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“We aim to deliver the same value to GPUs that we delivered for CPUs,” said Krish Prasad, senior vice president and general manager, Cloud Platform Business Unit, VMware. “By breaking down existing silos of GPU resources, organizations will be able to achieve better utilization and efficient use of them through sharing—resulting in immediate cost savings. More importantly, organizations will be able to jumpstart new or stalled AI/ML initiatives to drive their business forward by sharing those GPU resources with their teams on-demand with VMware vSphere 7.”
VMware vSphere 7 with Bitfusion Enables Efficient GPU Pooling and Sharing
AI and ML-based applications—deep learning training in particular—rely on hardware accelerators to tackle large and complex computation. With the newly integrated Bitfusion capabilities, VMware vSphere 7 will enable enterprises to pool their powerful GPU resources on their servers and share them within their data centers. That will enable organizations to efficiently and rapidly share GPUs across the network with teams of AI researchers, data scientists and ML developers relying on and/or building AI/ML applications.
Released in April 2020, VMware vSphere 7 was rearchitected into an open platform using Kubernetes to provide a cloud-like experience for developers and operators. The Bitfusion feature of VMware vSphere 7 will leverage GPUs for applications running in virtual machines or containers. Bitfusion can operate in a Kubernetes environment such as VMware Tanzu Kubernetes Grid, and is expected to run side-by-side as customers deploy AI/ML applications as part of an overall modern applications strategy. The Bitfusion feature of VMware vSphere will be available through a single download with no disruption to current infrastructure and will seamlessly integrate with existing workflows and lifecycles.
VMware acquired Bitfusion last year with the intention to integrate the technology into VMware vSphere. Bitfusion offered a software platform that decoupled specific physical resources from the servers they are attached to in the environment. This included sharing GPUs in a virtualized infrastructure, as a pool of network-accessible resources, rather than isolated resources per server.
Dell Technologies Taps VMware for Dell EMC Ready Solutions
Today, Dell Technologies also announced two new Ready Solutions: Dell EMC Ready Solutions for AI: GPU-as-a-Service and Dell EMC Ready Solutions for Virtualized High Performance Computing (HPC). Read more details here.
With the new Dell EMC Ready Solutions for AI: GPU-as-a-Service, customers will be able to quickly and conveniently take advantage of GPUs to supercharge AI projects including predictive analytics, machine learning and deep learning. These Ready Solutions will incorporate VMware Cloud Foundation including VMware vSphere Bitfusion along with Dell EMC servers, storage, networking and services. These solutions will help customers to provide developers and data scientists self-service access to a virtualized accelerator pool to increase the utilization and efficiency of these valuable resources.
The new Dell EMC Ready Solutions for Virtualized HPC (vHPC) will make it simpler for organizations to run demanding AI applications in VMware environments. The ability to virtualize HPC and AI operations with VMware Cloud Foundation including VMware vSphere Bitfusion or VMware vSphere Scale-Out Edition will offer rapid hardware provisioning on demand, faster initial setup, and configuration and ongoing maintenance with centralized management and security. Dell EMC Ready Solutions for vHPC support the intensive compute needs for bioinformatics, computational chemistry and computer-aided engineering.
