Tag: machine learning

Fast big data analytics and machine learning using Alluxio and Spark in Baidu

Strata+Hadoop World San Jose *

A few months ago, Baidu deployed Alluxio to accelerate its big data analytics workload. Bin Fan and Haojun Wang explain why Baidu chose Alluxio, as well as the details of how they achieved a 30x speedup with Alluxio in their production environment with hundreds of machines. Based on the success of the big data analytics engine, Baidu is currently expanding the Alluxio and Spark infrastructure to accelerate other applications, such as machine learning.

Shanghai Meetup: Talks from Ctrip, Qiniu, Intel & Alluxio

Shanghai Meetup *

The future is the era of data, and the abstraction of efficient management, storage, and access to data is undoubtedly the cornerstone of this era. Open source distributed virtual data system Alluxio is dedicated to providing simple and efficient data abstraction, convenient data sharing and high-speed I/O for big data, machine learning, and artificial intelligence, while keeping applications and data persistent and providing rich Storage system selection.
After several years of development, Alluxio was developed from a prototype of a research project involving only a few Ph.D. students and researchers in the AMPLab at the University of California, Berkeley, to more than 800 code contributors (Alluxio 1.8 release data), and deployed in Tencent. Baidu, JD, Two-Sigma, Barclays Bank and other hundreds of Chinese and foreign industry leaders in the production environment, become an important part of the data platform and data infrastructure.

Alluxio 2.0 Deep Dive & A Case of Real-time Processing with Spark

Bay Area Meetup *

We are excited to present Alluxio 2.0 to our community. The goal of Alluxio 2.0 was to significantly enhance data accessibility with improved APIs, expand use cases supported to include active workloads as well as better metadata management and availability to support hyperscale deployments. Alluxio 2.0 Preview Release is the first major milestone on this path to Alluxio 2.0 and includes many new features.

Introduction to Alluxio 2.0 Preview

Alluxio Tech Talk *

Alluxio 2.0 is the most ambitious platform upgrade since the inception of Alluxio with greatly expanded capabilities to empower users to run analytics and AI workloads on private, public or hybrid cloud infrastructures leveraging valuable data wherever it might be stored. This preview release, now available for download, includes many advancements that will allow users to push the limits of their data-workloads in the cloud.

Tech Talk: Accelerate and Scale Big Data Analytics and Machine Learning Pipelines with Disaggregated Compute and Storage

Enterprises are increasingly looking towards object stores to power their big data & machine learning workloads in a cost-effective way. The combination of SwiftStack and Alluxio together, enables users to seamlessly move towards a disaggregated architecture. Swiftstack provides a massively parallel cloud object storage and multi-cloud data management system. Alluxio is a data orchestration layer, which sits between compute frameworks and storage systems and enables big data workloads to be deployed directly on SwiftStack. Alluxio provides data locality, accessibility and elasticity via its core innovations. With the Alluxio and Swiftstack solution, Spark, Presto, Tensorflow and Hive and other compute workloads can benefit from 10X performance improvement and dramatically lower costs. In this tech talk, we will provide a brief overview of the Alluxio and SwiftStack solution as well as the key use cases it enables.

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Hedge Fund Improves Machine Learning Model Performance 4X with Alluxio

Quantitative hedge funds process large data sets with sophisticated financial models to drive investment decisions. Machine Learning is used to continuously improve models and maximize financial return. One firm with billions ($US) of assets under management turned to Alluxio to address the performance and cost challenges of large scale data processing in a hybrid cloud environment. With Alluxio, the number of model runs per day increased by 4x and the cost of compute was reduced by 95%.

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Flexible and Fast Storage for Deep Learning with Alluxio

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In the age of growing datasets and increased computing power, deep learning has become a popular technique for AI. Deep learning models continue to improve their performance across a variety of domains, with access to more and more data, and the processing power to train larger neural networks. This rise of deep learning advances the state-of-the-art for AI, but also exposes some challenges for the access to data and storage systems. In this article, we further describe the storage challenges for deep learning workloads and how Alluxio can help to solve them.