LEADER 14764nam 22010095 450 001 996466229703316 005 20230330003825.0 010 $a3-319-27308-6 024 7 $a10.1007/978-3-319-27308-2 035 $a(CKB)4340000000001245 035 $a(SSID)ssj0001599534 035 $a(PQKBManifestationID)16306002 035 $a(PQKBTitleCode)TC0001599534 035 $a(PQKBWorkID)14892292 035 $a(PQKB)10532568 035 $a(DE-He213)978-3-319-27308-2 035 $a(MiAaPQ)EBC6303945 035 $a(MiAaPQ)EBC5595015 035 $a(Au-PeEL)EBL5595015 035 $a(OCoLC)1076255993 035 $a(PPN)190884746 035 $a(EXLCZ)994340000000001245 100 $a20151217d2015 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aEuro-Par 2015: Parallel Processing Workshops$b[electronic resource] $eEuro-Par 2015 International Workshops, Vienna, Austria, August 24-25, 2015, Revised Selected Papers /$fedited by Sascha Hunold, Alexandru Costan, Domingo Giménez, Alexandru Iosup, Laura Ricci, María Engracia Gómez Requena, Vittorio Scarano, Ana Lucia Varbanescu, Stephen L. Scott, Stefan Lankes, Josef Weidendorfer, Michael Alexander 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (XLIII, 839 p. 323 illus. in color.) 225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v9523 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-319-27307-8 327 $aIntro -- Preface -- Organization -- Workshop Introduction and Organization -- 4th Workshop on Big Data Management in Clouds (BigDataCloud) -- First European Workshop on Parallel and Distributed Computing Education for Undergraduate Students (Euro-EDUPAR) -- 13th International Workshop on Algorithms, Models, and Tools for Parallel Computing on Heterogeneous Platforms (HeteroPar) -- Third Workshop on Large-Scale Distributed Virtual Environments (LSDVE) -- 4th International Workshop on On-Chip Memory Hierarchies and Interconnects (OMHI) -- Third Workshop on Parallel and Distributed Agent-Based Simulations (PADABS) -- First Workshop on Performance Engineering for Large-Scale Graph Analytics (PELGA) -- Second International Workshop on Reproducibility in Parallel Computing (REPPAR) -- 8th Workshop on Resiliency in High-Performance Computing in Clusters, Clouds, and Grids (Resilience) -- Third Workshop on Runtime and Operating Systems for the Many-Core Era (ROME) -- 8th Workshop on UnConventional High-Performance Computing 2015 (UCHPC) -- 10th Workshop on Virtualization in High-Performance Cloud Computing (VHPC) -- Contents -- BigDataCloud - Big Data Management in Clouds -- Distributed Range-Based Meta-Data Management for an In-Memory Storage -- 1 Introduction -- 2 DXRAM Architecture -- 2.1 Chunks -- 2.2 Super-Peer Overlay -- 3 CID-Ranges -- 3.1 CID-Tree -- 3.2 Backup Nodes Integration -- 3.3 Client-Side Caching -- 4 Evaluation -- 4.1 CID-Tree -- 4.2 Client-Side Caching -- 4.3 BG Benchmark -- 5 Related Work -- 6 Conclusions -- References -- Network-Based Data Processing Architecture for Reliable and High-Performance Distributed Storage System -- 1 Introduction -- 1.1 Background -- 1.2 Our Contribution -- 2 Related Work -- 3 System Design -- 3.1 Network-Based Data Processing Architecture -- 3.2 Overview of the System -- 3.3 Data Layout. 327 $a3.4 Switch Architeture -- 3.5 Fallback Mode -- 3.6 Prototype Implementation Overview -- 3.7 Optimized Data Transfer and Processing with RDMA -- 4 Evaluation -- 4.1 Evaluation Target and Conditions -- 4.2 Evaluation Results -- 5 Conclusion and Future Work -- References -- File-Less Approach to Large Scale Data Management -- 1 Introduction -- 2 Related Work -- 3 Filess Vision -- 4 Filess Data Model -- 4.1 Hypergraphs -- 4.2 Overview -- 4.3 Object Composition and Decomposition -- 5 Representing Existing Data Structures and Formats in Filess -- 6 Prototype Design and Implementation -- 7 Conclusions -- References -- Euro-EDUPAR - Parallel and Distributed Computing Education for Undergraduate Students -- Parallel Computing vs. Distributed Computing: A Great Confusion? (Position Paper) -- 1 A (Very) Quick Look at Parallel Computing -- 2 What Is Distributed Computing -- 3 A Fundamental Difference Between Parallel Computing and Distributed Computing -- 4 On the Computational Side: The Hardness of Distributed Computing -- 5 Parallel vs. Distributed Computing: A Schematic View -- 6 An Approach to Teach Distributed Computing -- 7 Distributed Algorithms at the Undergraduate Level -- 8 Distributed Algorithms at the Graduate Level -- 9 When Communication Is Through a Shared Memory -- 10 When Communication Is by Message-Passing -- 11 Conclusion -- A The Non-blocking Atomic Commit Problem -- B Remark on the Notion of a Consensus Number of an Object -- References -- SAUCE: A Web-Based Automated Assessment Tool for Teaching