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Big data and HPC :[electronic resour...

Grandinetti, Lucio, (1941-)

Big data and HPC :[electronic resource] /ecosystem and convergence

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	005.7
書名/作者:	Big data and HPC : : ecosystem and convergence/ edited by Lucio Grandinetti, Seyedeh Leili Mirtaheri, Reza Shahbazian, Thomas Sterling, and Vladimir Voevodin.
其他作者:	Grandinetti, Lucio,
出版者:	Amsterdam : : IOS Press,, [2018]
面頁冊數:	1 online resource (viii, 325 p.) : : ill.
附註:	Selected papers from the TopHPC2017 congress on Advances in High-Performance Computing and Big Data Analytics in the Exascale Era, held in Tehran, Iran, in April 2017.
標題:	Big data - Congresses.
標題:	High performance computing
ISBN:	9781614998822 (e-book)
ISBN:	9781614998815 (hardback)
書目註:	Includes bibliographical references.
內容註:	Intro; Title Page; Preface; Contents; State of the Art and Future Scenarios; Runtime System Architecture for Dynamic Adaptive Execution; High Performance Computing and Big Data Convergence: A Technical Review; Challenges in HPC Evaluation: Towards a Methodology for Scientific Application Requirements; Scaling Big Data Neuroscience: From Interactive Analytics to HPC Platforms; Big Data Challenges; CBIR on Big Data by Use of Deep Learning; APPGRIT: A Parallel Pipeline for Graph Representation in Text Mining; Introduction and Patent Analysis of Signal Processing for Big Data.
電子資源:	http://ebooks.windeal.com.tw/ios/cover.asp?isbn=9781614998815

Big data and HPC :[electronic resource] /ecosystem and convergence
Big data and HPC :ecosystem and convergence[electronic resource] /edited by Lucio Grandinetti, Seyedeh Leili Mirtaheri, Reza Shahbazian, Thomas Sterling, and Vladimir Voevodin. - Amsterdam :IOS Press,[2018] - 1 online resource (viii, 325 p.) :ill. - Advances in parallel computing,v. 330927-5452 ;. - Advances in parallel computing ;v. 16..

Selected papers from the TopHPC2017 congress on Advances in High-Performance Computing and Big Data Analytics in the Exascale Era, held in Tehran, Iran, in April 2017.

Includes bibliographical references.

Intro; Title Page; Preface; Contents; State of the Art and Future Scenarios; Runtime System Architecture for Dynamic Adaptive Execution; High Performance Computing and Big Data Convergence: A Technical Review; Challenges in HPC Evaluation: Towards a Methodology for Scientific Application Requirements; Scaling Big Data Neuroscience: From Interactive Analytics to HPC Platforms; Big Data Challenges; CBIR on Big Data by Use of Deep Learning; APPGRIT: A Parallel Pipeline for Graph Representation in Text Mining; Introduction and Patent Analysis of Signal Processing for Big Data.

ISBN: 9781614998822 (e-book)

LCCN: 2018952148Subjects--Topical Terms:

511438
Big data
--Congresses.

LC Class. No.: QA76.9.B45 / B52 2018

Dewey Class. No.: 005.7

Big data and HPC :[electronic resource] /ecosystem and convergence
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020 $a 9781614998815 (hardback)
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245 0 0 $a Big data and HPC : $b ecosystem and convergence $h [electronic resource] / $c edited by Lucio Grandinetti, Seyedeh Leili Mirtaheri, Reza Shahbazian, Thomas Sterling, and Vladimir Voevodin.
260 $a Amsterdam : $b IOS Press, $c [2018]
300 $a 1 online resource (viii, 325 p.) : $b ill.
490 1 $a Advances in parallel computing, $x 0927-5452 ; $v v. 33
500 $a Selected papers from the TopHPC2017 congress on Advances in High-Performance Computing and Big Data Analytics in the Exascale Era, held in Tehran, Iran, in April 2017.
504 $a Includes bibliographical references.
505 0 $a Intro; Title Page; Preface; Contents; State of the Art and Future Scenarios; Runtime System Architecture for Dynamic Adaptive Execution; High Performance Computing and Big Data Convergence: A Technical Review; Challenges in HPC Evaluation: Towards a Methodology for Scientific Application Requirements; Scaling Big Data Neuroscience: From Interactive Analytics to HPC Platforms; Big Data Challenges; CBIR on Big Data by Use of Deep Learning; APPGRIT: A Parallel Pipeline for Graph Representation in Text Mining; Introduction and Patent Analysis of Signal Processing for Big Data.
505 8 $a Analysis and Design of IoT Based Physical Location Monitoring SystemAutonomous Task Scheduling for Fast Big Data Processing; Adaptive Resource Management for Distributed Data Analytics; HPC Challenges; High-Performance Massive Subgraph Counting Using Pipelined Adaptive-Group Communication; Final Parallel and Distributed Computing Assignment for Master Students: Description of the Properties and Parallel Structure of Algorithms; Parallel Motion Estimation Based on GPU and Combined GPU-CPU; GPU-Based Iterative Hill Climbing Algorithm to Solve Symmetric Traveling Salesman Problem.
505 8 $a Reliability-Aware Voltage Scaling of Multicore Processors in Dark Silicon EraTime Collection: An Abstraction for Shared Objects in Parallel Programming; Parallel and Distributed Analysis of Microarray Data; Extracting Distributed Architecture from Source Code Using an Evolutionary Approach; An Architectural Approach to Grid Provisioning; Subject Index; Author Index.
650 0 $a Big data $v Congresses. $3 511438
650 0 $a High performance computing $3 184793
700 1 $a Grandinetti, Lucio, $d 1941- $3 386195
700 1 $a Mirtaheri, Seyedeh Leili, $e editor. $3 734697
700 1 $a Shahbazian, Reza, $e editor. $3 734698
700 1 $a Sterling, Thomas, $e editor. $3 734699
700 1 $a Voevodin, Vladimir, $e editor. $3 734700
830 0 $a Advances in parallel computing ; $v v. 16. $3 386196
856 4 0 $u http://ebooks.windeal.com.tw/ios/cover.asp?isbn=9781614998815

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