A bibliography on parallel and vector numerical algorithms

This is a bibliography of numerical methods. It also includes a number of other references on machine architecture, programming language, and other topics of interest to scientific computing. Certain conference proceedings and anthologies which have been published in book form are listed also

Future Computer Requirements for Computational Aerodynamics

Recent advances in computational aerodynamics are discussed as well as motivations for and potential benefits of a National Aerodynamic Simulation Facility having the capability to solve fluid dynamic equations at speeds two to three orders of magnitude faster than presently possible with general computers. Two contracted efforts to define processor architectures for such a facility are summarized

Sensitivity of Mountain Wave Drag Estimates on Separation Methods and Proposed Improvements

Internal gravity waves (GWs) are ubiquitous in the atmosphere, making significant contributions to the mesoscale motions. Since the majority of their spectrum is unresolved in global circulation models, their effects need to be parameterized. In recent decades GWs have been increasingly studied in high-resolution simulations, which, unlike direct observations, allow us to explore full spatio-temporal variations of the resolved wave field. In our study we analyze and refine a traditional method for GW analysis in a high-resolution simulation on a regional domain around the Drake Passage. We show that GW momentum drag estimates based on the Gaussian high-pass filter method applied to separate GW perturbations from the background are sensitive to the choice of a cutoff parameter. The impact of the cutoff parameter is higher for horizontal fluxes of horizontal momentum, which indicates higher sensitivity for horizontally propagating waves. Two modified methods, which choose the parameter value from spectral information, are proposed. The dynamically determined cutoff is mostly higher than the traditional cutoff values around 500 km, leading to larger GW fluxes and drag, and varies with time and altitude. The differences between the traditional and the modified methods are especially pronounced during events with significant drag contributions from horizontal momentum fluxes

Solution of partial differential equations on vector and parallel computers

The present status of numerical methods for partial differential equations on vector and parallel computers was reviewed. The relevant aspects of these computers are discussed and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic equations as well as explicit and implicit methods for initial boundary value problems. The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms. Application areas utilizing these computers are briefly discussed

NASA scientific and technical publications: A catalog of special publications, reference publications, conference publications, and technical papers, 1989

This catalog lists 190 citations of all NASA Special Publications, NASA Reference Publications, NASA Conference Publications, and NASA Technical Papers that were entered into the NASA scientific and technical information database during accession year 1989. The entries are grouped by subject category. Indexes of subject terms, personal authors, and NASA report numbers are provided

A parallel methodology using radial basis functions versus machine learning approaches applied to environmental modelling

Parallel nonlinear models using radial kernels on local mesh support have been designed and implemented for application to real-world problems. Although this recently developed approach reduces the memory requirements compared with other methodologies suggested over the last few years, its computational cost makes parallelisation necessary, especially for big datasets with many instances or attributes. In this work, several strategies for the parallelisation of this methodology are proposed and compared. The MPI communication protocol and the OpenMP application programming interface are used to implement the algorithm. The performance of this methodology is compared with various machine learning methods, with particular consideration of techniques using radial basis functions (RBF). Different methods are applied to model the daily maximum air temperature from real meteorological data collected from the Agroclimatic Station Network of the Phytosanitary Alert and Information Network of Andalusia, an autonomous community of southern Spain. The obtained goodness-of-fit measures illustrate the effectiveness of this nonlinear methodology, and its training process is shown to be simpler than those of other powerful machine learning methods.This research was supported by the Spanish Ministry of Science, Innovation and Universities Grant RTI2018-098156-B-C54, co-financed by the European Commission (FEDER funds), and by the University of Alicante