Deployment And Usage Guide For Running Ai Workloads On Red Hat Openshift And Nvidia Dgx Systems With Ibm Spectrum Scale eBook Download PDF

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Deployment and Usage Guide for Running AI Workloads on Red Hat OpenShift and NVIDIA DGX Systems with IBM Spectrum Scale

Author: Simon Lorenz

Publisher: IBM Redbooks

Published: 2020-11-30

Total Pages: 80

ISBN-13: 0738459097

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This IBM® Redpaper publication describes the architecture, installation procedure, and results for running a typical training application that works on an automotive data set in an orchestrated and secured environment that provides horizontal scalability of GPU resources across physical node boundaries for deep neural network (DNN) workloads. This paper is mostly relevant for systems engineers, system administrators, or system architects that are responsible for data center infrastructure management and typical day-to-day operations such as system monitoring, operational control, asset management, and security audits. This paper also describes IBM Spectrum® LSF® as a workload manager and IBM Spectrum Discover as a metadata search engine to find the right data for an inference job and automate the data science workflow. With the help of this solution, the data location, which may be on different storage systems, and time of availability for the AI job can be fully abstracted, which provides valuable information for data scientists.

Book Synopsis Deployment and Usage Guide for Running AI Workloads on Red Hat OpenShift and NVIDIA DGX Systems with IBM Spectrum Scale by : Simon Lorenz

Download or read book Deployment and Usage Guide for Running AI Workloads on Red Hat OpenShift and NVIDIA DGX Systems with IBM Spectrum Scale written by Simon Lorenz and published by IBM Redbooks. This book was released on 2020-11-30 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redpaper publication describes the architecture, installation procedure, and results for running a typical training application that works on an automotive data set in an orchestrated and secured environment that provides horizontal scalability of GPU resources across physical node boundaries for deep neural network (DNN) workloads. This paper is mostly relevant for systems engineers, system administrators, or system architects that are responsible for data center infrastructure management and typical day-to-day operations such as system monitoring, operational control, asset management, and security audits. This paper also describes IBM Spectrum® LSF® as a workload manager and IBM Spectrum Discover as a metadata search engine to find the right data for an inference job and automate the data science workflow. With the help of this solution, the data location, which may be on different storage systems, and time of availability for the AI job can be fully abstracted, which provides valuable information for data scientists.

Data Accelerator for AI and Analytics

Author: Simon Lorenz

Publisher: IBM Redbooks

Published: 2021-01-20

Total Pages: 88

ISBN-13: 0738459321

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This IBM® Redpaper publication focuses on data orchestration in enterprise data pipelines. It provides details about data orchestration and how to address typical challenges that customers face when dealing with large and ever-growing amounts of data for data analytics. While the amount of data increases steadily, artificial intelligence (AI) workloads must speed up to deliver insights and business value in a timely manner. This paper provides a solution that addresses these needs: Data Accelerator for AI and Analytics (DAAA). A proof of concept (PoC) is described in detail. This paper focuses on the functions that are provided by the Data Accelerator for AI and Analytics solution, which simplifies the daily work of data scientists and system administrators. This solution helps increase the efficiency of storage systems and data processing to obtain results faster while eliminating unnecessary data copies and associated data management.

Book Synopsis Data Accelerator for AI and Analytics by : Simon Lorenz

Download or read book Data Accelerator for AI and Analytics written by Simon Lorenz and published by IBM Redbooks. This book was released on 2021-01-20 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redpaper publication focuses on data orchestration in enterprise data pipelines. It provides details about data orchestration and how to address typical challenges that customers face when dealing with large and ever-growing amounts of data for data analytics. While the amount of data increases steadily, artificial intelligence (AI) workloads must speed up to deliver insights and business value in a timely manner. This paper provides a solution that addresses these needs: Data Accelerator for AI and Analytics (DAAA). A proof of concept (PoC) is described in detail. This paper focuses on the functions that are provided by the Data Accelerator for AI and Analytics solution, which simplifies the daily work of data scientists and system administrators. This solution helps increase the efficiency of storage systems and data processing to obtain results faster while eliminating unnecessary data copies and associated data management.

