Virtualization of GPU resources simply and affordably supports AI/ML, remote desktop and other performance-intensive workloads
ANN ARBOR, Mich.—August 16, 2022 — VergeIO, the company with a simpler way to virtualize data centers, has added significant new features to its VergeOS software to give users the performance of GPUs as virtualized, shared resources. This creates a cost-effective, simple and flexible way to perform GPU-based machine learning, remote desktop and other compute-intensive workloads within an agile, scalable, secure VergeOS virtual data center.
VergeOS abstracts compute, network, and storage from commodity servers and creates pools of raw resources that are simple to run and manage, creating feature-rich infrastructures for environments and workloads like clusteredHPC in universities, ultra-converged and hyperconverged enterprises, DevOps andTest/Dev, compliant medical and healthcare, remote and edge compute includingVDI, and xSPs offering hosted services including private clouds.
Current methods for deploying GPUs systemwide are complex and expensive, especially for remote users. Rather than supplying GPUs throughout the organization, VergeIO allows users and applications with access to a virtual data center to share the computing resources of a singleGPU-equipped server. Users/administrators can ‘pass through’ an installed GPU to a virtual data center by simply creating a virtual machine with access to that GPU and its resources.
Alternatively, VergeIO can manage the virtualization of theGPU and serve up vGPUs to virtual data centers. This allows organizations to easily manage vGPUs on the same platform as all other shared resources.
According to Darren Pulsipher, Chief Solution Architect of PublicSector at Intel, “The market is looking for simplicity, and VergeOS is like an‘Easy Button’ for creating a virtual cloud that is so much faster and easier to set up than a private cloud. With VergeOS, my customers can migrate and manage their data centers anywhere and upgrade their hardware with zero downtime.”
“The ability to deploy GPU in a virtualized, converged environment, and access that performance as needed, even remotely, radically reduces the investment in hardware while simplifying management,” said VergeIO CEO Yan Ness. “Our users are increasingly needing GPU performance, from scientific research to machine learning, so vGPU and GPU Passthrough are simple ways to share and pool GPU resources as they do with the rest of their processing capabilities.”
VergeOS is an ultra-thin software—less than 300,000 lines of code—that is easy to install and scale on low-cost commodity hardware and self-manages based on AI/ML. A single license replaces separate hypervisor, networking, storage, data protection, and management tools to simplify operations and downsize complex technology stacks.
Secure virtual data centers based on VergeOS include all enterprise data services like global deduplication, disaster recovery, continuous data protection, snapshots, long-distance synch, and auto-failover. They are ideal for creating honeypots, sandboxes, cyber ranges, air-gapped computing, and secure compliance enclaves to meet regulations such as HIPAA, CUI, SOX, NIST, and PCI. Nested multi-tenancy gives service providers, departmental enterprises, and campuses the ability to assign resources and services to groups and sub-groups.
Currently VergeIO supports NVIDIATesla and Ampere cards; additional licenses must be purchased for vGPU capability.
For a complete list of enhancements please visit https://wiki.verge.io/public/release-notes
About VergeIO
VergeIO provides a simpler way to virtualize data centers and end IT infrastructure complexity. The company’s VergeOS software is the first and only fully integrated virtual cloud software stack to build, deploy and manage virtual data centers. VergeOS delivers significant capital savings, increased operational efficiencies, reduced risk, and rapid scalability. For more information, visit www.verge.io or simply call 855-855-8300.
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Judy Smith
JPR Communications
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