A collaboration of Alibaba, Alluxio, and Nanjing University in tackling the problems of Deep Learning model training in the cloud. Our goal was to reduce the cost and complexity of data access for Deep Learning training in a hybrid environment, which resulted in over 40% reduction in training time and cost.
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This article describes how Alluxio can accelerate the training of deep learning models in a hybrid cloud environment when using Intel’s Analytics Zoo open source platform, powered by oneAPI. Details on the new architecture and workflow, as well as Alluxio’s performance benefits and benchmarks results will be discussed.
Are you using SQL engines, such as Presto, to query existing Hive data warehouse and experiencing challenges including overloaded Hive Metastore with slow and unpredictable access, unoptimized data formats and layouts such as too many small files, or lack of influence over the existing Hive system and other Hive applications?
In this talk, we share our lessons in building and rebuilding our monitoring systems and data platforms at Electronic Arts (EA). … Continued
Best use cases for Presto from the Data Engineer’s perspective. Also hear about recent Presto advancements such as Cost-Based Optimizer, Kubernetes-native deployment and the … Continued
The whole Ryte-Platform is built with a scalable architecture to support our heavy load and make it possible for our customers to drill-down from … Continued
Hear about the challenges and evolution of data orchestration at Rakuten data system with the collaboration of Alluxio. … Continued
In this session, we share common design patterns AWS customers are applying as part of their Data and AI journey. … Continued
Learn more about Alluxio's structured data management, developer preview in Alluxio 2.1.0 and catch the demo. … Continued
Learn about Alibaba's use case in deep learning and gene computing acceleration using Alluxio in Kubernetes. … Continued