This week Microsoft and NVIDIA have unveiled a new industry standard hyperscale GPU accelerator they have created in partnership to drive artificial intelligent cloud computing.
Blueprints for the new hyperscale GPU accelerator have now been unveiled and are part of an open-source design released in conjunction with Microsoft’s Project Olympus.
Today’s press release explains more :
HGX-1 does for cloud-based AI workloads what ATX — Advanced Technology eXtended — did for PC motherboards when it was introduced more than two decades ago. It establishes an industry standard that can be rapidly and efficiently embraced to help meet surging market demand. The new architecture is designed to meet the exploding demand for AI computing in the cloud — in fields such as autonomous driving, personalized healthcare, superhuman voice recognition, data and video analytics, and molecular simulations.
Cloud workloads are more diverse and complex than ever. AI training, inferencing and HPC workloads run optimally on different system configurations, with a CPU attached to a varying number of GPUs. The highly modular design of the HGX-1 allows for optimal performance no matter the workload. It provides up to 100x faster deep learning performance compared with legacy CPU-based servers, and is estimated at one-fifth the cost for conducting AI training and one-tenth the cost for AI inferencing.
Jen-Hsun Huang, founder and chief executive officer of NVIDIA adds :
AI is a new computing model that requires a new architecture. The HGX-1 hyperscale GPU accelerator will do for AI cloud computing what the ATX standard did to make PCs pervasive today. It will enable cloud-service providers to easily adopt NVIDIA GPUs to meet surging demand for AI computing.
For more information on the new hyperscale GPU accelerator jump over to the official NVIDIA website for details by following the link below.
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