Parametric micro-level performance models for parallel computing and parallel implementation of hydrostatic MM5

This dissertation presents Parametric micro-level performance models and Parallel implementation of the hydrostatic version of MM5;Parametric micro-level (PM) performance models are introduced to address the important issue of how to realistically model parallel performance. These models can be used to predict execution times and identify performance bottlenecks. The accurate prediction and analysis of execution times is achieved by incorporating precise details of interprocessor communication, memory operations, auxiliary instructions, and effects of communication and computation schedules. The parameters provide the flexibility to study various algorithmic and architectural issues. The development and verification process, parameters and the scope of applicability of these models are discussed. A coherent view of performance is obtained from the execution profiles generated by PM models. The models are targeted at a large class numerical algorithms commonly implemented on both SIMD and MIMD machines. Specific models are presented for matrix multiplication, LU decomposition, and FFT on a 2-D processor array with distributed memory. A case study includes comparison of parallel machines and parallel algorithms. In a comparison of parallel machines, PM models are used to analyze execution times so as to relate the performance to architectural attributes of a machine. In a comparison of parallel algorithms, PM models are used to study performance of two LU decomposition algorithms: non-blocked and blocked. Two algorithms are compared to identify the tradeoffs between them. This analysis is useful to determine an optimum block size for the blocked algorithm. The case study is done on MasPar MP-1 and MP-2 machines;The dissertation also describes the parallel implementation of the hydrostatic version of MM5 (the fifth generation of Mesoscale Model), which has been widely used for climate studies. The model was parallelized in machine-independent manner using the Runtime System Library (RSL), a runtime library for handling message-passing and index transformation. The dissertation discusses validation of the parallel implementation of MM5 using field data and presents performance results. The parallel model was tested on the IBM SP1, a distributed memory parallel computer

NASA high performance computing and communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 100-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientist's abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects as well as summaries of individual research and development programs within each project

Semiannual final report, 1 October 1991 - 31 March 1992

A summary of research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period 1 Oct. 1991 through 31 Mar. 1992 is presented

Linear mixing model applied to coarse resolution satellite data

A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies

An N-body Tree Algorithm for the Cray T3D

We describe in this paper an algorithm for solving the gravitational N-body problem using tree data structures on the Cray T3D parallel supercomputer. This implementation is an adaptation of previous work where this problem was solved using an SIMD, fine-grained parallel computer. We show here that this approach lends itself, with small modifications, to more coarse-grained parallelism as well. We also show that the performance of the algorithm on the Cray T3D parallel architecture scales adequately with the number of processors (up to 256). Specific levels to be reached using the Cray T3D parallel architecture. A peak performance level of 9.6 Gflop/s is reached on 256 processors for the time critical gravity computation

Probabilistic structural mechanics research for parallel processing computers

Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical

High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems

This is the final technical report for the project entitled: "High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems", funded at NPAC by the DAO at NASA/GSFC. First, the motivation for the project is given in the introductory section, followed by the executive summary of major accomplishments and the list of project-related publications. Detailed analysis and description of research results is given in subsequent chapters and in the Appendix

ハードウェアリソースの高稼働率化に基づく細粒度多値リコンフィギャラブルVLSIアーキテクチャ

Tohoku University亀山充隆課