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

Turbomachinery CFD on parallel computers

The role of multistage turbomachinery simulation in the development of propulsion system models is discussed. Particularly, the need for simulations with higher fidelity and faster turnaround time is highlighted. It is shown how such fast simulations can be used in engineering-oriented environments. The use of parallel processing to achieve the required turnaround times is discussed. Current work by several researchers in this area is summarized. Parallel turbomachinery CFD research at the NASA Lewis Research Center is then highlighted. These efforts are focused on implementing the average-passage turbomachinery model on MIMD, distributed memory parallel computers. Performance results are given for inviscid, single blade row and viscous, multistage applications on several parallel computers, including networked workstations

Fast data parallel polygon rendering

Journal ArticleThis paper describes a data parallel method for polygon rendering on a massively parallel machine. This method, based on a simple shading model, is targeted for applications which require very fast rendering for extremely large sets of polygons. Such sets are found in many scienti c visualization applications. The renderer can handle arbitrarily complex polygons which need not be meshed. Issues involving load balancing are addressed and a data parallel load balancing algorithm is presented. The rendering and load balancing algorithms are implemented on both the CM-200 and the CM-5. Experimental results are presented. This rendering toolkit enables a scientist to display 3D shaded polygons directly from a parallel machine avoiding the transmission of huge amounts of data to a post-processing rendering system

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