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IBM Platform Computing Solutions for High Performance and Technical Computing Workloads

Book Description

This IBM® Redbooks® publication is a refresh of IBM Technical Computing Clouds, SG24-8144, Enhance Inbound and Outbound Marketing with a Trusted Single View of the Customer, SG24-8173, and IBM Platform Computing Integration Solutions, SG24-8081, with a focus on High Performance and Technical Computing on IBM Power Systems™.

This book describes synergies across the IBM product portfolio by using case scenarios and showing solutions such as IBM Spectrum™ Scale (formerly GPFS™). This book also reflects and documents the IBM Platform Computing Cloud Services as part of IBM Platform Symphony® for analytics workloads and IBM Platform LSF® (with new features, such as a Hadoop connector, a MapReduce accelerator, and dynamic cluster) for job scheduling. Both products are used to help customers schedule and analyze large amounts of data for business productivity and competitive advantages.

This book is targeted at technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) that are responsible for delivering cost-effective cloud services and big data solutions on IBM Power Systems to uncover insights among client data so that they can take actions to optimize business results, product development, and scientific discoveries.

Table of Contents

  1. Front cover
  2. Notices
    1. Trademarks
  3. IBM Redbooks promotions
  4. Preface
    1. Authors
    2. Now you can become a published author, too!
    3. Comments welcome
    4. Stay connected to IBM Redbooks
  5. Chapter 1. Introduction to IBM Platform Computing
    1. 1.1 IBM Platform Computing solutions purpose
    2. 1.2 Cluster, grids, and clouds
    3. 1.3 IBM Platform Computing Services
      1. 1.3.1 IBM Platform High Performance Cluster
      2. 1.3.2 IBM Load Sharing Facility
      3. 1.3.3 IBM Platform Symphony
    4. 1.4 Benefits and industries
  6. Chapter 2. Technical computing software portfolio
    1. 2.1 Data-centric view for technical computing
    2. 2.2 Storage management
    3. 2.3 Workload management
    4. 2.4 Cluster management
    5. 2.5 Virtual resource management
    6. 2.6 IBM Platform Computing Cloud Services
  7. Chapter 3. Big data, analytics, and risk calculation software portfolio
    1. 3.1 What is big data
    2. 3.2 Big data analytics
      1. 3.2.1 Big data analytics challenge
      2. 3.2.2 Big data analytics solution
      3. 3.2.3 IBM Big Data and analytics areas with solutions
      4. 3.2.4 IBM Big Data analytics advantage
    3. 3.3 Why use an IBM Risk Analytics solutions
      1. 3.3.1 IBM Algorithmics software
      2. 3.3.2 IBM OpenPages software
    4. 3.4 Scenario for minimizing risk and building a better model
      1. 3.4.1 Algo Market Risk
      2. 3.4.2 IBM SPSS Statistics: Monte Carlo simulation
      3. 3.4.3 Scenario
  8. Chapter 4. IBM Spectrum Scale (formerly GPFS)
    1. 4.1 IBM Spectrum Scale overview
    2. 4.2 Spectrum Scale for technical computing
      1. 4.2.1 Argonne Leadership Computing Facility
      2. 4.2.2 Jülich Supercomputing Centre
      3. 4.2.3 IBM Elastic Storage Server
    3. 4.3 Spectrum Scale for big data
    4. 4.4 Installing IBM Spectrum Scale
      1. 4.4.1 Introducing IBM Spectrum Scale
      2. 4.4.2 The strengths of Spectrum Scale
      3. 4.4.3 Preparing the environment on Linux nodes
      4. 4.4.4 Spectrum Scale open source portability layer
      5. 4.4.5 Configuring the cluster
  9. Chapter 5. IBM Platform Load Sharing Facility product family
    1. 5.1 Overview
    2. 5.2 Platform LSF add-ons and capabilities
      1. 5.2.1 Using IBM Platform MapReduce Accelerator for Platform LSF
      2. 5.2.2 Using IBM Platform Data Manager for LSF
    3. 5.3 Using IBM Platform MultiCluster
    4. 5.4 IBM Platform Application Center
