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What is HPCWorks?

HPCWorks transforms high-performance computing by providing solutions that are not only rapid and efficient but also enhance productivity in both on-premises and cloud settings. This platform empowers teams to expertly tackle IT challenges, simplify administrative workloads, manage costs effectively, and utilize the latest advancements in AI and mixed workloads through its extensive HPC offerings. Designed to support essential functions in HPC, AI, and high-throughput operations across diverse industries such as healthcare, climate modeling, semiconductor design, simulations, and data analytics, HPCWorks allows organizations to significantly upgrade their computational systems. The technology stands out with its superior GPU acceleration, fast scaling capabilities, flexible scheduling, and optimized workflow designs to meet the requirements of today’s most demanding AI initiatives. Furthermore, its intelligent AI assistant evaluates job resource requirements, reducing wait times and enhancing job throughput by continuously improving from incoming data insights. In addition, HPCWorks provides sophisticated job scheduling and workload management tools, enabling teams to minimize wait times, reduce system downtime, prioritize critical tasks, and effectively manage nodes, CPUs, cloud resources, licenses, GPUs, and more, ensuring an uninterrupted operational flow. With its comprehensive approach, HPCWorks not only enhances computational efficiency but also acts as a vital resource for organizations aiming to optimize their IT processes and achieve greater scalability in their operations. This innovative platform is essential for staying competitive in an ever-evolving technological landscape.

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

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

Siemens

Date Founded

1847

Company Location

Germany

Company Website

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

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/bright-cluster-manager

Categories and Features

HPC

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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