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OCoLC |
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200210s2020 sz a o 101 0 eng d |
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|a 1140353743
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|a 9783030389611
|q (electronic bk.)
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|a 3030389618
|q (electronic bk.)
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|a 10.1007/978-3-030-38961-1
|2 doi
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|a (OCoLC)1140074342
|z (OCoLC)1140353743
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|a com.springer.onix.9783030389611
|b Springer Nature
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|a QA76.58
|b .I528 2019eb
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|a HCDD
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|a International Conference on Algorithms and Architectures for Parallel Processing
|n (19th :
|d 2019 :
|c Melbourne, Vic.)
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|a Algorithms and architectures for parallel processing :
|b 19th International Conference, ICA3PP 2019, Melbourne, VIC, Australia, December 9-11, 2019, Proceedings.
|n Part II /
|c Sheng Wen, Albert Zomaya, Laurence T. Yang (eds.).
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|a ICA3PP 2019
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|a Cham :
|b Springer,
|c 2020.
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|a 1 online resource (xxi, 699 pages) :
|b illustrations (some color)
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Lecture notes in computer science ;
|v 11945
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|a LNCS sublibrary. SL 1, Theoretical computer science and general issues
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|a International conference proceedings.
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|a Includes author index.
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|a Online resource; title from PDF title page (SpringerLink, viewed February 10, 2020).
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|a The two-volume set LNCS 11944-11945 constitutes the proceedings of the 19th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2019, held in Melbourne, Australia, in December 2019. The 73 full and 29 short papers presented were carefully reviewed and selected from 251 submissions. The papers are organized in topical sections on: Parallel and Distributed Architectures, Software Systems and Programming Models, Distributed and Parallel and Network-based Computing, Big Data and its Applications, Distributed and Parallel Algorithms, Applications of Distributed and Parallel Computing, Service Dependability and Security, IoT and CPS Computing, Performance Modelling and Evaluation. --
|c Provided by publisher.
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|a Intro -- Preface -- Organization -- Contents -- Part II -- Contents -- Part I -- Parallel and Distributed Architectures -- SPM: Modeling Spark Task Execution Time from the Sub-stage Perspective -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Modeling Task-Level Execution Time -- 3.1 Parameters for Prediction -- 3.2 Prediction of Sub-stage Execution Time -- 4 Experiments -- 4.1 Experimental Setup and Data Acquisition -- 4.2 Experimental Results -- 5 Conclusion -- Acknowledgement -- References -- Improving the Parallelism of CESM on GPU -- 1 Introduction -- 2 Background -- 2.1 CESM Overview
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|a 2.2 The Atmosphere Component -- 2.3 Parallelization of CESM -- 3 Performance Optimization Strategies -- 3.1 Bottleneck Analysis of CESM -- 3.2 Solar Radiation Optimization -- 3.3 Longwave Radiation Optimization -- 3.4 Aerosol Masses Conversion Optimization -- 4 Evaluation -- 4.1 Experiment Setup -- 4.2 Performance Analysis -- 5 Related Work -- 6 Conclusion -- References -- Parallel Approach to Sliding Window Sums -- 1 Introduction -- 1.1 Prefix Sum -- 1.2 Sliding Window Sum -- 1.3 The Seed-filter-extend Paradigm -- 1.4 Seed Tables and Minimizers -- 2 Methods -- 2.1 Vector Algorithms -- 3 Results
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|a 4 Conclusion -- References -- Rise the Momentum: A Method for Reducing the Training Error on Multiple GPUs -- 1 Introduction -- 2 Related Work -- 2.1 Parameter Server -- 2.2 Stochastic Gradient Descent and Its Variants -- 3 Multi-GPUs Training -- 3.1 Linear Scaling Rule ch4linearstrategy -- 3.2 Batch Normalization -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 SGD -- 4.3 Adam -- 4.4 NAG -- 4.5 Warm-Up Strategy -- 5 Conclusion -- A Appendix A -- B Appendix B -- References -- Pimiento: A Vertex-Centric Graph-Processing Framework on a Single Machine -- 1 Introduction
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|a 2 Disk-Based Graph Computation -- 2.1 Maintaining Specification Integrity -- 2.2 Computational Model -- 2.3 Update Scheme -- 2.4 Analysis of the I/O Costs -- 3 System Design and Implementation -- 3.1 I/O Thread Optimization -- 3.2 Memory Resource Monitoring -- 4 Experimental Evaluation -- 4.1 Test Setup -- 4.2 Comparison with Other Systems -- 4.3 Optimization of the Update- and I/O Thread Proportions -- 5 Related Work -- 6 Conclusions -- References -- Software Systems and Programming Models -- Parallel Software Testing Sequence Generation Method Target at Full Covering Tested Behaviors
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|a Abstract -- 1 Introduction -- 2 Key Operations -- 3 Testing Sequence Generation Algorithm -- 4 Testing Example and Result Analysis -- 5 Conclusion -- Acknowledgment -- References -- Accurate Network Flow Measurement with Deterministic Admission Policy -- 1 Introduction -- 2 Background and Motivation -- 3 Architectural Overview -- 3.1 Design of DAP -- 3.2 Accuracy Analysis -- 4 dL-DAP -- 4.1 Hash Collision Resolution -- 4.2 Design of dL-DAP -- 5 Evaluation -- 5.1 Experimental Setup -- 5.2 Experimental Result -- 6 Conclusion -- References
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|a Parallel processing (Electronic computers)
|v Congresses.
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|a Computer architecture
|v Congresses.
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|a Computer algorithms
|v Congresses.
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|a Computer algorithms
|2 fast
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|a Computer architecture
|2 fast
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|a Parallel processing (Electronic computers)
|2 fast
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|a proceedings (reports)
|2 aat
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|a Conference papers and proceedings
|2 fast
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|a Conference papers and proceedings.
|2 lcgft
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|a Actes de congrès.
|2 rvmgf
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1 |
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|a Wen, Sheng
|c (Computer scientist),
|e editor.
|1 https://id.oclc.org/worldcat/entity/E39PCjwRPtyY8jJR7FmBmkhXHP
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|a Zomaya, Albert Y.,
|e editor.
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|a Yang, Laurence Tianruo,
|e editor.
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|i has work:
|a Algorithms and architectures for parallel processing Part II (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGFxddYpQH7QyJmYkp4br3
|4 https://id.oclc.org/worldcat/ontology/hasWork
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|a Lecture notes in computer science ;
|v 11945.
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830 |
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0 |
|a LNCS sublibrary.
|n SL 1,
|p Theoretical computer science and general issues.
|
856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-38961-1
|y Click for online access
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|a SPRING-COMP2020
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|a 92
|b HCD
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