High Performant File System Workloads for AI and HPC on AWS using IBM Spectrum Scale

Author: Sanjay Sudam

Publisher: IBM Redbooks

Published: 2021-03-31

Total Pages: 34

ISBN-13: 0738459550

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This IBM® Redpaper® publication is intended to facilitate the deployment and configuration of the IBM Spectrum® Scale based high-performance storage solutions for the scalable data and AI solutions on Amazon Web Services (AWS). Configuration, testing results, and tuning guidelines for running the IBM Spectrum Scale based high-performance storage solutions for the data and AI workloads on AWS are the focus areas of the paper. The LAB Validation was conducted with the Red Hat Linux nodes to IBM Spectrum Scale by using the various Amazon Elastic Compute Cloud (EC2) instances. Simultaneous workloads are simulated across multiple Amazon EC2 nodes running with Red Hat Linux to determine scalability against the IBM Spectrum Scale clustered file system. Solution architecture, configuration details, and performance tuning demonstrate how to maximize data and AI application performance with IBM Spectrum Scale on AWS.

Book Synopsis High Performant File System Workloads for AI and HPC on AWS using IBM Spectrum Scale by : Sanjay Sudam

Download or read book High Performant File System Workloads for AI and HPC on AWS using IBM Spectrum Scale written by Sanjay Sudam and published by IBM Redbooks. This book was released on 2021-03-31 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redpaper® publication is intended to facilitate the deployment and configuration of the IBM Spectrum® Scale based high-performance storage solutions for the scalable data and AI solutions on Amazon Web Services (AWS). Configuration, testing results, and tuning guidelines for running the IBM Spectrum Scale based high-performance storage solutions for the data and AI workloads on AWS are the focus areas of the paper. The LAB Validation was conducted with the Red Hat Linux nodes to IBM Spectrum Scale by using the various Amazon Elastic Compute Cloud (EC2) instances. Simultaneous workloads are simulated across multiple Amazon EC2 nodes running with Red Hat Linux to determine scalability against the IBM Spectrum Scale clustered file system. Solution architecture, configuration details, and performance tuning demonstrate how to maximize data and AI application performance with IBM Spectrum Scale on AWS.

IBM Power Systems Enterprise AI Solutions

Author: Scott Vetter

Publisher: IBM Redbooks

Published: 2019-09-25

Total Pages: 64

ISBN-13: 0738458058

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This IBM® Redpaper publication helps the line of business (LOB), data science, and information technology (IT) teams develop an information architecture (IA) for their enterprise artificial intelligence (AI) environment. It describes the challenges that are faced by the three roles when creating and deploying enterprise AI solutions, and how they can collaborate for best results. This publication also highlights the capabilities of the IBM Cognitive Systems and AI solutions: IBM Watson® Machine Learning Community Edition IBM Watson Machine Learning Accelerator (WMLA) IBM PowerAI Vision IBM Watson Machine Learning IBM Watson Studio Local IBM Video Analytics H2O Driverless AI IBM Spectrum® Scale IBM Spectrum Discover This publication examines the challenges through five different use case examples: Artificial vision Natural language processing (NLP) Planning for the future Machine learning (ML) AI teaming and collaboration This publication targets readers from LOBs, data science teams, and IT departments, and anyone that is interested in understanding how to build an IA to support enterprise AI development and deployment.

