Ai And Big Data On Ibm Power Systems Servers


Ai And Big Data On Ibm Power Systems Servers
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Ai And Big Data On Ibm Power Systems Servers


Ai And Big Data On Ibm Power Systems Servers
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2019-04-10

Ai And Big Data On Ibm Power Systems Servers written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-10 with Computers categories.


As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments. In this IBM® Redbooks® publication, we cover the best practices for deploying and integrating some of the best AI solutions on the market, including: IBM Watson Machine Learning Accelerator (see note for product naming) IBM Watson Studio Local IBM Power SystemsTM IBM SpectrumTM Scale IBM Data Science Experience (IBM DSX) IBM Elastic StorageTM Server Hortonworks Data Platform (HDP) Hortonworks DataFlow (HDF) H2O Driverless AI We map out all the integrations that are possible with our different AI solutions and how they can integrate with your existing or new data lake. We also walk you through some of our client use cases and show you how some of the industry leaders are using Hortonworks, IBM PowerAI, and IBM Watson Studio Local to drive decision making. We also advise you on your deployment options, when to use a GPU, and why you should use the IBM Elastic Storage Server (IBM ESS) to improve storage management. Lastly, we describe how to integrate IBM Watson Machine Learning Accelerator and Hortonworks with or without IBM Watson Studio Local, how to access real-time data, and security. Note: IBM Watson Machine Learning Accelerator is the new product name for IBM PowerAI Enterprise. Note: Hortonworks merged with Cloudera in January 2019. The new company is called Cloudera. References to Hortonworks as a business entity in this publication are now referring to the merged company. Product names beginning with Hortonworks continue to be marketed and sold under their original names.



Ai And Big Data On Ibm Power Systems Servers


Ai And Big Data On Ibm Power Systems Servers
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Author : Ivaylo B. Bozhinov
language : en
Publisher:
Release Date : 2019

Ai And Big Data On Ibm Power Systems Servers written by Ivaylo B. Bozhinov and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.




Ibm Power Systems Enterprise Ai Solutions


Ibm Power Systems Enterprise Ai Solutions
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2019-09-25

Ibm Power Systems Enterprise Ai Solutions written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-25 with Computers categories.


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


Ibm Powerai Deep Learning Unleashed On Ibm Power Systems Servers
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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2019-06-05

Ibm Powerai Deep Learning Unleashed On Ibm Power Systems Servers written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-05 with Computers categories.


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.



Networking Design For Hpc And Ai On Ibm Power Systems


Networking Design For Hpc And Ai On Ibm Power Systems
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2018-04-26

Networking Design For Hpc And Ai On Ibm Power Systems written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-26 with Computers categories.


This publication provides information about networking design for IBM® High Performance Computing (HPC) and AI for Power SystemsTM. This paper will help you understand the basic requirements when designing a solution, the components in an infrastructure for HPC and AI Systems, the designing of interconnect and data networks with use cases based in real life scenarios, the administration and the Out-Of-Band management networks. We cover all the necessary requirements, provide a good understanding of the technology and include examples for small, medium and large cluster environments. This paper is intended for IT architects, system designers, data center planners, and system administrators who must design or provide a solution for the infrastructure of a HPC cluster.



Ibm Power Systems Enterprise Ai Solutions


Ibm Power Systems Enterprise Ai Solutions
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Author : Glen Corneau
language : en
Publisher:
Release Date : 2019

Ibm Power Systems Enterprise Ai Solutions written by Glen Corneau and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.




Cognitive Computing Featuring The Ibm Power System Ac922


Cognitive Computing Featuring The Ibm Power System Ac922
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2019-10-17

Cognitive Computing Featuring The Ibm Power System Ac922 written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-17 with Computers categories.


This IBM® Redpaper publication describes the advantages of using IBM Power System AC922 for cognitive solutions, and how it can enhance clients' businesses. In order to optimize the hardware and software, IBM partners with NVIDIA, Mellanox, H2O.ai, SQream, Kinetica, and other prominent companies to design the Power AC922 server, specifically enhanced for the cognitive era. Most of its outstanding hardware features, such as NVIDIA NVLink 2.0 and PCIe 4.0, are described in this publication to illustrate the advantages that clients can realize in comparison with IBM competitors. We also include a brief description about what cognitive computing is, and how to use IBM Watson® Machine Learning cognitive solutions to bring more value to your business ecosystem. Additionally, we show performance charts that show the advantages of using Power AC922 versus x86 competitors. In the last chapter, we describe the most remarkable use cases in which IBM solves real problems using cognitive solutions. This IBM Redpaper publication is aimed at IT technical audiences, especially decision-making levels that need a full look at the benefits and improvements that an IBM Cognitive Solution can offer. It also provides valuable information to data science professionals, enabling them to plan their modeling needs. Finally, it offers information to the infrastructure support group in charge of maintaining the solution.



