Users of the latest NVIDIA Virtual Compute Server software and NVIDIA A100 GPUs boost performance for AI and data science workloads on virtualized infrastructure.
by ANNE HECHT
From AI to VDI, NVIDIA virtual GPU products provide employees with powerful performance for any workflow.
vGPU technology helps IT departments easily scale the delivery of GPU resources, and allows professionals to collaborate and run advanced graphics and computing workflows from the data center or cloud.
Now, NVIDIA is expanding its vGPU software features with a new release that supports the NVIDIA A100 Tensor Core GPU with NVIDIA Virtual Compute Server (vCS) software. Based on NVIDIA vGPU technology, vCS enables AI and compute-intensive workloads to run in VMs.
With support for the NVIDIA A100, the latest NVIDIA vCS delivers significantly faster performance for AI and data analytics workloads.
Powered by the NVIDIA Ampere architecture, the A100 GPU provides strong scaling for GPU compute and deep learning applications running in single- and multi-GPU workstations, servers, clusters, cloud data centers, systems at the edge and supercomputers.
Enterprise data centers standardized on hypervisor-based virtualization can now deploy the A100 with vCS for all the operational benefits that virtualization brings with management and monitoring, without sacrificing performance. And with the workloads running in virtual machines, they can be managed, monitored and run remotely on any device, anywhere.
-Graph shows normalized performance of MIG 2g.10gb running inferencing workload in bare metal (dark green) is nearly the same when running a Virtual Compute Server VM on each MIG instance (light green).
Engineers, researchers, students, data scientists and others can now tackle compute-intensive workloads in a virtual environment, accessing the most powerful GPU in the world through virtual machines that can be securely provisioned in minutes. As NVIDIA A100 GPUs become available in vGPU-certified servers from NVIDIA’s partners, professionals across all industries can accelerate their workloads with powerful performance.
Also, IT professionals get the management, monitoring and multi-tenancy benefits from hypervisors like Red Hat RHV/RHEL.
“Our customers have an increasing need to manage multi-tenant workflows running on virtual machines while providing isolation and security benefits,” said Chuck Dubuque, senior director of product marketing at Red Hat. “The new multi-instance GPU capabilities on NVIDIA A100 GPUs enable a new range of AI-accelerated workloads that run on Red Hat platforms from the cloud to the edge.”
Additional new features of the NVIDIA vGPU September 2020 release include:
1.Multi-Instance GPU (MIG) with VMs: MIG expands the performance and value of NVIDIA A100 by partitioning the GPUs in up to seven instances. Each MIG can be fully isolated with its own high-bandwidth memory, cache and compute cores. Combining MIG with vCS, enterprises can take advantage of management, monitoring and operational benefits of hypervisor-based server virtualization, running a VM on each MIG partition.
2.Heterogeneous Profiles and OSes: With the ability to have different sized instances through MIG, heterogenous vCS profiles can be used on an A100 GPU. This allows VMs of various sizes to be run on a single A100 GPU. Additionally, with VMs running on the NVIDIA GPUs with vCS, heterogeneous operating systems can also be run on an A100 GPU, where different Linux distributions can be run simultaneously in different VMs.
3.GPUDirect Remote Direct Memory Access: Now supported with NVIDIA vCS, GPUDirect RDMA enables network devices to directly access GPU memory, bypassing CPU host memory and decreasing GPU-GPU communication latency to completely offload the CPU in a virtualized environment.
Learn more about NVIDIA Virtual Compute Server, including how the technology was recognized as Disruptive Technology of the Year at VMworld, and see the latest announcement of VMware and NVIDIA partnering to develop enterprise AI solutions.
VMware vSphere support for vCS with A100 will be available next year. The NVIDIA virtual GPU portfolio also includes the Quadro Virtual Workstation for technical and creative professionals, and GRID vPC and vApps for knowledge workers.
GTC Brings the Latest in vGPU
Hear more about how NVIDIA Virtual Compute Server is being used in industries at the GPU Technology Conference, taking place October 5-9.
Adam Tetelman and Jeff Weiss from NVIDIA, joined by Timothy Dietrich from NetApp, will give an overview of NVIDIA Virtual Compute Server technology and discuss use cases and manageability.
As well, a panel of experts from NVIDIA, ManTech and Maxar will share how NVIDIA vGPU is used in their solutions to analyze large amounts of data, enable remote visualization and accelerate compute for video streams and images.
Register now for GTC and check out all the sessions available.