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What is OpenHPC?

Welcome to the OpenHPC website, a collaborative platform that emerged from a community-driven initiative focused on integrating crucial elements required for the effective deployment and management of High Performance Computing (HPC) Linux clusters. This effort includes an array of tools tailored for provisioning, resource management, I/O clients, development utilities, and a variety of scientific libraries, all meticulously designed with a priority on HPC integration. The packages provided by OpenHPC are pre-constructed to function as reusable building blocks for the HPC community, thereby ensuring both efficiency and ease of access. As the community continues to grow, there is a vision to establish and develop abstraction interfaces among key components to enhance modularity and interchangeability throughout the ecosystem. This initiative encompasses a wide range of stakeholders, including software vendors, hardware manufacturers, research institutions, and supercomputing centers, all committed to the smooth integration of popular components available for open-source use. In their collaborative efforts, they not only strive to stimulate innovation and teamwork in High Performance Computing but also aim to continuously improve the tools and technologies that define this dynamic field. This commitment to collective progress is essential for shaping the future landscape of HPC.

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

Has API

Pricing Information

Free
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

The Linux Foundation

Company Location

United States

Company Website

openhpc.community/

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/bright-cluster-manager

Categories and Features

Categories and Features

Deep Learning

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

HPC

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