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Average Ratings 0 Ratings
Description
Featuring up to 8 NVidia® H100 80GB GPUs, each equipped with 16896 CUDA cores and 528 Tensor Cores, this represents NVidia®'s latest flagship technology, setting a high standard for AI performance. The system utilizes the SXM5 NVLINK module, providing a memory bandwidth of 2.6 Gbps and enabling peer-to-peer bandwidth of up to 900GB/s. Additionally, the fourth generation AMD Genoa processors support up to 384 threads with a boost clock reaching 3.7GHz. For NVLINK connectivity, the SXM4 module is employed, which boasts an impressive memory bandwidth exceeding 2TB/s and a P2P bandwidth of up to 600GB/s. The second generation AMD EPYC Rome processors can handle up to 192 threads with a boost clock of 3.3GHz. The designation 8A100.176V indicates the presence of 8 RTX A100 GPUs, complemented by 176 CPU core threads and virtualized capabilities. Notably, even though it has fewer tensor cores compared to the V100, the architecture allows for enhanced processing speeds in tensor operations. Moreover, the second generation AMD EPYC Rome is also available with configurations supporting up to 96 threads and a boost clock of 3.35GHz, further enhancing the system's performance capabilities. This combination of advanced hardware ensures optimal efficiency for demanding computational tasks.
Description
AI Infrastructure Virtualization Software. Enhance oversight and management of AI tasks to optimize GPU usage. Run:AI has pioneered the first virtualization layer specifically designed for deep learning training models. By decoupling workloads from the underlying hardware, Run:AI establishes a collective resource pool that can be allocated as needed, ensuring that valuable GPU resources are fully utilized. This approach allows for effective management of costly GPU allocations. With Run:AI’s scheduling system, IT departments can direct, prioritize, and synchronize computational resources for data science projects with overarching business objectives. Advanced tools for monitoring, job queuing, and the automatic preemption of tasks according to priority levels provide IT with comprehensive control over GPU resource utilization. Furthermore, by forming a versatile ‘virtual resource pool,’ IT executives can gain insights into their entire infrastructure’s capacity and usage, whether hosted on-site or in the cloud, thus facilitating more informed decision-making. This comprehensive visibility ultimately drives efficiency and enhances resource management.
API Access
Has API
API Access
Has API
Integrations
HPE Ezmeral
Pricing Details
$3.01 per hour
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
DataCrunch
Country
Finland
Website
datacrunch.io
Vendor Details
Company Name
Run:AI
Founded
2018
Country
Israel
Website
www.run.ai/
Product Features
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