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Unleash the Power of AI

The Pavilion HyperParallel Data Platform™ delivers unmatched performance, density, scalability, and flexibility to NVIDIA systems. Pavilion enables organizations to run AI and Analytics operations faster and on any size dataset, so they can do more with their data than they ever thought possible.


Validated by NVIDIA

In performance testing validated by NVIDIA, the Pavilion HyperParallel Data Platform demonstrated unrivaled performance with NVIDIA DGX A100 systems.

Download Solution Brief


High Performance Ingest

Capable of writing data faster than most competitors can read, Pavilion can ingest more data and make it available for AI inference and analytics than any other solution.

Storage (2)

Data at Scale

AI and big data analytics are powered by massive data sets. Pavilion enables DGX systems to quickly process datasets of any size with unmatched performance.

High performance computing requires high performance IO.
The rule is simple, the higher processing power the computer element the more data it can process hence faster data delivery is required.
Fast delivery is just one part. Efficient network interfaces that are required to keep computing going: RDMA, (and) GPUDirect Technologies enable direct communication between GPU powered computer elements and the cluster

Michael Kagan,

NVIDIA CTO at SuperComputing20


High Performance

120GB/s Read @100µs
90GB/s Write @25µs


Efficient Networking

40 x 100 GbE/EDR or 10 x 200 HDR ports
MagnumIO GPUDirect Storage for block and file data

Pavilion Data Takes Pole Position in GPUDirect Race

Blocks and Files says:

“Pavilion Data, the high-end storage array maker, sends data to an Nvidia DGX-A100 GPU server faster than DDN, VAST Data and WekaIO, according to a Nvidia-validated test result.”
Blocks and Files, January 26, 2021

Ultra-Low Latency

GPU powered systems process data in parallel, making low latency IO more critical than ever. With this in mind, NVIDIA developed MagnumIO GPUDirect Storage to deliver data with ultra low latency. In NVIDIA validated testing using GDSIO, Pavilion demonstrated the lowest latency available for both block and file data.


Read: 182GB/s @ 3.87ms
Write: 149GB/s @ 4.51ms


Read: 191GB/s @ 1.75ms
Write: 118GB/s @ 5.60ms

All numbers were tested with one Pavilion system and four GPUs and extrapolated to two Pavilion systems and eight GPUs. Performance is expected to scale linearly

For environments that have not adopted MagnumIO GPUDirect Storage, Pavilion still delivers ultra low latency through NVMe-oF/RoCE. Whether customers use GPUDirect storage or not, Pavilion delivers ultra-low latency.

Linear Scalability for Any Size Dataset

AI engines need to process massive amounts of data to deliver meaningful results, but GPU based systems with limited internal storage cannot contain the volumes of data needed. The Pavilion HyperParallel Data Platform, with up to 2PB of usable capacity per system, delivers the performance of internal storage with the ability to scale performance and capacity linearly, so organizations can use any size dataset.

To learn more read the Pavilion Scalability Solution Brief.

Pavilion and NVIDIA showcase how organizations can maximize investments and accelerate applications

Pavilion partnered with NVIDIA to showcase how organizations can maximize investments and accelerate applications running on NVIDIA platforms.

High performance: How a multi-controller storage architecture shatters expectations for modern applications

How High Performance NVMe-oF Storage Accelerates CPU & GPU-Powered Virtualized Environments Demonstrated by Pavilion

Visually investigating patterns in logs at scale with Graphistry, RAPIDS, and Pavilion

How to respond to rapidly scaling Geospatial Intelligence with OmniSci and Pavilion

“High performance compute requires high performance IO.”

-Michael Kagan, CTO, NVIDIA


Hear from NVIDIA and Pavilion on how organizations are optimizing their GPU investments with the performance, density, scalability and flexibility of the Pavilion HyperParallel Data Platform.