by Adam Armstrong

NVIDIA & VMware To Accelerate ML, Data Science, & AI Workloads

Today at VMworld 2019 in San Francisco, NVIDIA and VMware announced that they were going to deliver accelerated GPU services for VMware Cloud on AWS. This new combination of technology will allows VMware Cloud on AWS uses to power their modern enterprise applications, including AI, machine learning and data analytics workflows in a way that is both highly scalable and secure. 

AI can literally transform enterprise applications. Many organizations, both large and small, are adopting AI and AI strategies to create predictive models. At the same time, machine learning applications are being deployed such as image and voice recognition, advanced financial modeling and natural language processing using neural networks. Both AI and ML applications rely heavily on NVIDIA GPUs for faster training and real-time inference.

VMware Cloud on AWS customers are looking to leverage AI and ML as well and now through this partnership they will have access to a highly scalable and secure cloud service consisting of Amazon EC2 bare metal instances to be accelerated by NVIDIA T4 GPUs and new NVIDIA Virtual Compute Server (vComputeServer) software. Customers using VMware vSphere-based applications will be able to seamlessly migrate them, as well as containers to the VMware Cloud on AWS. Not only will these applications migrate unchanged, they will then have access to all the benefits of the cloud including high performance computing, machine learning, data analytics and video processing applications.

Benefits of VMware Cloud on AWS with NVIDIA GPU for AI, ML and Data Analytics include:

  • Seamless portability: Customers will be able to move workloads powered by NVIDIA vComputeServer software and GPUs with a single click of a button and no downtime using VMware HCX. This will give customers more choice and flexibility to execute training and inference in the cloud or on-premises.
  • Elastic AWS infrastructure: With the ability to automatically scale VMware Cloud on AWS clusters accelerated by NVIDIA T4, administrators will be able to grow or shrink available training environments depending on the needs of their data scientists.
  • Accelerated computing for modern applications: NVIDIA T4 GPUs feature Tensor Cores for acceleration of deep learning inference workflows. When these are combined with vComputeServer software for GPU virtualization businesses have the flexibility to run GPU-accelerated workloads like AI, machine learning and data analytics in virtualization environments for improved security, utilization and manageability.
  • Consistent Hybrid Cloud Infrastructure and Operations: With VMware Cloud on AWS, organizations can establish consistent infrastructure and consistent operations across the hybrid cloud, leveraging VMware industry-standard vSphere, vSAN and NSX as a foundation for modernizing business-critical applications. IT operators will be able to manage GPU-accelerated workloads within vCenter, right alongside GPU-accelerated workloads running on vSphere on-premises.
  • Seamless, end-to-end data science and analytics pipeline: The NVIDIA T4 data center GPU supercharges mainstream servers and accelerates data science techniques using NVIDIA RAPIDS, a collection of NVIDIA GPU acceleration libraries for data science including deep learning, machine learning and data analytics.

NVIDIA

Discuss this story

Sign up for the StorageReview newsletter

Related News and Reviews