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?
Barclays Data Scientist Gianmario Spacagna and Harry Powell, Head of Advanced Analytics, describe how they iteratively process raw data directly from the central data … Continued
ODSC West 2015 - Tachyon, a memory-centric fault-tolerant distributed storage system. An introduction of architecture, performance evaluation, and real world use cases. … Continued
Tachyon: A reliable memory-centric distributed storage system presentation by founder Haoyuan Li. … Continued
Memory is the key to fast big data processing. This has been realized by many, and frameworks such as Spark and Shark already leverage … Continued
We introduce Tachyon, a memory centric fault-tolerant distributed file system, which enables reliable file sharing at memory-speed across cluster frameworks, such as Spark and … Continued
Shaoshan Liu (Baidu) presents how Tachyon can help improve big data analytics (ad-hoc query) efficiency within Baidu. … Continued