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What is NVIDIA Run:ai?

NVIDIA Run:ai is a powerful enterprise platform engineered to revolutionize AI workload orchestration and GPU resource management across hybrid, multi-cloud, and on-premises infrastructures. It delivers intelligent orchestration that dynamically allocates GPU resources to maximize utilization, enabling organizations to run 20 times more workloads with up to 10 times higher GPU availability compared to traditional setups. Run:ai centralizes AI infrastructure management, offering end-to-end visibility, actionable insights, and policy-driven governance to align compute resources with business objectives effectively. Built on an API-first, open architecture, the platform integrates with all major AI frameworks, machine learning tools, and third-party solutions, allowing seamless deployment flexibility. The included NVIDIA KAI Scheduler, an open-source Kubernetes scheduler, empowers developers and small teams with flexible, YAML-driven workload management. Run:ai accelerates the AI lifecycle by simplifying transitions from development to training and deployment, reducing bottlenecks, and shortening time to market. It supports diverse environments, from on-premises data centers to public clouds, ensuring AI workloads run wherever needed without disruption. The platform is part of NVIDIA's broader AI ecosystem, including NVIDIA DGX Cloud and Mission Control, offering comprehensive infrastructure and operational intelligence. By dynamically orchestrating GPU resources, Run:ai helps enterprises minimize costs, maximize ROI, and accelerate AI innovation. Overall, it empowers data scientists, engineers, and IT teams to collaborate effectively on scalable AI initiatives with unmatched efficiency and control.

What is HPCWorks Grid Engine?

HPCWorks Grid Engine is a Siemens workload management and distributed resource optimization solution for high-performance computing environments. It helps organizations improve throughput, application performance, and resource utilization across shared on-premises, cloud, and hybrid infrastructure. The platform is designed to support some of today’s largest AI and HPC workloads and has been proven in environments with more than one million cores. HPCWorks Grid Engine enables teams to maximize the use of specialized computing resources, including GPUs, while reducing bottlenecks and improving job turnaround times. Its workload management capabilities help lower hardware, software, and data center costs by scheduling jobs more efficiently and reducing idle resources. License-first scheduling helps reduce wait times and downtime by aligning software license availability with computing demand. Organizations can deploy HPC clusters in their preferred cloud environments and manage workloads across a wide range of operating systems and processor architectures. The software supports thousands of commercial and open-source applications across industries such as life sciences, manufacturing, energy, semiconductor, and research. Priority and utilization policies allow administrators to align cluster workloads with business goals, such as maximizing machine utilization or prioritizing critical departmental workloads. Quotas and limits help teams manage usage by user, group, or project while maintaining control over cluster workload volumes. With comprehensive monitoring and reporting, HPCWorks Grid Engine gives organizations the visibility they need to optimize resources, improve productivity, and deliver faster results.

Media

Media

Integrations Supported

HPCWorks Monitor
HPE Ezmeral

Integrations Supported

HPCWorks Monitor
HPE Ezmeral

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

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

Company Facts

Organization Name

Siemens

Date Founded

1847

Company Location

Germany

Company Website

www.siemens.com/en-us/products/hpcworks/grid-engine/

Categories and 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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