Book Synopsis IBM Power Systems Enterprise AI Solutions by : Scott Vetter

Download or read book IBM Power Systems Enterprise AI Solutions written by Scott Vetter and published by IBM Redbooks. This book was released on 2019-09-25 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redpaper publication helps the line of business (LOB), data science, and information technology (IT) teams develop an information architecture (IA) for their enterprise artificial intelligence (AI) environment. It describes the challenges that are faced by the three roles when creating and deploying enterprise AI solutions, and how they can collaborate for best results. This publication also highlights the capabilities of the IBM Cognitive Systems and AI solutions: IBM Watson® Machine Learning Community Edition IBM Watson Machine Learning Accelerator (WMLA) IBM PowerAI Vision IBM Watson Machine Learning IBM Watson Studio Local IBM Video Analytics H2O Driverless AI IBM Spectrum® Scale IBM Spectrum Discover This publication examines the challenges through five different use case examples: Artificial vision Natural language processing (NLP) Planning for the future Machine learning (ML) AI teaming and collaboration This publication targets readers from LOBs, data science teams, and IT departments, and anyone that is interested in understanding how to build an IA to support enterprise AI development and deployment.

IBM PowerAI: Deep Learning Unleashed on IBM Power Systems Servers

Author: Dino Quintero

Publisher: IBM Redbooks

Published: 2019-06-05

Total Pages: 278

ISBN-13: 0738442941

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This IBM® Redbooks® publication is a guide about the IBM PowerAI Deep Learning solution. This book provides an introduction to artificial intelligence (AI) and deep learning (DL), IBM PowerAI, and components of IBM PowerAI, deploying IBM PowerAI, guidelines for working with data and creating models, an introduction to IBM SpectrumTM Conductor Deep Learning Impact (DLI), and case scenarios. IBM PowerAI started as a package of software distributions of many of the major DL software frameworks for model training, such as TensorFlow, Caffe, Torch, Theano, and the associated libraries, such as CUDA Deep Neural Network (cuDNN). The IBM PowerAI software is optimized for performance by using the IBM Power SystemsTM servers that are integrated with NVLink. The AI stack foundation starts with servers with accelerators. graphical processing unit (GPU) accelerators are well-suited for the compute-intensive nature of DL training, and servers with the highest CPU to GPU bandwidth, such as IBM Power Systems servers, enable the high-performance data transfer that is required for larger and more complex DL models. This publication targets technical readers, including developers, IT specialists, systems architects, brand specialist, sales team, and anyone looking for a guide about how to understand the IBM PowerAI Deep Learning architecture, framework configuration, application and workload configuration, and user infrastructure.

Book Synopsis IBM PowerAI: Deep Learning Unleashed on IBM Power Systems Servers by : Dino Quintero

Download or read book IBM PowerAI: Deep Learning Unleashed on IBM Power Systems Servers written by Dino Quintero and published by IBM Redbooks. This book was released on 2019-06-05 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redbooks® publication is a guide about the IBM PowerAI Deep Learning solution. This book provides an introduction to artificial intelligence (AI) and deep learning (DL), IBM PowerAI, and components of IBM PowerAI, deploying IBM PowerAI, guidelines for working with data and creating models, an introduction to IBM SpectrumTM Conductor Deep Learning Impact (DLI), and case scenarios. IBM PowerAI started as a package of software distributions of many of the major DL software frameworks for model training, such as TensorFlow, Caffe, Torch, Theano, and the associated libraries, such as CUDA Deep Neural Network (cuDNN). The IBM PowerAI software is optimized for performance by using the IBM Power SystemsTM servers that are integrated with NVLink. The AI stack foundation starts with servers with accelerators. graphical processing unit (GPU) accelerators are well-suited for the compute-intensive nature of DL training, and servers with the highest CPU to GPU bandwidth, such as IBM Power Systems servers, enable the high-performance data transfer that is required for larger and more complex DL models. This publication targets technical readers, including developers, IT specialists, systems architects, brand specialist, sales team, and anyone looking for a guide about how to understand the IBM PowerAI Deep Learning architecture, framework configuration, application and workload configuration, and user infrastructure.

An Implementation of Red Hat OpenShift Network Isolation Using Multiple Ingress Controllers

Author: Dino Quintero

Publisher: IBM Redbooks

Published: 2021-07-28

Total Pages: 22

ISBN-13: 0738459895

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Red Hat OpenShift is a great platform for developing, testing, and running applications. It handles multitenancy within Red Hat OpenShift Cluster by using users and namespaces, which allows it to run different production applications and workloads on the same Red Hat OpenShift Cluster. This IBM® Redpaper describes network isolation on a multitenant Red Hat OpenShift cluster.

