Nvidia Reveals GPU-Accelerated Supercomputer in Microsoft Azure Cloud

November 19, 2019 0 By urbantechnoobs

NVIDIA today announced the availability of a new kind of GPU-accelerated supercomputer in the cloud on Microsoft Azure.

Built to handle the most demanding AI and high-performance computing applications, the largest deployments of Azure’s new NDv2 instance rank among the world’s fastest supercomputers, offering up to 800 NVIDIA V100 Tensor Core GPUs interconnected on a single Mellanox InfiniBand backend network. It enables customers for the first time to rent an entire AI supercomputer on-demand from their desk, and match the capabilities of large-scale, on-premises supercomputers that can take months to deploy.

Dramatic Performance, Cost Benefits

The new offering — which is ideal for complex AI, machine learning and HPC workloads — can provide dramatic performance and cost advantages over traditional CPU-based computing. AI researchers needing fast solutions can quickly spin up multiple NDv2 instances and train complex conversational AI models in just hours.

Microsoft and NVIDIA engineers used 64 NDv2 instances on a pre-release version of the cluster to train BERT, a popular conversational AI model, in roughly three hours. This was achieved in part by taking advantage of multi-GPU optimizations provided by NCCL, an NVIDIA CUDA XTM library and high-speed Mellanox interconnects.

Customers can also see benefits from using multiple NDv2 instances to run complex HPC workloads, such as LAMMPS, a popular molecular dynamics application used to simulate materials down to the atomic scale in such areas as drug development and discovery. A single NDv2 instance can deliver an order of magnitude faster results than a traditional HPC node without GPU acceleration for specific types of applications, such as deep learning. This performance can scale linearly to a hundred instances for large-scale simulations.
All NDv2 instances benefit from the GPU-optimized HPC applications, machine learning software and deep learning frameworks such as TensorFlow, PyTorch, and MXNet from the NVIDIA NGC container registry and Azure Marketplace. The registry also offers Helm charts to easily deploy the AI software on Kubernetes clusters.

Availability and Pricing

NDv2 is available now in preview. One instance with eight NVIDIA V100 GPUs can be clustered to scale up to a variety of workload demands. See more details here.