Using Hpc For Computational Fluid Dynamics

Using HPC for Computational Fluid Dynamics: A Guide to High Performance Computing for CFD Engineers offers one of the first self-contained guides on the use of high performance computing for computational work in fluid dynamics. Beginning with an introduction to HPC, including its history and basic terminology, the book moves on to consider how modern supercomputers can be used to solve common CFD challenges, including the resolution of high density grids and dealing with the large file sizes generated when using commercial codes. Written to help early career engineers and post-graduate students compete in the fast-paced computational field where knowledge of CFD alone is no longer sufficient, the text provides a one-stop resource for all the technical information readers will need for successful HPC computation. Offers one of the first self-contained guides on the use of high performance computing for computational work in fluid dynamics Tailored to the needs of engineers seeking to run CFD computations in a HPC environment

Using HPC for Computational Fluid Dynamics: A Guide to High Performance Computing for CFD Engineers offers one of the first self-contained guides on the use of high performance computing for computational work in fluid dynamics. Beginning with an introduction to HPC, including its history and basic terminology, the book moves on to consider how modern supercomputers can be used to solve common CFD challenges, including the resolution of high density grids and dealing with the large file sizes generated when using commercial codes. Written to help early career engineers and post-graduate students compete in the fast-paced computational field where knowledge of CFD alone is no longer sufficient, the text provides a one-stop resource for all the technical information readers will need for successful HPC computation. Offers one of the first self-contained guides on the use of high performance computing for computational work in fluid dynamics Tailored to the needs of engineers seeking to run CFD computations in a HPC environment.

Proceedings of the Summerschool on High Performance Computing in Fluid Dynamics, held at Delft University of Technology, the Netherlands, June 24-28 1996

Supercomputer technologies have evolved rapidly since the first commercial-based supercomputer, CRAY-1 was introduced in 1976. In early 1980's three Japanese super computers appeared, and Cray Research delivered the X-MP series. These machines including the later-announced CRAY-2 and NEC SX series created one generation of supercomputers, and the market was spread dramatically. The peak performance was higher than 1 GFLOPS and the compiler improvement was remarkable. There appeared many articles and books that described their architecture and their performance on The late 1980's saw a new generation of supercomputers. several benchmark problems. Following CRAY Y-MP and Hitachi S-820 delivered in 1988, NEC announced SX-3 and Fujitsu announced the VP2000 series in 1990. In addition, Cray Research announced the Y-MP C-90 late in 1991. The peak performance of these machines reached several to a few ten's GFLOPS. The hardware characteristics of these machines are known, but their practical performance has not been well documented so far. Computational Fluid Dynamics (CFD) is one of the important research fields that have been progressing with the growth of supercomputers. Today's fluid dynamic re search cannot be discussed without supercomputers and since CFD is one of the im portant users of supercomputers, future development of supercomputers has to take the requirements of CFD into account. There are many benchmark reports available today. However, they mostly use so called kernels. For fluid dynamics researchers, benchmark test on real fluid dynamic codes are necessary.

The book introduces modern high-order methods for computational fluid dynamics. As compared to low order finite volumes predominant in today's production codes, higher order discretizations significantly reduce dispersion errors, the main source of error in long-time simulations of flow at higher Reynolds numbers. A major goal of this book is to teach the basics of the discontinuous Galerkin (DG) method in terms of its finite volume and finite element ingredients. It also discusses the computational efficiency of high-order methods versus state-of-the-art low order methods in the finite difference context, given that accuracy requirements in engineering are often not overly strict. The book mainly addresses researchers and doctoral students in engineering, applied mathematics, physics and high-performance computing with a strong interest in the interdisciplinary aspects of computational fluid dynamics. It is also well-suited for practicing computational engineers who would like to gain an overview of discontinuous Galerkin methods, modern algorithmic realizations, and high-performance implementations.

This book is the result of a careful selection of contributors in the field of CFD. It is divided into three sections according to the purpose and approaches used in the development of the contributions. The first section describes the "high-performance computing" (HPC) tools and their impact on CFD modeling. The second section is dedicated to "CFD models for local and large-scale industrial phenomena." Two types of approaches are basically contained here: one concerns the adaptation from global to local scale, - e.g., the applications of CFD to study the climate changes and the adaptations to local scale. The second approach, very challenging, is the multiscale analysis. The third section is devoted to "CFD in numerical modeling approach for experimental cases." Its chapters emphasize on the numerical approach of the mathematical models associated to few experimental (industrial) cases. Here, the impact and the importance of the mathematical modeling in CFD are focused on. It is expected that the collection of these chapters will enrich the state of the art in the CFD domain and its applications in a lot of fields. This collection proves that CFD is a highly interdisciplinary research area, which lies at the interface of physics, engineering, applied mathematics, and computer science.