VMware Cloud on AWS Gets NVIDIA Hardware Boost for AI Workloads
The popular VMware Cloud on AWS service will better handle high-compute workloads for data science, machine learning and AI projects thanks to a new partnership with NVIDIA.
The chip maker and graphics hardware specialist will provide accelerated GPU services to VMware's AWS offering to handle the intensive workloads, specifically via NVIDIA T4 GPUs that will be integrated with Amazon EC2 bare-metal computing instances, along with new NVIDIA Virtual Compute Server (vComputeServer) software.
"These services will enable customers to seamlessly migrate VMware vSphere-based applications and containers to the cloud, unchanged, where they can be modernized to take advantage of high-performance computing, machine learning, data analytics and video processing applications," said a news release issued during the ongoing VMworld U.S. 2019 conference.
Benefits of the partnership were said to 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, 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.
The companies didn't say when the new GPU-accelerated service will be available.
During its conference VMware also announced a new commissioned study that reportedly shows cloud customers can save 59 percent in operational costs with VMware Cloud on AWS in comparison to the equivalent capacity in a traditional datacenter.
"For companies considering a cloud migration, VMware Cloud on AWS represents an ideal destination," the company said. "As evidence, VMware recently commissioned Forrester Consulting to conduct a Total Economic Impact (TEI) study and examined the potential ROI enterprises can realize by migrating to VMware Cloud on AWS. Forrester constructed a composite organization representative of companies interviewed for the study. The composite organization has the following characteristics: 80 servers; 40 to 1 ratio of VMs to applications; $2 million annual software budget and a three-year contract. Overall, the study showed the composite organization saved 59 percent of operational costs in the cloud, versus the equivalent capacity on-premises."
David Ramel is an editor and writer for Converge360.