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Designed for the Data Centric World

As organizations become increasingly reliant on AI/ML and Deep Learning applications to make better decisions, the need to move and analyze massive amounts of data quickly has become critical. The Pavilion HyperParallel Data Platform™ uniquely empowers organizations to process more data, in less time, to achieve what was previously thought impossible. 

Modern AI relies on high performance access to vast amounts of data. While local NVMe SSDs can deliver the needed performance, they lack the capacity required. Scale out storage offers capacity, though they cannot meet performance demands. 

In terms of AI storage solutions, only Pavilion can accelerate AI with storage that delivers the performance of direct attached NVMe SSDs while offering linear scalability to support any size dataset.

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Offering Unmatched Performance

Each Pavilion HyperParallel Data Platform delivers best-in-class performance for block, file, and object data, so you can apply your AI initiatives to any dataset. Collect any type of data, from a variety of sources, and store them all in one location. Only Pavilion delivers industry leading performance for each data type simultaneously.

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Eliminate Data Ingest Challenges

As increasing volumes of data are collected from a variety of sources, ingesting data for analysis becomes a challenge. Before an AI model can analyze data, that data must be created and stored where the AI model can access it.

If the data is being created faster than it can be stored and processed, data will get missed and the AI model predictions will lose accuracy. Pavilion solves this challenge with extreme write performance of up 90GB/s, which is faster than many competitors’ read performance.

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Take Full Advantage of Your GPUs

GPU based computing has revolutionized what AI can do by parallelizing how data is processed. Keeping costly GPUs saturated requires low latency data access. 

To meet these requirements, Pavilion takes advantage of NVMe-oF and RoCE technologies to deliver ultra-low latency. Capable of delivering latencies as low as 100µs for read and 25µs for write measured at the host, Pavilion delivers the same or better performance than direct attached NVMe SSDs.

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Analyze Data at Scale

AI, Deep Learning, and Deep Neural Networks (DNNs) require massive data sets to train. The Pavilion HyperParallel Data Platform provides the performance these tools need, along with exabyte scalability to support any size dataset.

Enabling customers to leverage a high performance parallel file system to manage block storage, a global namespace for file or object data, or use all three in any combination across an unlimited number of systems to meet any capacity or performance requirement. 

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