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NVIDIA and VMware Cloud on AWS get a Hardware Boost for AI Workloads. The popular VMware Cloud service on AWS will be able to handle more complex workloads for data science, machine-learning, and AI projects through a new partnership. The graphics hardware specialist and chip manufacturer will offer accelerated GPU services to VMware’s AWS offering to deal with the heavy workloads. This will be done using NVIDIA T4 GPUs. These GPUs will be integrated with Amazon EC2 bare metal computing instances. NVIDIA Virtual ComputeServer (vComputeServer). According to a news release, these services will allow customers to seamlessly move VMware vSphere-based containers and applications to the cloud. The partnership will bring benefits such as:

  • Seamless portability: Customers can move workloads using NVIDIA vComputeServer software or GPUs with a single click and without any downtime using VMware HCX. Customers will have more options and flexibility to perform training and inference on-premises or in the cloud.
  • Elastic AWS infrastructure: Administrators will be able, using NVIDIA T4, to automatically scale VMware Cloud on AWS clusters. This will allow them to expand or contract training environments according to their data scientists’ needs.
  • Accelerated computing for modern apps: NVIDIA T4 GPUs have Tensor Cores that accelerate deep learning inference workflows. Combining these with vComputeServer software to GPU virtualization gives businesses the ability to run GPU-accelerated workloads such as AI, machine learning, and data analytics in virtualization environments. This allows for increased security, utilization, and management.
  • Consistent Hybrid Cloud Operations and Infrastructure: VMware Cloud on AWS allows organizations to establish consistent infrastructure and operations across the hybrid cloud. It leverages VMware industry-standard vSphere and vSAN as a foundation for modernizing critical business applications. IT managers will be able manage GPU-accelerated workloads in vCenter as well as workloads on vSphere on premises.
  • Seamless, end to end data science and analytics pipeline: NVIDIA T4 GPU data center GPU supercharges main servers and accelerates data sciences techniques using NVIDIA RAPID, a collection NVIDIA GPU acceleration libraries, for data science, including deep learning and machine learning.

The companies did not say when the new GPU-accelerated service would be available. VMware announced at its conference that it had commissioned a study that showed cloud customers can save 59 per cent on operational costs when they use VMware Cloud on AWS, as compared to traditional datacenters with the same capacity. The company stated that VMware Cloud on AWS is a great option for companies looking to migrate to the cloud. VMware recently commissioned Forrester Consulting for a Total Economic Impact (TEI), which examined the potential ROI that enterprises could realize by migrating from their old systems to VMware Cloud on AWS. Forrester created a composite organization representing the companies that were interviewed for the study. The composite organization includes 80 servers, 40 to 1 ratio of applications to VMs; $2 million annually in software budget; and a three year contract. The study revealed that the composite organization saved 59 per cent of its operational costs by using the cloud instead of the equivalent capacity on-premises.