Accelerating Machine Learning / Deep Learning in the Cloud: Architecture and Benchmark

This whitepaper introduces how to speed up end-to-end  distributed training in the cloud using Alluxio to accelerate data access. With the help of Alluxio, loading data from cloud storage, training and caching data can be done in a transparent and distributed way as a part of the training process. This whitepaper also demonstrates how to set up and benchmark the end-to-end performance of the training process, along with a comparison of other popular approaches.

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Alluxio Use Cases Overview

Alluxio started as a virtual distributed file system, a research project out of the AMPLab at U.C. Berkeley. Alluxio foresaw the need for agility when accessing large data stores separated from compute engines like Hadoop or Spark.
Fast forward several years and over a thousand committers later, and Alluxio has blossomed into the industry’s leading data orchestration platform for analytics and AI/ML. But as with any new type of technology, figuring out the best ways to use it depends on your data environment, computational workloads, issues, and goals. 

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Aunalytics Leverages Alluxio as a “one-stop-shop” for Data I/O

Alluxio is a leading data orchestration platform that offers a compute agnostic, storage agnostic, and cloud agnostic solution for big data and machine learning applications. Aunalytics is a data platform company delivering Insights-as-a-Service to answer enterprise and mid-sized companies’ most important IT and business questions.

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Accelerating Data Computation on Ceph Objects using Alluxio

In this talk, we will present how using Alluxio computation and storage ecosystems can better interact benefiting of the “bringing the data close to the code” approach. Moving away from the complete disaggregation of computation and storage, data locality can enhance the computation performance. During this talk, we will present our observations and testing results that will show important enhancements in accelerating Spark Data Analytics on Ceph Objects Storage using Alluxio.

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Accelerating Data Computation on Ceph Objects using Alluxio

In this talk, we will present how using Alluxio computation and storage ecosystems can better interact benefiting the “bringing the data close to the code” approach. Moving away from the complete disaggregation of computation and storage, data locality can enhance the computation performance. During this talk, we will present our observations and testing results that will show important enhancements in accelerating Spark Data Analytics on Ceph Objects Storage using Alluxio.

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