000 | 03463nam a22005175i 4500 | ||
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001 | 978-3-031-01749-0 | ||
003 | DE-He213 | ||
005 | 20240730163712.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2016 sz | s |||| 0|eng d | ||
020 |
_a9783031017490 _9978-3-031-01749-0 |
||
024 | 7 |
_a10.1007/978-3-031-01749-0 _2doi |
|
050 | 4 | _aTK7867-7867.5 | |
072 | 7 |
_aTJFC _2bicssc |
|
072 | 7 |
_aTEC008010 _2bisacsh |
|
072 | 7 |
_aTJFC _2thema |
|
082 | 0 | 4 |
_a621.3815 _223 |
100 | 1 |
_aBordawekar, Rajesh. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _980046 |
|
245 | 1 | 0 |
_aAnalyzing Analytics _h[electronic resource] / _cby Rajesh Bordawekar, Bob Blainey, Ruchir Puri. |
250 | _a1st ed. 2016. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
|
300 |
_aX, 118 p. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSynthesis Lectures on Computer Architecture, _x1935-3243 |
|
505 | 0 | _aIntroduction -- Overview of Analytics Exemplars -- Accelerating Analytics -- Accelerating Analytics in Practice: Case Studies -- Architectural Desiderata for Analytics -- Bibliography -- Authors' Biographies . | |
520 | _aThis 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. | ||
650 | 0 |
_aElectronic circuits. _919581 |
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650 | 0 |
_aMicroprocessors. _980047 |
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650 | 0 |
_aComputer architecture. _93513 |
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650 | 1 | 4 |
_aElectronic Circuits and Systems. _980048 |
650 | 2 | 4 |
_aProcessor Architectures. _980049 |
700 | 1 |
_aBlainey, Bob. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _980050 |
|
700 | 1 |
_aPuri, Ruchir. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _980051 |
|
710 | 2 |
_aSpringerLink (Online service) _980052 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031006210 |
776 | 0 | 8 |
_iPrinted edition: _z9783031028779 |
830 | 0 |
_aSynthesis Lectures on Computer Architecture, _x1935-3243 _980053 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-01749-0 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
999 |
_c84892 _d84892 |