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?
Alluxio is the world’s first memory-speed virtual distributed storage system that bridges applications and underlying storage systems, providing unified data access orders of magnitudes … Continued
Big Data Day LA 2016 - In the past year, the Alluxio project experienced a tremendous improvement in performance and scalability and was extended … Continued
This whitepaper consists of two portions. The first is a high level overview of the advantages of using Alluxio as a core technology with … Continued
At Qunar, we have been running Alluxio in production for over 9 months, resulting in 15x speedup on average, and 300x speedup at peak … Continued
O'Reilly - An Alluxio tour to any data scientist, developer or system administrator looking to improve the performance of their workloads, develop applications with … Continued