  10. Chapter 6. IBM Platform Symphony V7.1 with Application Service Controller
    1. 6.1 Introduction to IBM Platform Symphony V7.1
    2. 6.2 IBM Platform Symphony: An overview
    3. 6.3 IBM Symphony for multitenant designs
      1. 6.3.1 Challenges and advantages
      2. 6.3.2 Multitenant designs
      3. 6.3.3 Requirements gathering
      4. 6.3.4 Building a multitenant big data infrastructure
      5. 6.3.5 Summary
    4. 6.4 Product editions
      1. 6.4.1 IBM Platform Symphony Developer Edition
      2. 6.4.2 IBM Platform Symphony Advanced Edition
    5. 6.5 Optional applications to extend Platform Symphony capabilities
    6. 6.6 Overview of IBM Platform Application Service Controller
      1. 6.6.1 Application framework integrations
      2. 6.6.2 Basic concepts
      3. 6.6.3 Key prerequisites
      4. 6.6.4 IBM Platform Application Service Controller: Application templates
    7. 6.7 IBM Platform Symphony application implementation
      1. 6.7.1 Planning for Platform Symphony
      2. 6.7.2 Accessing the Platform Symphony Management Console
      3. 6.7.3 Configuring a cluster for multitenancy
      4. 6.7.4 Adding an application / tenant
      5. 6.7.5 Configuring application properties
      6. 6.7.6 Associating applications with consumers
      7. 6.7.7 Summary
    8. 6.8 Overview of Apache Spark as part of the IBM Platform Symphony solution
      1. 6.8.1 Hadoop implementations in IBM technology
      2. 6.8.2 Advantages of Spark technology
      3. 6.8.3 Spark deployments
      4. 6.8.4 Spark infrastructure
      5. 6.8.5 Spark deployment templates
    9. 6.9 ASC as the attachment for cloud-native framework: Apache Cassandra
    10. 6.10 Summary
  11. Chapter 7. IBM Platform High Performance Computing
    1. 7.1 Overview
    2. 7.2 IBM Platform HPC advantages
    3. 7.3 Implementation
      1. 7.3.1 Installing a management node
      2. 7.3.2 Installing a compute node
  12. Chapter 8. IBM Platform Cluster Manager
    1. 8.1 Platform Cluster Manager - Standard Edition V4.2
      1. 8.1.1 Platform Cluster Manager - Standard Edition support for POWER8 nodes
      2. 8.1.2 LDAP integration
      3. 8.1.3 Tagging nodes
    2. 8.2 Platform Cluster Manager - Advanced Edition V4.2
      1. 8.2.1 Multitenant environment
  13. Chapter 9. IBM Cloud Manager
    1. 9.1 IBM Software Defined Environment
    2. 9.2 The software-defined everything vision
    3. 9.3 OpenStack
    4. 9.4 Introducing IBM Cloud Manager
    5. 9.5 IBM Cloud Manager value points
  14. Chapter 10. IBM Platform Computing Cloud Services
    1. 10.1 IBM Platform Computing Cloud Services: Purpose and benefits
    2. 10.2 Platform Computing Cloud Services architecture
    3. 10.3 IBM Spectrum Scale high-performance services
    4. 10.4 IBM Platform Symphony services
    5. 10.5 IBM High Performance Services for Hadoop
    6. 10.6 IBM Platform LSF Services
    7. 10.7 Hybrid Platform LSF on-premises with a cloud service scenario
      1. 10.7.1 Upgrading IBM Platform HPC to enable the multicluster function
      2. 10.7.2 Tasks to install IBM Platform LSF in the cloud
      3. 10.7.3 Configuring the multicluster feature
      4. 10.7.4 Configuring job forwarding
      5. 10.7.5 Testing your configuration
      6. 10.7.6 Hybrid cloud is ready
    8. 10.8 Data management on hybrid clouds
      1. 10.8.1 IBM Platform Data Manager for LSF
      2. 10.8.2 IBM Spectrum Scale Active File Management
  15. Appendix A. IBM Platform Computing Message Passing Interface
    1. IBM Platform Computing Message Passing Interface
    2. IBM Platform Computing Message Passing Interface implementation
  16. Appendix B. LDAP server configuration and management
    1. OpenLDAP installation
    2. LDAP user account management
  17. Related publications
    1. IBM Redbooks
    2. Other publications
    3. Online resources
    4. Help from IBM
  18. Back cover