Red Hat Openshift V4 3 On Ibm Power Systems Reference Guide


Red Hat Openshift V4 3 On Ibm Power Systems Reference Guide
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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2020-09-10

Red Hat Openshift V4 3 On Ibm Power Systems Reference Guide written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-10 with Computers categories.


This IBM® Redpaper publication describes how to deploy Red Hat OpenShift V4.3 on IBM Power Systems servers. This book presents reference architectures for deployment, initial sizing guidelines for server, storage, and IBM Cloud® Paks. Moreover, this publication delivers information about initial supported Power System configurations for Red Hat OpenShift V4.3 deployment (bare metal, IBM PowerVM® LE LPARs, and others). This book serves as a guide for how to deploy Red Hat OpenShift V4.3 and provide start guidelines and recommended practices for implementing it on Power Systems and completing it with the supported IBM Cloud Paks. The publication addresses topics for developers, IT architects, IT specialists, sellers, and anyone who wants to implement a Red Hat OpenShift V4.3 and IBM Cloud Paks on IBM Power Systems. This book also provides technical content to transfer how-to skills to the support teams, and solution guidance to the sales team. This book compliments the documentation that is available at IBM Knowledge Center, and also aligns with the educational offerings that are provided by the IBM Systems Technical Education (SSE).



Enterprise Data Warehouse Optimization With Hadoop On Ibm Power Systems Servers


Enterprise Data Warehouse Optimization With Hadoop On Ibm Power Systems Servers
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2018-01-31

Enterprise Data Warehouse Optimization With Hadoop On Ibm Power Systems Servers written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-31 with Computers categories.


Data warehouses were developed for many good reasons, such as providing quick query and reporting for business operations, and business performance. However, over the years, due to the explosion of applications and data volume, many existing data warehouses have become difficult to manage. Extract, Transform, and Load (ETL) processes are taking longer, missing their allocated batch windows. In addition, data types that are required for business analysis have expanded from structured data to unstructured data. The Apache open source Hadoop platform provides a great alternative for solving these problems. IBM® has committed to open source since the early years of open Linux. IBM and Hortonworks together are committed to Apache open source software more than any other company. IBM Power SystemsTM servers are built with open technologies and are designed for mission-critical data applications. Power Systems servers use technology from the OpenPOWER Foundation, an open technology infrastructure that uses the IBM POWER® architecture to help meet the evolving needs of big data applications. The combination of Power Systems with Hortonworks Data Platform (HDP) provides users with a highly efficient platform that provides leadership performance for big data workloads such as Hadoop and Spark. This IBM RedpaperTM publication provides details about Enterprise Data Warehouse (EDW) optimization with Hadoop on Power Systems. Many people know Power Systems from the IBM AIX® platform, but might not be familiar with IBM PowerLinuxTM, so part of this paper provides a Power Systems overview. A quick introduction to Hadoop is provided for those not familiar with the topic. Details of HDP on Power Reference architecture are included that will help both software architects and infrastructure architects understand the design. In the optimization chapter, we describe various topics: traditional EDW offload, sizing guidelines, performance tuning, IBM Elastic StorageTM Server (ESS) for data-intensive workload, IBM Big SQL as the common structured query language (SQL) engine for Hadoop platform, and tools that are available on Power Systems that are related to EDW optimization. We also dedicate some pages to the analytics components (IBM Data Science Experience (IBM DSX) and IBM SpectrumTM Conductor for Spark workload) for the Hadoop infrastructure.



Ibm Power Systems Bits Understanding Ibm Patterns For Cognitive Systems


Ibm Power Systems Bits Understanding Ibm Patterns For Cognitive Systems
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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2018-02-14

Ibm Power Systems Bits Understanding Ibm Patterns For Cognitive Systems written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-14 with Computers categories.


This IBM® RedpaperTM publication addresses IBM Patterns for Cognitive Systems topics to anyone developing, implementing, and using Cognitive Solutions on IBM Power SystemsTM servers. Moreover, this publication provides documentation to transfer the knowledge to the sales and technical teams. This publication describes IBM Patterns for Cognitive Systems. Think of a pattern as a use case for a specific scenario, such as event-based real-time marketing for real-time analytics, anti-money laundering, and addressing data oceans by reducing the cost of Hadoop. These examples are just a few of the cognitive patterns that are now available. Patterns identify and address challenges for cognitive infrastructures. These entry points then help you understand where you are on the cognitive journey and enables IBM to demonstrate the set of solutions capabilities for each lifecycle stage. This book targets technical readers, including IT specialist, systems architects, data scientists, developers, and anyone looking for a guide about how to unleash the cognitive capabilities of IBM Power Systems by using patterns.