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 keynote, you will learn about the evolution of the global data platform at Rakuten spread across multiple regions, and clouds. In addition, … Continued
This is an open source community conference focused on the key data engineering challenges and solutions around building cloud-native data and AI platforms using … Continued
In this keynote from Haoyuan Li, founder and CEO of Alluxio, we will showcase how organizations have built data platforms based on data orchestration. … Continued
JD.com is one of the largest e-commerce corporations. In big data platform of JD.com, there are tens of thousands of nodes and tens of … Continued
In this talk, Baolong Mao from Tencent will share his experience in developing Apache Ozone under file system, showing how to create a new … Continued