Provides the advances in modelling and simulation on supercomputers. Presenting results achieved on systems of the High Performance Computing Center Stuttgart (HLRS) for the year 2005, these reports cover various fields of computational science and engineering, ranging from CFD via computational physics and chemistry to computer science.
Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the author
This book constitutes the refereed proceedings of the 12th International Conference on High-Performance Computing, HiPC 2005, held in Goa, India in December 2005. The 50 revised full papers presented were carefully reviewed and selected from 362 submissions. After the keynote section and the presentation of the 2 awarded best contributions the papers are organized in topical sections on algorithms, applications, architecture, systems software, communication networks, and systems and networks.
Contemporary High Performance Computing: From Petascale toward Exascale focuses on the ecosystems surrounding the world’s leading centers for high performance computing (HPC). It covers many of the important factors involved in each ecosystem: computer architectures, software, applications, facilities, and sponsors. The first part of the book examines significant trends in HPC systems, including computer architectures, applications, performance, and software. It discusses the growth from terascale to petascale computing and the influence of the TOP500 and Green500 lists. The second part of the book provides a comprehensive overview of 18 HPC ecosystems from around the world. Each chapter in this section describes programmatic motivation for HPC and their important applications; a flagship HPC system overview covering computer architecture, system software, programming systems, storage, visualization, and analytics support; and an overview of their data center/facility. The last part of the book addresses the role of clouds and grids in HPC, including chapters on the Magellan, FutureGrid, and LLGrid projects. With contributions from top researchers directly involved in designing, deploying, and using these supercomputing systems, this book captures a global picture of the state of the art in HPC.
This book constitutes the thoroughly refereed proceedings of the 5th International Workshop, PMBS 2014 in New Orleans, LA, USA in November 2014. The 12 full and 2 short papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers cover topics on performance benchmarking and optimization; performance analysis and prediction; and power, energy and checkpointing.
Collects in four chapters single monographs related to the fundamental advances in parallel computer systems and their developments from different points of view (from computer scientists, computer manufacturers, end users) and related to the establishment and evolution of grids fundamentals, implementation and deployment.
Software Engineering for Science provides an in-depth collection of peer-reviewed chapters that describe experiences with applying software engineering practices to the development of scientific software. It provides a better understanding of how software engineering is and should be practiced, and which software engineering practices are effective for scientific software. The book starts with a detailed overview of the Scientific Software Lifecycle, and a general overview of the scientific software development process. It highlights key issues commonly arising during scientific software development, as well as solutions to these problems. The second part of the book provides examples of the use of testing in scientific software development, including key issues and challenges. The chapters then describe solutions and case studies aimed at applying testing to scientific software development efforts. The final part of the book provides examples of applying software engineering techniques to scientific software, including not only computational modeling, but also software for data management and analysis. The authors describe their experiences and lessons learned from developing complex scientific software in different domains. About the Editors Jeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He is one of the primary organizers of the workshop series on Software Engineering for Science (http://www.SE4Science.org/workshops). Neil P. Chue Hong is Director of the Software Sustainability Institute at the University of Edinburgh. His research interests include barriers and incentives in research software ecosystems and the role of software as a research object. George K. Thiruvathukal is Professor of Computer Science at Loyola University Chicago and Visiting Faculty at Argonne National Laboratory. His current research is focused on software metrics in open source mathematical and scientific software.
This book provides basic and fundamental knowledge of various aspects of energy-aware computing at the component, software, and system level. It provides a broad range of topics dealing with power-, energy-, and temperature-related research areas for individuals from industry and academia.
