Azure’s cloud-based AI supercomputer includes powerful and scalable ND- and NC-series virtual machines optimised for AI-distributed training and inference. It is the first public cloud to incorporate NVIDIA’s advanced AI stack, adding tens of thousands of NVIDIA A100 and H100 GPUs, NVIDIA Quantum-2 400Gb/s InfiniBand networking, and the NVIDIA AI Enterprise software suite to its platform.
As part of the collaboration, NVIDIA will utilize Azure’s scalable virtual machine instances to research and further accelerate advances in generative AI, a rapidly emerging area of AI in which foundational models like Megatron Turing NLG 530B are the basis for unsupervised, self-learning algorithms to create new text, code, digital images, video or audio.
The companies will also collaborate to optimize Microsoft’s DeepSpeed deep learning optimization software. NVIDIA’s full stack of AI workflows and software development kits, optimized for Azure, will be made available to Azure enterprise customers.
Quantum
Microsoft Azure’s AI-optimized virtual machine instances are architected with NVIDIA’s most advanced data centre GPUs and are the first public cloud instances to incorporate NVIDIA Quantum-2 400Gb/s InfiniBand networking. Customers can deploy thousands of GPUs in a single cluster to train even the most massive large language models, build the most complex recommender systems at scale, and enable generative AI at scale.
The current Azure instances feature NVIDIA Quantum 200Gb/s InfiniBand networking with NVIDIA A100 GPUs. Future ones will be integrated with NVIDIA Quantum-2 400Gb/s InfiniBand networking and NVIDIA H100 GPUs. Combined with Azure’s advanced compute cloud infrastructure, networking and storage, these AI-optimized offerings will provide scalable peak performance for AI training and deep learning inference workloads of any size.
The platform will support a broad range of AI applications and services, including Microsoft DeepSpeed and the NVIDIA AI Enterprise software suite.
Microsoft DeepSpeed will leverage the NVIDIA H100 Transformer Engine to accelerate transformer-based models used for large language models, generative AI, and writing computer code, among other applications. This technology applies 8-bit floating point precision capabilities to DeepSpeed to dramatically accelerate AI calculations for transformers — at twice the throughput of 16-bit operations.