Unlock high-performance computing with Private Cloud Director's GPU acceleration for virtual machines. Efficiently manage specialized workloads like AI/ML training and video rendering using passthroug
Private Cloud Director (PCD) now supports GPU acceleration for virtual machines, enabling high performance computing workloads that require specialized hardware acceleration. This support addresses the growing enterprise demand for GPU resources during AI/ML training, video rendering, simulation software, and other compute-intensive applications.
Many enterprise customers need GPU acceleration for their critical workloads but previously had to manage these resources manually or outside PCD . With GPU support, you can now:
Assign full physical GPUs using passthrough mode for maximum performance, ideal for demanding ML training jobs, high-end graphics workloads, and applications requiring bare-metal GPU performance.
Share GPU resources efficiently using vGPU mode, allowing multiple virtual machines to access portions of the same physical GPU. This maximizes resource utilization and reduces costs for lighter workloads like AI inference and development environments.
The GPU capabilities serve different roles across your organization, each with specific needs and workflows.
Cloud Administrators and Infrastructure Teams configure GPU hosts, manage resource allocation, and monitor GPU utilization across the infrastructure. As an person with this role or similar you can set up GPU enabled clusters, create resource policies, and ensure optimal GPU resource distribution.
Developers and Data Scientists consume GPU enabled VMs for their high performance workloads. As an person with this role or similar you can select appropriate GPU configurations based on their specific needs from lightweight development and testing to intensive training and inference workloads.
Enterprise Teams running specialized applications benefit from dedicated GPU resources. Engineering teams use GPUs for CAD simulations, media teams for video rendering, and research teams for complex computational tasks.
Before setting up GPU support, familiarize yourself with these essential GPU concepts and terminology.
GPU Passthrough: Assigns an entire physical GPU directly to a single VM. This provides the highest performance but the GPU cannot be shared with other VMs.
vGPU (Virtual GPU): Allows a single physical GPU to be shared across multiple VMs. Each VM receives a "slice" of the GPU with predefined resources.
vGPU Profile: A preset configuration that determines the resources (memory, cores, compute features) allocated to each vGPU slice.
GPU Host Aggregate: A logical grouping of hosts that have GPU capabilities, used to schedule GPU VMs to appropriate hosts.
Private Cloud Director supports these GPU modes for different workload requirements:
Best for: High-performance computing, ML training, applications requiring full GPU access
Resource model: One physical GPU per VM (exclusive access)
Performance: Maximum performance (bare-metal equivalent)
Use cases: Deep learning training, high-end graphics workloads, applications requiring full GPU memory
Learn more about Set up GPU Passthrough
Best for: Multi-tenant environments, development, testing, lighter workloads
Resource model: Multiple VMs share one physical GPU through virtualization
Performance: Good performance with resource sharing
Use cases: AI inference, development environments, graphics virtualization, cost-effective GPU sharing
Learn more about Set up vGPU
PCD supports these NVIDIA GPU models:
GPU Model
Passthrough
vGPU
NVIDIA L4*
NVIDIA T4
NVIDIA L40
NVIDIA L40S
A100
A40
*Private Cloud Director validated
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