IBM PowerAI : deep learning unleashed on IBM Power Systems servers / Dino Quintero [and six others].

Format:

Book

Author/Creator:

Quintero, Dino, author.

He, Bing, author.

Faria, Bruno, author.

Jara, Alfonso, author.

Parsons, Chris (Machine learning engineer), author.

Tsukamoto, Shota, author.

Wale, Richard, author.

Series:

IBM redbooks.

IBM Redbooks

Language:

English

Subjects (All):

Artificial intelligence--Data processing.

Artificial intelligence.

Client/server computing.

Physical Description:

1 online resource (264 pages).

Edition:

First edition.

Other Title:

International Business Machines Power Artificial Intelligence

Deep learning unleashed on IBM Power Systems Servers

Place of Publication:

Poughkeepsie, New York : IBM, 2018.

System Details:

text file

Summary:

Abstract 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 Spectrum™ 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 Systems™ 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.

Notes:

"Part Number: SG24840900."

Description based on: online resource; title from pdf title page (Safari, viewed October 19, 2019).

Includes bibliographical references.

OCLC:

1029302531