CIQ Successfully Tests Popular AI Machine Learning Frameworks and Libraries for Mountain Subscribers

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CIQ, a company focused on innovation with Rocky Linux, has announced new capabilities for its software subscriptions available through the CIQ Mountain offering. The company has conducted testing on popular machine learning frameworks like TensorFlow and PyTorch, as well as other artificial intelligence utilities and libraries such as Jupyter notebooks. These capabilities broaden the range of applications and functions that are compatible with the High-Performance Computing (HPC) subscriptions based on Rocky 8 and Rocky 9, which were announced in June.

The goal of these new capabilities is to demonstrate how the HPC software infrastructure can handle a variety of workloads, from traditional HPC simulations to newer AI use cases. This is particularly important as blended workflows become more common, with HPC and AI working together. According to Brock Taylor, Vice President of High-Performance Computing and Strategic Partners at CIQ, this expanded compatibility will support the rapid rise of these blended workflows.

In addition to working with machine learning frameworks, CIQ has also collaborated with Intel to provide optimized AI tools for Intel architectures. These tools, including TensorFlow and PyTorch, can be used in cloud deployments as well as in conjunction with the CIQ HPC software stacks available in CIQ Mountain. The collaboration with Intel allows CIQ to offer valuable optimizations that Intel has made as a value-added service.

CIQ Mountain is a global repository that offers software and artifact delivery and lifecycle management for turnkey solutions across different infrastructure types, both on-premises and in the cloud. All assets in the Mountain repository are certified, tested, and supported by enterprise-level expertise from CIQ. The repository launched in May with a range of certified and supported assets and turnkey solutions, such as Rocky Linux images, verifiable packages, containers, individual applications, and microservices.

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Over the past month, CIQ has made several additions to the Mountain repository, including full HPC stack subscriptions for Rocky 8 and Rocky 9, builds of Warewulf and Apptainer for use with these versions of Rocky Linux, and rapid bug fix support delivered via the Mountain platform. Furthermore, CIQ has added tested codes for popular open-source research applications like Quantum Espresso, OpenFOAM, LAMMPS, and GROMACS.

CIQ recently hosted a webinar to provide more details on these new features in Mountain, and they will be hosting a series of webinars throughout the rest of 2023 to cover various topics related to their offerings.

CIQ is an organization that powers the next generation of software infrastructure, leveraging capabilities from enterprise, cloud, hyperscale, and HPC systems. They work with every part of the technology stack to deliver stable, scalable, and secure production environments. CIQ is the founding support and services partner of Rocky Linux and is known for creating the next generation federated computing stack.

For more information on CIQ Mountain and its capabilities, visit the CIQ Mountain landing page or reach out to info@ciq.com.

Frequently Asked Questions (FAQs) Related to the Above News

What is CIQ Mountain?

CIQ Mountain is a global repository that offers software and artifact delivery and lifecycle management for turnkey solutions across different infrastructure types, both on-premises and in the cloud. It provides certified, tested, and supported assets and turnkey solutions, such as Rocky Linux images, verifiable packages, containers, individual applications, and microservices.

What are the new capabilities announced for CIQ Mountain?

CIQ has conducted successful testing on popular machine learning frameworks like TensorFlow and PyTorch, as well as other artificial intelligence utilities and libraries such as Jupyter notebooks. These capabilities broaden the range of applications and functions that are compatible with the High-Performance Computing (HPC) subscriptions based on Rocky 8 and Rocky 9.

Why was it important to expand the compatibility of CIQ Mountain with popular frameworks and libraries?

The goal was to demonstrate how the HPC software infrastructure can handle a variety of workloads, from traditional HPC simulations to newer AI use cases. This is crucial as blended workflows, where HPC and AI work together, become more common. The expanded compatibility supports the rapid rise of these blended workflows.

What collaborations has CIQ made to provide optimized AI tools?

CIQ has collaborated with Intel to provide optimized AI tools for Intel architectures. These tools, including TensorFlow and PyTorch, can be used in cloud deployments as well as in conjunction with the CIQ HPC software stacks available in CIQ Mountain. The collaboration with Intel allows CIQ to offer valuable optimizations made by Intel as a value-added service.

What other additions have been made to the Mountain repository?

In addition to the machine learning frameworks and libraries, CIQ has added full HPC stack subscriptions for Rocky 8 and Rocky 9, builds of Warewulf and Apptainer for use with these versions of Rocky Linux, and rapid bug fix support delivered via the Mountain platform. They have also added tested codes for popular open-source research applications like Quantum Espresso, OpenFOAM, LAMMPS, and GROMACS.

Are there any upcoming webinars related to CIQ Mountain?

Yes, CIQ recently hosted a webinar to provide more details on the new features in Mountain, and they will be hosting a series of webinars throughout the rest of 2023 to cover various topics related to their offerings.

How can I get more information about CIQ Mountain?

For more information on CIQ Mountain and its capabilities, you can visit the CIQ Mountain landing page or reach out to info@ciq.com.

Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.

Kunal Joshi
Kunal Joshi
Meet Kunal, our insightful writer and manager for the Machine Learning category. Kunal's expertise in machine learning algorithms and applications allows him to provide a deep understanding of this dynamic field. Through his articles, he explores the latest trends, algorithms, and real-world applications of machine learning, making it accessible to all.

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