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?
Many companies we talk to have on premises data lakes and use the cloud(s) to burst compute. Many are now establishing new object data … Continued
In this talk, I will introduce the high-level architecture of the current system, and present the various components of Alluxio. Also, I will discuss … Continued
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
We introduce Data Orchestration Hub, a management service that makes it easy to build an analytics or machine learning platform on data sources across … Continued
Distributed applications are not new. The first distributed applications were developed over 50 years ago with the arrival of computer networks, such as ARPANET. … Continued