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What is NVIDIA GPU-Optimized AMI?

The NVIDIA GPU-Optimized AMI is a specialized virtual machine image crafted to optimize performance for GPU-accelerated tasks in fields such as Machine Learning, Deep Learning, Data Science, and High-Performance Computing (HPC). With this AMI, users can swiftly set up a GPU-accelerated EC2 virtual machine instance, which comes equipped with a pre-configured Ubuntu operating system, GPU driver, Docker, and the NVIDIA container toolkit, making the setup process efficient and quick. This AMI also facilitates easy access to the NVIDIA NGC Catalog, a comprehensive resource for GPU-optimized software, which allows users to seamlessly pull and utilize performance-optimized, vetted, and NVIDIA-certified Docker containers. The NGC catalog provides free access to a wide array of containerized applications tailored for AI, Data Science, and HPC, in addition to pre-trained models, AI SDKs, and numerous other tools, empowering data scientists, developers, and researchers to focus on developing and deploying cutting-edge solutions. Furthermore, the GPU-optimized AMI is offered at no cost, with an additional option for users to acquire enterprise support through NVIDIA AI Enterprise services. For more information regarding support options associated with this AMI, please consult the 'Support Information' section below. Ultimately, using this AMI not only simplifies the setup of computational resources but also enhances overall productivity for projects demanding substantial processing power, thereby significantly accelerating the innovation cycle in these domains.

What is DataCrunch?

Boasting up to 8 NVidia® H100 80GB GPUs, each outfitted with 16,896 CUDA cores and 528 Tensor Cores, this setup exemplifies NVidia®'s cutting-edge technology, establishing a new benchmark for AI capabilities. The system is powered by the SXM5 NVLINK module, which delivers a remarkable memory bandwidth of 2.6 Gbps while facilitating peer-to-peer bandwidth of as much as 900GB/s. Additionally, the fourth generation AMD Genoa processors support a maximum of 384 threads, achieving a turbo clock speed of 3.7GHz. For NVLINK connectivity, the system makes use of the SXM4 module, which provides a staggering memory bandwidth that surpasses 2TB/s and offers P2P bandwidth of up to 600GB/s. The second generation AMD EPYC Rome processors are capable of managing up to 192 threads and feature a boost clock speed of 3.3GHz. The designation 8A100.176V signifies the inclusion of 8 RTX A100 GPUs, along with 176 CPU core threads and virtualization capabilities. Interestingly, while it contains fewer tensor cores than the V100, the architecture is designed to yield superior processing speeds for tensor computations. Furthermore, the second generation AMD EPYC Rome also comes in configurations that support up to 96 threads with a boost clock reaching 3.35GHz, thus further amplifying the system's overall performance. This impressive amalgamation of advanced hardware guarantees maximum efficiency for even the most demanding computational workloads. Ultimately, such a robust setup is essential for organizations seeking to push the boundaries of AI and machine learning tasks.

Media

Media

Integrations Supported

AWS Marketplace
Amazon Web Services (AWS)
Azure Marketplace
Gaia
NVIDIA NGC
OpenLIT

Integrations Supported

AWS Marketplace
Amazon Web Services (AWS)
Azure Marketplace
Gaia
NVIDIA NGC
OpenLIT

API Availability

Has API

API Availability

Has API

Pricing Information

$3.06 per hour
Free Trial Offered?
Free Version

Pricing Information

$3.01 per hour
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

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/marketplace/pp/prodview-7ikjtg3um26wq

Company Facts

Organization Name

DataCrunch

Company Location

Finland

Company Website

datacrunch.io

Categories and Features

Deep Learning

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

HPC

Categories and Features

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