Parallel Programming -- 1 Introduction -- 2 Related Work -- 3 Technical Aspects -- 3.1 Python -- 3.2 SAUCE Web Application -- 3.3 Learning Tools Interoperability -- 3.4 Security Considerations -- 3.5 Distributed Execution -- 4 Use Cases -- 4.1 Solving the Poisson Equation Using MPI -- 4.2 Odd-Even Sort Using OpenMP -- 4.3 Array Reversal Using CUDA. 327 $a4.4 Grading Features -- 5 Conclusion -- References -- Teaching Parallel Programming in Interdisciplinary Studies -- 1 Introduction -- 2 Basic Concepts for Interdisciplinary Students -- 3 Parallel Programming -- 3.1 Shared Memory: OpenMP -- 3.2 Message Passing: MPI -- 3.3 GPUs: CUDA -- 3.4 Performance Analysis: Tools -- 4 Applied Modelling and Simulation -- 5 Conclusions -- References -- On-line Service for Teaching Parallel Programming -- 1 Introduction -- 2 Motivation -- 3 ZawodyWeb System -- 3.1 Overview -- 3.2 Technical Details -- 3.3 Functionality -- 4 UNICORE -- 5 ZawodyWeb Support for Parallel Computing -- 6 Supported Languages -- 6.1 OpenMP -- 6.2 MPI -- 6.3 PCJ -- 7 Results -- 7.1 Practical Evaluation -- 8 Conclusions -- References -- Challenges of a Systematic Approach to Parallel Computing and Supercomputing Education -- 1 Introduction -- 2 Supercomputing Education Infrastructure -- 3 Supercomputing Consortium of Russian Universities -- 4 Supercomputing Education National Project -- 5 Supercomputing Education in Russia's Universities Today -- 5.1 Supercomputing Education at Lomonosov Moscow State University -- 5.2 Supercomputing Education at the Lobachevsky Nizhny Novgorod State University -- 6 Supercomputer Technologies and School Education -- 7 Conclusion -- References -- Teaching Heart Modeling and Simulation on Parallel Computing Systems -- 1 Introduction -- 2 Related Work -- 3 The Course Track ``Heart Modeling and Simulation on Parallel Computing Systems'' -- 3.1 General Course Track Description -- 3.2 Prerequisite Courses -- 3.3 Computational Resources -- 4 Parallel and Distributed Computing Module -- 4.1 Parallel and Distributed Computing -- 4.2 GPU Programming -- 4.3 Xeon Phi Programming -- 5 Numerical Methods Module -- 5.1 Parallel Numerical Methods -- 5.2 Science Hackathon -- 6 Heart Modeling Module. 327 $a6.1 Simulation of Living Systems -- 6.2 Modeling Heart Dynamics on Parallel Computing Systems -- 7 Discussion -- 8 Conclusion -- References -- Integration of ICT in Concurrent and Parallel Programming Lectures -- 1 Introduction -- 1.1 Environment -- 1.2 Objectives -- 1.3 Time Schedule -- 2 What Has Been Innovated? -- 2.1 Development Methodology -- 3 Results -- 3.1 Pre-assessment -- 3.2 Post-assessment -- 4 Conclusions and Future Work -- References -- Teamwork Across Disciplines: High-Performance Computing Meets Engineering -- 1 Interdisciplinary Education and Teamwork -- 1.1 Introduction -- 1.2 Challenges -- 1.3 Outline -- 2 Course Curriculum -- 2.1 Teamwork Across Disciplines: Concept -- 2.2 Realization: Turbulent Flow Simulation on HPC-Systems -- 3 Evaluation -- 4 Conclusion -- References -- An Educational Module Illustrating How Sparse Matrix-Vector Multiplication on Parallel Processors Connects to Graph Partitioning -- 1 Introduction -- 2 A Simple Sparse Matrix Data Structure -- 3 Sparse Matrix-Vector Multiplication Goes Parallel -- 4 An Undirected Graph Model for Data Partitioning -- 5 An Educational Module Illustrating the Connection -- 6 Related Work -- 7 Concluding Remarks -- References -- FERBJMON Tools - Visualizing Thread Access on Java Objects using Lightweight Runtime Monitoring -- 1 Introduction -- 2 Related Work -- 3 Java Runtime Monitoring Using FERBJMON Tools -- 3.1 Bytecode Instrumentation -- 3.2 FerbJmon Call Graph -- 3.3 FERBJMON Timeline Diagram of Thread Accesses -- 4 Examples -- 4.1 Producer and Consumer -- 4.2 Cooperative Task Execution -- 5 Performance of FerbJmon Runtime Monitoring -- 6 Conclusion -- References -- Interdisciplinary Practical Course on Parallel Finite Element Method Using HiFlow3 -- 1 Introduction -- 2 HiFlow3 -- 3 Practical Course on Parallel Numerics -- 4 Summary and Future Work -- References. 