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Euro-Par 2015: Parallel Processing Workshops [[electronic resource] ] : Euro-Par 2015 International Workshops, Vienna, Austria, August 24-25, 2015, Revised Selected Papers / / edited 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
| Euro-Par 2015: Parallel Processing Workshops [[electronic resource] ] : Euro-Par 2015 International Workshops, Vienna, Austria, August 24-25, 2015, Revised Selected Papers / / edited 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 |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XLIII, 839 p. 323 illus. in color.) |
| Disciplina | 004.6 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Electronic digital computers—Evaluation
Software engineering Computer networks Database management Algorithms Application software System Performance and Evaluation Software Engineering Computer Communication Networks Database Management Computer and Information Systems Applications |
| ISBN | 3-319-27308-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- 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.
3.4 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. 4.4 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. 6.1 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. HeteroPar - 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. 4.1 Granularities and Decomposition. |
| Record Nr. | UNISA-996466229703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Euro-Par 2015: Parallel Processing Workshops : Euro-Par 2015 International Workshops, Vienna, Austria, August 24-25, 2015, Revised Selected Papers / / edited 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
| Euro-Par 2015: Parallel Processing Workshops : Euro-Par 2015 International Workshops, Vienna, Austria, August 24-25, 2015, Revised Selected Papers / / edited 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 |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XLIII, 839 p. 323 illus. in color.) |
| Disciplina | 004.6 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Electronic digital computers—Evaluation
Software engineering Computer networks Database management Algorithms Application software System Performance and Evaluation Software Engineering Computer Communication Networks Database Management Computer and Information Systems Applications |
| ISBN | 3-319-27308-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- 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.
3.4 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. 4.4 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. 6.1 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. HeteroPar - 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. 4.1 Granularities and Decomposition. |
| Record Nr. | UNINA-9910484693003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||