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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

NVIDIA's virtual GPU (vGPU) software delivers high-performance GPU capabilities essential for various tasks, including graphics-intensive virtual workstations and advanced data science applications, allowing IT teams to harness the advantages of virtualization alongside the robust performance provided by NVIDIA GPUs for contemporary workloads. This software is installed on a physical GPU within a cloud or enterprise data center server, effectively creating virtual GPUs that can be distributed across numerous virtual machines, permitting access from any device at any location. The performance achieved is remarkably similar to that of a bare metal setup, ensuring a seamless user experience. Additionally, it utilizes standard data center management tools, facilitating processes like live migration, and enables the provisioning of GPU resources through fractional or multi-GPU virtual machine instances. This flexibility is particularly beneficial for adapting to evolving business needs and supporting remote teams, thus enhancing overall productivity and operational efficiency.

Description

NVIDIA Run:ai is a cutting-edge platform that streamlines AI workload orchestration and GPU resource management to accelerate AI development and deployment at scale. It dynamically pools GPU resources across hybrid clouds, private data centers, and public clouds to optimize compute efficiency and workload capacity. The solution offers unified AI infrastructure management with centralized control and policy-driven governance, enabling enterprises to maximize GPU utilization while reducing operational costs. Designed with an API-first architecture, Run:ai integrates seamlessly with popular AI frameworks and tools, providing flexible deployment options from on-premises to multi-cloud environments. Its open-source KAI Scheduler offers developers simple and flexible Kubernetes scheduling capabilities. Customers benefit from accelerated AI training and inference with reduced bottlenecks, leading to faster innovation cycles. Run:ai is trusted by organizations seeking to scale AI initiatives efficiently while maintaining full visibility and control. This platform empowers teams to transform resource management into a strategic advantage with zero manual effort.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS Marketplace
Armet AI
Azure Marketplace
HPE Ezmeral
IBM Spectrum LSF Suites
IONOS Cloud GPU Servers
IREN Cloud
Mistral Compute
NVIDIA Base Command Manager
NVIDIA Magnum IO
NVIDIA TensorRT
SF Compute

Integrations

AWS Marketplace
Armet AI
Azure Marketplace
HPE Ezmeral
IBM Spectrum LSF Suites
IONOS Cloud GPU Servers
IREN Cloud
Mistral Compute
NVIDIA Base Command Manager
NVIDIA Magnum IO
NVIDIA TensorRT
SF Compute

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

www.nvidia.com/en-us/data-center/virtual-solutions/

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

www.nvidia.com/en-us/software/run-ai/

Product Features

Server Virtualization

Audit Management
Health Monitoring
Live Machine Migration
Multi-OS Virtual Machines
Patching / Backup
Performance Log
Performance Optimization
Rapid Provisioning
Security Management
Type 1 / Type 2 Hypervisor

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Virtualization

Archiving & Retention
Capacity Monitoring
Data Mobility
Desktop Virtualization
Disaster Recovery
Namespace Management
Performance Management
Version Control
Virtual Machine Monitoring

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