327 $aHeteroPar - Algorithms, Models, and Tools for Parallel Computing on Heterogeneous Platforms -- A Randomized LU-based Solver Using GPU and Intel Xeon Phi Accelerators -- 1 Introduction -- 2 Hybrid RBT Solver -- 3 RBT for Graphics Processing Units -- 3.1 Implementation -- 3.2 Performance Results -- 4 RBT for Intel Xeon Phi -- 4.1 Implementation -- 4.2 Performance Results -- 5 Conclusion -- References -- Identifying Optimization Opportunities Within Kernel Execution in GPU Codes -- 1 Introduction -- 1.1 Motivation -- 1.2 Contributions -- 2 Background -- 3 Methodology -- 3.1 Static Analysis -- 3.2 Dynamic Analysis -- 3.3 Instruction Operation Metrics -- 4 Analysis -- 4.1 Applications -- 4.2 Methodology -- 4.3 Results -- 5 Related Work -- 6 Conclusion and Future Work -- References -- Modeling Contention and Mapping Effects in Multi-core Clusters -- 1 Introduction -- 2 Related Work -- 3 Modeling Parallel Algorithms -- 4 Case Study 1: Analyzing the Effect of the Contention in Shared Memory -- 5 Case Sudy 2: Modeling the Mapping Effects on Multi-core Clusters -- 6 Test Platforms -- 7 Conclusions -- References -- Towards Community Detection on Heterogeneous Platforms -- 1 Introduction -- 2 Background -- 2.1 The WCC Metric -- 2.2 The Scalable Community Detection Algorithm -- 3 Design and Implementation -- 3.1 The Massively Parallel Version -- 3.2 The Heterogeneous Version -- 3.3 Automatic Partitioning -- 4 Evaluation -- 4.1 The GPU Version -- 4.2 The Heterogenous Version -- 4.3 End-to-End Performance -- 5 Related Work -- 6 Conclusion and Future Work -- References -- A Design Proposal for a Next Generation Scientific Software Framework -- 1 Introduction -- 2 Requirements -- 3 Approach -- 3.1 Embedded Domain-specific-languages -- 3.2 Tiling -- 3.3 Task Based Runtime Support -- 3.4 Proposed Architecture -- 4 Example: Structured AMR. 327 $a4.1 Granularities and Decomposition. 330 $aThis book constitutes the thoroughly refereed post-conference proceedings of 12 workshops held at the 21st International Conference on Parallel and Distributed Computing, Euro-Par 2015, in Vienna, Austria, in August 2015. The 67 revised full papers presented were carefully reviewed and selected from 121 submissions. The volume includes papers from the following workshops: BigDataCloud: 4th Workshop on Big Data Management in Clouds - Euro-EDUPAR: First European Workshop on Parallel and Distributed Computing Education for Undergraduate Students - Hetero Par: 13th International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms - LSDVE: Third Workshop on Large Scale Distributed Virtual Environments - OMHI: 4th International Workshop on On-chip Memory Hierarchies and Interconnects - PADAPS: Third Workshop on Parallel and Distributed Agent-Based Simulations - PELGA: Workshop on Performance Engineering for Large-Scale Graph Analytics - REPPAR: Second International Workshop on Reproducibility in Parallel Computing - Resilience: 8th Workshop on Resiliency in High Performance Computing in Clusters, Clouds, and Grids - ROME: Third Workshop on Runtime and Operating Systems for the Many Core Era - UCHPC: 8th Workshop on UnConventional High Performance Computing - and VHPC: 10th Workshop on Virtualization in High-Performance Cloud Computing. 410 0$aTheoretical Computer Science and General Issues,$x2512-2029 ;$v9523 606 $aElectronic digital computers?Evaluation 606 $aSoftware engineering 606 $aComputer networks 606 $aDatabase management 606 $aAlgorithms 606 $aApplication software 606 $aSystem Performance and Evaluation 606 $aSoftware Engineering 606 $aComputer Communication Networks 606 $aDatabase Management 606 $aAlgorithms 606 $aComputer and Information Systems Applications 615 0$aElectronic digital computers?Evaluation. 615 0$aSoftware engineering. 615 0$aComputer networks. 615 0$aDatabase management. 615 0$aAlgorithms. 615 0$aApplication software. 615 14$aSystem Performance and Evaluation. 615 24$aSoftware Engineering. 615 24$aComputer Communication Networks. 615 24$aDatabase Management. 615 24$aAlgorithms. 615 24$aComputer and Information Systems Applications. 676 $a004.6 702 $aHunold$b Sascha$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aCostan$b Alexandru$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGiménez$b Domingo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aIosup$b Alexandru$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRicci$b Laura$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGómez Requena$b María Engracia$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aScarano$b Vittorio$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aVarbanescu$b Ana Lucia$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aScott$b Stephen L$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLankes$b Stefan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWeidendorfer$b Josef$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAlexander$b Michael$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466229703316 996 $aEuro-Par 2015: Parallel Processing Workshops$92831775 997 $aUNISA