past job submissions, view results, and share with others. We have built Krylov from the ground up, leveraging JVM, Python, and Go as the main technologies to build the Krylov components, while standing in shoulder of giants of technology such as Docker, Kubernetes, and Apache Hadoop. Using Krylov, AI scientists can access eBay's massive datasets; build and train AI models; spin up powerful compute (high-memory or GPU instances) on the Krylov HPC cluster; and set up machine learning pipelines, such as using declarative constructs that stitch together pipeline lifecycle.
The Krylov Project is the key component in eBay's AI Platform initiative that provides an easy to use, open, and fast AI orchestration engine that is deployed as managed services in eBay cloud. The main goals of the project are: Every AI and machine learning algorithm should be shareable and easily implementable with possible options of frameworks; enable machine learning engineers to do end-to-end training pipelines that distribute and parallelize over many machines; training models should be automated and allow easy access to vast eBay datasets; engineers should be able to search past job submissions, view results, and share with others. We have built Krylov from the ground up, leveraging JVM, Python, and Go as the main technologies to build the Krylov components, while standing in shoulder of giants of technology such as Docker, Kubernetes, and Apache Hadoop. Using Krylov, AI scientists can access eBay's massive datasets; build and train AI models; spin up powerful compute (high-memory or GPU instances) on the Krylov HPC cluster; and set up machine learning pipelines, such as using declarative constructs that stitch together pipeline lifecycle.  Back
 
Topics:
Data Center & Cloud Infrastructure, HPC and AI
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8277
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