IBM Redbooks

Dino Quintero

Bing He

Shawn Bodily

Bernhard Buehler

Primitivo Cervantes

Sergio Baeta

Mihai Huica

Howard Knight

This IBM® Redbooks® publication addresses topics to help answer customers' complex high availability requirements to help maximize systems availability and resources, and provide documentation to transfer the how-to-skills to the worldwide sales and support teams. This publication helps strengthen the position of the IBM PowerHA® SystemMirror® solution with a well-defined and documented deployment models within an IBM Power SystemsTM virtualized environment, providing customers a planned foundation for business resilient infrastructure solutions. This book describes documentation, and other resources available to help the technical teams provide business resilience solutions and support with the IBM PowerHA SystemMirror Standard and Enterprise Editions on IBM Power Systems. This publication targets technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) responsible for providing high availability solutions and support with IBM PowerHA SystemMirror Standard and Enterprise Editions on IBM Power Systems.

IBM PowerHA SystemMirror V7.2 for IBM AIX Updates

Richard Wale

Chris Parsons

Bruno C. Faria

Alfonso Jara

Shota Tsukamoto

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.

IBM PowerAI: Deep Learning Unleashed on IBM Power Systems Servers

Fabio Martins

Bunphot Chuprasertsuk

Maria-Katharina Esser

Matthew W Radford

Anthony Steel

This IBM® Redbooks® publication helps strengthen the position of the IBM PowerHA® SystemMirror® solution with a well-defined and documented deployment models within an IBM Power SystemsTM virtualized environment, which provides customers with a planned foundation for business resilience and disaster recovery for their IBM Power Systems infrastructure solutions. This publication addresses topics to help meet customers' complex high availability and disaster recovery requirements on IBM Power Systems servers to help maximize their systems' availability and resources, and provide technical documentation to transfer the how-to-skills to users and support teams. This book is targeted at technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for providing high availability and disaster recovery solutions and support with IBM PowerHA SystemMirror Standard and Enterprise Editions on IBM Power Systems servers.

IBM PowerHA SystemMirror V7.2.1 for IBM AIX Updates

JinHoon Baek

Guillermo Diez

Hassan Elsetohy

Debra Francis

Rajesh Jeyapaul

Anil Kalavakolanu

Tejaswini Kaujalgi

David Kgabo

Ricardo Puig

Vani Ramagiri

This IBM® Redbooks® publication illustrates implementation, testing, and helpful scenarios with IBM Power® Systems 780 and 795 using the comprehensive set of the Power virtualization features. We focus on the Power Systems functional improvements, in particular, highlighting the reliability, availability, and serviceability (RAS) features of the enterprise servers. This document highlights IBM Power Systems Enterprise Server features, such as system scalability, virtualization features, and logical partitioning among others. This book provides a documented deployment model for Power 780 and Power 795 within a virtualized environment, which allows clients to plan a foundation for exploiting and using the latest features of the IBM Power Systems Enterprise Servers. The target audience for this book includes technical professionals (IT consultants, technical support staff, IT Architects, and IT Specialists) responsible for providing IBM Power Systems solutions and support.

Power Systems Enterprise Servers with PowerVM Virtualization and RAS

Bing He

Books

Your next favorite book is out there