Analyzing Analytics (Record no. 84892)

000 -LEADER
fixed length control field 03463nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-031-01749-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730163712.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2016 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031017490
-- 978-3-031-01749-0
082 04 - CLASSIFICATION NUMBER
Call Number 621.3815
100 1# - AUTHOR NAME
Author Bordawekar, Rajesh.
245 10 - TITLE STATEMENT
Title Analyzing Analytics
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2016.
300 ## - PHYSICAL DESCRIPTION
Number of Pages X, 118 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Computer Architecture,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Overview of Analytics Exemplars -- Accelerating Analytics -- Accelerating Analytics in Practice: Case Studies -- Architectural Desiderata for Analytics -- Bibliography -- Authors' Biographies .
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Blainey, Bob.
700 1# - AUTHOR 2
Author 2 Puri, Ruchir.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-01749-0
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Koha item type eBooks
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-- Springer International Publishing :
-- Imprint: Springer,
-- 2016.
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-- text
-- txt
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-- computer
-- c
-- rdamedia
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-- online resource
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-- rdacarrier
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-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic circuits.
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-- Microprocessors.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer architecture.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic Circuits and Systems.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Processor Architectures.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1935-3243
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