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This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on High Performance Computing for Computational Science, VECPAR 2010, held in Berkeley, CA, USA, in June 2010. The 34 revised full papers presented together with five invited contributions were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on linear algebra and solvers on emerging architectures, large-scale simulations, parallel and distributed computing, numerical algorithms.
This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on High Performance Computing for Computational Science, VECPAR 2012, held in Kope, Japan, in July 2012. The 28 papers presented together with 7 invited talks were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on CPU computing, applications, finite element method from various viewpoints, cloud and visualization performance, method and tools for advanced scientific computing, algorithms and data analysis, parallel iterative solvers on multicore architectures.
This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on High Performance Computing for Computational Science, VECPAR 2014, held in Eugene, OR, USA, in June/July 2014. The 25 papers presented were carefully reviewed and selected of numerous submissions. The papers are organized in topical sections on algorithms for GPU and manycores, large-scale applications, numerical algorithms, direct/hybrid methods for solving sparse matrices, performance tuning. The volume also contains the papers presented at the 9th International Workshop on Automatic Performance Tuning.
This book constitutes the thoroughly refereed post-conference proceedings of the 13th International Conference on High Performance Computing in Computational Science, VECPAR 2018, held in São Pedro, Brazil, in September 2018. The 17 full papers and one short paper included in this book were carefully reviewed and selected from 32 submissions presented at the conference. The papers cover the following topics: heterogeneous systems, shared memory systems and GPUs, and techniques including domain decomposition, scheduling and load balancing, with a strong focus on computational science applications.
This book constitutes the thoroughly refereed post-conference proceedings of the 12fth International Conference on High Performance Computing in Computational Science, VECPAR 2016, held in Porto, Portugal, in June 2016. The 20 full papers presented were carefully reviewed and selected from 36 submissions. The papers are organized in topical sections on applications; performance modeling and analysis; low level support; environments/libraries to support parallelization.
This book constitutes the refereed proceedings of the 30th International Conference, ISC High Performance 2015, [formerly known as the International Supercomputing Conference] held in Frankfurt, Germany, in July 2015. The 27 revised full papers presented together with 10 short papers were carefully reviewed and selected from 67 submissions. The papers cover the following topics: cost-efficient data centers, scalable applications, advances in algorithms, scientific libraries, programming models, architectures, performance models and analysis, automatic performance optimization, parallel I/O and energy efficiency.
This book presents the state-of-the-art in simulation on supercomputers. Leading researchers present results achieved on systems of the Gauss-Allianz, the association of High-Performance Computing centers in Germany. The reports cover all fields of computational science and engineering, ranging from CFD to Computational Physics and Biology to Computer Science, with a special emphasis on industrially relevant applications. Presenting results for large-scale parallel microprocessor-based systems and GPU and FPGA-supported systems, the book makes it possible to compare the performance levels and usability of various architectures. Its outstanding results in achieving the highest performance for production codes are of particular interest for both scientists and engineers. The book includes a wealth of color illustrations and tables.
This book presents the state of the art in parallel numerical algorithms, applications, architectures, and system software. The book examines various solutions for issues of concurrency, scale, energy efficiency, and programmability, which are discussed in the context of a diverse range of applications. Features: includes contributions from an international selection of world-class authorities; examines parallel algorithm-architecture interaction through issues of computational capacity-based codesign and automatic restructuring of programs using compilation techniques; reviews emerging applications of numerical methods in information retrieval and data mining; discusses the latest issues in dense and sparse matrix computations for modern high-performance systems, multicores, manycores and GPUs, and several perspectives on the Spike family of algorithms for solving linear systems; presents outstanding challenges and developing technologies, and puts these in their historical context.
High-performance system architectures are increasingly exploiting heterogeneity. The HipHaC workshop aims at combining new aspects of parallel, heterogeneous, and reconfigurable microprocessor technologies with concepts of high-performance computing and, particularly, numerical solution methods. Compute- and memory-intensive applications can only benefit from the fullhardware potential if all features on all levels are taken into account in a holistic approach.
This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including: Computational materials science and engineering Computational cardiovascular analysis Multiscale analysis of wind turbines and turbomachinery Weather forecasting Machine learning techniques Parallel Algorithms in Computational Science and Engineering will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work.