As companies gather increasing amounts of data, they face a choice over bottlenecks. They can have it in the storage component or the backend compute system. Some companies have attacked the problem by using GPUs to streamline the back end problem or Flash storage to speed up the storage problem. Pure Storage wants to give customers the best of both worlds.
Today it announced, Airi, a complete data storage solution for AI workloads in a box.
Under the hood Airi starts with a Pure Storage FlashBlade, a storage solution that Pure created specifically with AI and machine learning kind of processing in mind. NVidia contributes the pure power with four NVIDIA DGX-1 supercomputers, delivering
four petaFLOPS of performance with NVIDIA ® Tesla ® V100 GPUs. Arista provides the networking hardware to make it all work together with Arista 100GbE switches. The software glue layer comes from the NVIDIA GPU Cloud deep learning stack and Pure Storage AIRI Scaling Toolkit.
Photo: Pure Storage
One interesting aspect of this deal is that the FlashBlade product operates as a separate product inside of the Pure Storage organization. They have put together a team of engineers with AI and data pipeline understanding with the focus inside the company on finding ways to move beyond the traditional storage market and find out where the market is going.
This approach certainly does that, but the question is do companies want to chase the on-prem hardware approach or take this kind of data to the cloud. Pure would argue that the data gravity of AI workloads would make this difficult to achieve with a cloud solution, but we are seeing increasingly large amounts of data moving to the cloud with the cloud vendors providing tools for data scientists to process that data with the tools they need.
If companies choose to go the hardware route over the cloud, each vendor in this equation — whether Nvidia, Pure Storage or Arista — should benefit from a multi-vendor sale. The idea ultimately is to provide customers with a one-stop solution they can install quickly inside a data center if that’s the approach they want to take.
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