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What is Charg?

Charg is an innovative platform that streamlines the entire lifecycle of AI infrastructure, transforming traditional enterprise-grade supercomputing systems into flexible cloud environments tailored for AI and high-performance computing tasks. The public HPC cloud provided by Charg grants access to a wide range of resources, from a singular GPU to an expansive cluster exceeding 60 PFLOPS, empowering teams to leverage supercomputing power without the burden of owning or maintaining the hardware themselves. It incorporates cutting-edge CRAY supercomputers and the formidable NVIDIA DGX architecture, which combines clustered NVIDIA V100 GPUs with high-speed 200 GbE InfiniBand networking and comprehensive all-flash CEPH storage, delivering exceptional low-latency and high-throughput performance. Charg is meticulously crafted to address demanding AI workflows, scientific inquiries, and engineering calculations, facilitating a multitude of tasks such as model training, large-scale inference, simulations, complex data analysis, finite element analysis, and computational fluid dynamics. By utilizing an API-driven framework, Charg not only integrates effortlessly with existing workflows but also provides scalable on-demand capacity, free from operational constraints, making it a prime solution for various computational requirements. This adaptability guarantees that organizations can swiftly modify their resources in response to fluctuating demands, ensuring efficiency and effectiveness in their computational endeavors. Moreover, the platform prioritizes user experience, making it easier for teams to focus on innovation rather than infrastructure challenges.

What is Bright Cluster Manager?

Bright Cluster Manager provides a diverse array of machine learning frameworks, such as Torch and TensorFlow, to streamline your deep learning endeavors. In addition to these frameworks, Bright features some of the most widely used machine learning libraries, which facilitate dataset access, including MLPython, NVIDIA's cuDNN, the Deep Learning GPU Training System (DIGITS), and CaffeOnSpark, a Spark package designed for deep learning applications. The platform simplifies the process of locating, configuring, and deploying essential components required to operate these libraries and frameworks effectively. With over 400MB of Python modules available, users can easily implement various machine learning packages. Moreover, Bright ensures that all necessary NVIDIA hardware drivers, as well as CUDA (a parallel computing platform API), CUB (CUDA building blocks), and NCCL (a library for collective communication routines), are included to support optimal performance. This comprehensive setup not only enhances usability but also allows for seamless integration with advanced computational resources.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Pricing Information

$0.99 per hour

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Online Training

Training Options

Not specified

Company Facts

Organization Name

Charg

Company Location

United States

Company Website

charg.cloud/

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/bright-cluster-manager

Categories and Features

Cloud GPU

Not specified

Categories and Features

Cluster Management

Not specified

Deep Learning

ML Algorithm Library

HPC

Not specified

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