Book Synopsis An Implementation of Red Hat OpenShift Network Isolation Using Multiple Ingress Controllers by : Dino Quintero

Download or read book An Implementation of Red Hat OpenShift Network Isolation Using Multiple Ingress Controllers written by Dino Quintero and published by IBM Redbooks. This book was released on 2021-07-28 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: Red Hat OpenShift is a great platform for developing, testing, and running applications. It handles multitenancy within Red Hat OpenShift Cluster by using users and namespaces, which allows it to run different production applications and workloads on the same Red Hat OpenShift Cluster. This IBM® Redpaper describes network isolation on a multitenant Red Hat OpenShift cluster.

AI and Big Data on IBM Power Systems Servers

Author: Ivaylo B. Bozhinov

Publisher:

Published: 2019

Total Pages:

ISBN-13:

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Book Synopsis AI and Big Data on IBM Power Systems Servers by : Ivaylo B. Bozhinov

Download or read book AI and Big Data on IBM Power Systems Servers written by Ivaylo B. Bozhinov and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

IBM Power Systems Enterprise AI Solutions

Author: Glen Corneau

Publisher:

Published: 2019

Total Pages:

ISBN-13:

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Book Synopsis IBM Power Systems Enterprise AI Solutions by : Glen Corneau

Download or read book IBM Power Systems Enterprise AI Solutions written by Glen Corneau and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

An Implementation of Red Hat OpenShift Network Isolation Using Multiple Ingress Controllers

Author: Dino Quintero

Publisher:

Published: 2021

Total Pages: 0

ISBN-13:

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Book Synopsis An Implementation of Red Hat OpenShift Network Isolation Using Multiple Ingress Controllers by : Dino Quintero

Download or read book An Implementation of Red Hat OpenShift Network Isolation Using Multiple Ingress Controllers written by Dino Quintero and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Red Hat OpenShift is a great platform for developing, testing, and running applications. It handles multitenancy within Red Hat OpenShift Cluster by using users and namespaces, which allows it to run different production applications and workloads on the same Red Hat OpenShift Cluster. This IBM® Redpaper describes network isolation on a multitenant Red Hat OpenShift cluster.

IBM Spectrum LSF Suite: Installation Best Practices Guide

Author: Dino Quintero

Publisher: IBM Redbooks

Published: 2020-04-21

Total Pages: 94

ISBN-13: 0738458570

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This IBM® Redpaper publication describes IBM Spectrum® LSF® Suite best practices installation topics, application checks for workload management, and high availability configurations by using theoretical knowledge and hands-on exercises. These findings are documented by way of sample scenarios. This publication addresses topics for sellers, IT architects, IT specialists, and anyone who wants to implement and manage a high-performing workload management solution with LSF. Moreover, this guide provides documentation to transfer how-to-skills to the technical teams, and solution guidance to the sales team. This publication compliments documentation that is available at IBM Knowledge Center, and aligns with educational materials that are provided by IBM Systems.

Book Synopsis IBM Spectrum LSF Suite: Installation Best Practices Guide by : Dino Quintero

Download or read book IBM Spectrum LSF Suite: Installation Best Practices Guide written by Dino Quintero and published by IBM Redbooks. This book was released on 2020-04-21 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redpaper publication describes IBM Spectrum® LSF® Suite best practices installation topics, application checks for workload management, and high availability configurations by using theoretical knowledge and hands-on exercises. These findings are documented by way of sample scenarios. This publication addresses topics for sellers, IT architects, IT specialists, and anyone who wants to implement and manage a high-performing workload management solution with LSF. Moreover, this guide provides documentation to transfer how-to-skills to the technical teams, and solution guidance to the sales team. This publication compliments documentation that is available at IBM Knowledge Center, and aligns with educational materials that are provided by IBM Systems.