IT giant Microsoft's cloud division Azure is partnering with chipmaker Nvidia to offer virtual machines with high computational power required for processing huge data sets for machine learning.
"As GPUs [graphics processing units] provide outstanding performance for artificial intelligence (AI) and hyperscale computing (HPC), Microsoft Azure provides a variety of virtual machines enabled with Nvidia GPUs," said Brett Tanzer of Azure Specialized Compute division.
Nvidia offers such machines via its NVIDIA GPU Cloud (NGC) platform.
“Azure users and cloud developers have a new way to accelerate their AI and HPC workflows with powerful GPU-optimized software that takes full advantage of supported Nvidia GPUs on Azure,” Tanzer added.
This means that data scientists, researchers and developers can now use Nvidia GPU instances on Microsoft Azure to speed up their AI and HPC projects - a facility that was not available earlier.
Tanzer said that in order to make it easy to use NGC containers with Azure, a new image called NVIDIA GPU Cloud Image for Deep Learning and HPC is available on Azure Marketplace.
This image provides a pre-configured environment for using containers from NGC on Azure, he said.
The partnership assumes significance because it will help Microsoft expand its customer base, helping it challenge rival Amazon Web Services (AWS) which has already been offering multiple Nvidia-based solutions via its marketplace.
Last year, AWS and Nvidia partnered on multiple initiatives including bringing the faster Volta-based GPU instances especially for AI developers, collaborating to bring deep learning from the cloud to the edge and optimising tools for developers.
"Microsoft is committed to making Azure the cloud of choice for HPC. Azure CycleCloud and NVIDIA GPUs ease integration and the ability to manage and scale," Tanzer said.
Azure CycleCloud is a tool for creating, managing, operating, and optimising HPC clusters of any scale in the Azure environment.
The GPUs that run on Turing architecture combine the power of RT (ray tracing) cores and Tensor Cores for artificial intelligence (AI) inferencing.