Nvidia plans to acquire object storage vendor SwiftStack to help its customers accelerate their artificial intelligence, high-performance computing and data analytics workloads.

The GPU vendor, based in Santa Clara, Calif., will not sell SwiftStack software but will use SwiftStack's 1space as part of its internal artificial intelligence (AI) stack. It will also enable customers to use the SwiftStack software as part of their AI stacks, according to Nvidia's head of enterprise computing, Manuvir Das.

SwiftStack and Nvidia disclosed the acquisition today. They did not reveal the purchase price, but they said it expects the deal to close with weeks.

Nvidia previously worked with SwiftStack Nvidia worked with San Francisco-based SwiftStack for more than 18 months on tackling the data challenges associated with running AI applications at a massive scale. Nvidia found 1space particularly helpful. SwiftStack introduced 1space in 2018 to accelerate data access across public and private clouds through a single object namespace. "Simply put, it's a way of placing the right data in the right place at the right time, so that when the GPU is busy, the data can be sent to it quickly," Das said. Das said Nvidia customers would be able to use enterprise storage from any vendor. The SwiftStack 1space technology will form the "storage orchestration layer" that sits between the compute and the storage to properly place the data so the AI stack runs optimally, Das said. "We are not a storage vendor. We do not intend to be a storage vendor. We're not in the business of selling storage in any form," Das said. "We work very closely with our storage partners. This acquisition is designed to further the integration between different storage technologies and the work we do for AI." We are not a storage vendor. We do not intend to be a storage vendor. Manuvir DasHead of enterprise computing, Nvidia Nvidia partners with storage vendors such as Pure Storage, NetApp, Dell EMC and IBM. The storage vendors integrate Nvidia GPUs into their arrays or sell the GPUs along with their storage in reference architectures.