Thousand-Node Alluxio Cluster Powers Game AI Platform – A Production Case Study from Tencent

Tencent is one of the largest technology companies in the world and a leader in the gaming sector. The game AI platform supports AI research and development at Tencent. To provide model training with the best experience, Tencent has implemented a 1000-node Alluxio cluster and designed a scalable, robust, and performant architecture to accelerate the game AI training.

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Speeding Up the Atlas Supercomputing Platform with Fluid + Alluxio

Unisound is an artificial intelligence company focusing on Internet of Things services. Unisound’s AI technology stacks include the perception and expression capabilities of signals, voices, images, and texts, and the cognitive technologies such as knowledge, understanding, analysis, and decision-making, towards a multi-modal AI system. Atlas is the supercomputing platform supporting all kinds of AI applications including model training and reasoning inferencing. 

Speeding Up the Atlas Supercomputing Platform with Fluid + Alluxio

Unisound is an artificial intelligence company focusing on Internet of Things services. Unisound’s AI technology stacks include the perception and expression capabilities of signals, voices, images, and texts, and the cognitive technologies such as knowledge, understanding, analysis, and decision-making, towards a multi-modal AI system. Atlas is the supercomputing platform supporting all kinds of AI applications including model training and reasoning inferencing. 

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“Zero-Copy” Hybrid Bursting with no App Changes

This whitepaper details how to leverage any public cloud (AWS, Google Cloud Platform, or Microsoft Azure) to scale analytics workloads directly on on-prem data without copying and synchronizing the data into the cloud. We will show an example of what it might look like to run on-demand Starburst Presto, Spark, and Hive with Alluxio in the public cloud using on-prem HDFS.

The paper also includes a real world case study on a leading hedge fund based in New York City, who deployed large clusters of Google Compute Engine VMs with Spark and Alluxio using on-prem HDFS as the underlying storage tier.

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China Unicom Uses Alluxio and Spark to Build New Computing Platform to Serve Mobile Users

China Unicom is one of the five largest telecom operators in the world. China Unicom’s booming business in 4G and 5G networks has to serve an exploding base of hundreds of millions of smartphone users. This unprecedented growth brought enormous challenges and new requirements to the data processing infrastructure. The previous generation of its data processing system was based on IBM midrange computers, Oracle databases, and EMC storage devices. This architecture could not scale to process the amounts of data generated by the rapidly expanding number of mobile users. Even after deploying Hadoop and Greenplum database, it was still difficult to cover critical business scenarios with their varying massive data processing requirements.

Achieving 10x acceleration of Spark and Hive Jobs on AWS S3 with Alluxio Tiered Storage

 

The data engineering team at Bazaarvoice, a software-as-a-service digital marketing company based in Austin, Texas, must handle data at massive Internet-scale to serve its customers. Facing challenges with scaling their storage capacity up and provisioning hardware, they turned to Alluxio’s tiered storage system and saw 10x acceleration of their Spark and Hive jobs running on AWS S3.

In this whitepaper you’ll learn:

  • How to build a big data analytics platform on AWS that includes technologies like Hive, Spark, Kafka, Storm, Cassandra, and more
  • How to setup a Hive metastore using a storage tier for hot tables
  • How to leverage tiered storage for maximized read performance

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