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?
Vitaliy and Dipti dive into how DBS Bank built a modern big data analytics stack, leveraging an object store as persistent storage even for … Continued
This online meetup shows why and how we solve some challenging technical issues, improve the speed, and reduce the costs of our AWS EMR … Continued
In this talk, we present: trends and challenges in the data ecosystem in cloud era; Data engineering in the cloud with data orchestration; Use … Continued
Learn more about Bazaarvoice's use case leveraging Apache Spark, Hive, and Alluxio on S3. Along with how to set up Hive with Alluxio so … Continued
In this online presentation, we present how ING is leveraging Presto (interactive query), Alluxio (data orchestration & acceleration), S3 (massive storage), and DC/OS (container … Continued
EMR has become a widely used service to run big data analytics in the public cloud. But issues around slow/inconsistent EMR performance due to … Continued
This tech talk gives shows how to set up EMR Spark and Hive with Alluxio to seamlessly read/write to your S3 data lake, along … Continued