Slides from our latest talks

Speeding Up Atlas Deep Learning Platform with Alluxio + Fluid

Unisound focuses on Artificial Intelligence services for the Internet of Things. It is an artificial intelligence company with completely independent intellectual property rights and the world’s top intelligent voice technology. Atlas is the Deep Learning platform within Unisound AI Labs, which provides deep learning pipeline support for hundreds of algorithm scientists. This talk shares three real business training scenarios that leverage Alluxio’s distributed caching capabilities and Fluid’s cloud native capabilities, and achieve significant training acceleration and solve platform IO bottlenecks. We hope that the practice of Alluxio & Fluid on Atlas platform will bring benefits to more companies and engineers.

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Fluid: When Alluxio Meets Kubernetes

Nowadays, cloud native environments have attracted lots of data-intensive applications deployed and ran on them, due to the efficient-to-deploy and easy-to-maintain advantages provided by cloud native platforms and frameworks such as Docker, Kubernetes. However, cloud native frameworks does not provide the data abstraction support to the applications natively. Therefore, we build Fluid project, which co-orchestrate data and containers together. We use Alluxio as the cache runtime inside Fluid to warm up hot data. In this report, we will introduce the design and effects of the Fluid project.

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Ultra Fast Deep Learning in Hybrid Cloud using Intel Analytics Zoo & Alluxio

Today, many people run deep learning applications with training data from separate storage such as object storage or remote data centers. This presentation will demo the Intel Analytics Zoo + Alluxio stack, an architecture that enables high performance while keeping cost and resource efficiency balanced without network being I/O bottlenecked.

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Bursting on-premise analytic workloads to Amazon EMR using Alluxio

Data infrastructure on-premises is increasingly complex and cloud adoption is attractive for business agility. Operating a hybrid environment is an approach to start benefiting from cloud elasticity quickly without abandoning the infrastructure on-premises. In this session I will discuss the benefits of using Alluxio’s Data Orchestration Platform to dynamically burst Apache Spark and Presto workloads to Amazon EMR for best performance and agility.

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Speeding Up Spark Performance using Alluxio at China Unicom

Unicom’s traditional batch architecture consists mainly of IOE, Hive, and Greenplum systems. With the development of business, a large number of computing application modules based on diverse scenarios, chimney-like, decentralized applications have emerged. To solve the problem of resource fragmentation, we have introduced a unified computing platform for computing ecology with Spark and Alluxio as the core. Alluxio plays an important role in accelerating data processing and ensuring process stability.

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