Proceedings Of The Sixth Siam Conference On Parallel Processing For Scientific Computing

The March 1993 SIAM Conference focused on themes from the High Performance Computing and Communications (HPCC) program and, in particular, on grand challenge problems. The proceedings, which contain invited and contributed papers, minisymposia, and poster presentations, consist of two parts based on the conference themes: grand challenge problems or applications, and support for grand challenge problems or infrastructure. Applications include computational fluid dynamics, geophysical modeling, materials science, molecular dynamics, and others. The infrastructure not only emphasizes the development and analysis of numerical algorithms for parallel computing, but also includes parallel environments and tools. No subject index. Annotation copyright by Book News, Inc., Portland, OR

Proceedings -- Parallel Computing.

Proceedings -- Parallel Computing.

This text gives the proceedings for the fifth conference on parallel processing for scientific computing.

The papers in this volume were presented at the Nineteenth SIAM Conference on Parallel Processing for Scientific Computing (PP20), held at February 12-15, 2020 in Seattle, Washington, U.S. This series of conferences has played a key role in promoting parallel scientific computing, algorithms for parallel systems, and parallel numerical algorithms. The conference is unique in its emphasis on the intersection between high performance scientific computing and scalable algorithms, architectures, and software. The conference provides a forum for communication among the applied mathematics, computer science, and computational science and engineering communities.

Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering.

Proceedings -- Parallel Computing.