Analyzing analytics /
| Main Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) :
Morgan & Claypool,
2016.
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| Series: | Synthesis lectures in computer architecture ;
# 35. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Abstract: | This book aims to achieve the following goals: (1) to provide a high-level survey of key analytics models and algorithms without going into mathematical details; (2) to analyze the usage patterns of these models; and (3) to discuss opportunities for accelerating analytics workloads using software, hardware, and system approaches. The book first describes 14 key analytics models (exemplars) that span data mining, machine learning, and data management domains. For each analytics exemplar, we summarize its computational and runtime patterns and apply the information to evaluate parallelization and acceleration alternatives for that exemplar. Using case studies from important application domains such as deep learning, text analytics, and business intelligence (BI), we demonstrate how various software and hardware acceleration strategies are implemented in practice. This book is intended for both experienced professionals and students who are interested in understanding core algorithms behind analytics workloads. It is designed to serve as a guide for addressing various open problems in accelerating analytics workloads, e.g., new architectural features for supporting analytics workloads, impact on programming models and runtime systems, and designing analytics systems. |
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| Physical Description: | 1 online resource (x, 114 pages) Also available in print. |
| Format: | Mode of access: World Wide Web. System requirements: Adobe Acrobat Reader. |
| Bibliography: | Includes bibliographical references (pages 79-111). |
| ISBN: | 9781627058360 |
| ISSN: | 1935-3243 ; |
| DOI: | 10.2200/S00678ED1V01Y201511CAC035 |
| Access: | Abstract freely available; full-text restricted to subscribers or individual document purchasers. |