Efficient Parallel Algorithm For Direct Numerical Simulation of Turbulent Flows

A distributed algorithm for a high-order-accurate finite-difference approach to the direct numerical simulation (DNS) of transition and turbulence in compressible flows is described. This work has two major objectives. The first objective is to demonstrate that parallel and distributed-memory machines can be successfully and efficiently used to solve computationally intensive and input/output intensive algorithms of the DNS class. The second objective is to show that the computational complexity involved in solving the tridiagonal systems inherent in the DNS algorithm can be reduced by algorithm innovations that obviate the need to use a parallelized tridiagonal solver

Parallel software tools at Langley Research Center

This document gives a brief overview of parallel software tools available on the Intel iPSC/860 parallel computer at Langley Research Center. It is intended to provide a source of information that is somewhat more concise than vendor-supplied material on the purpose and use of various tools. Each of the chapters on tools is organized in a similar manner covering an overview of the functionality, access information, how to effectively use the tool, observations about the tool and how it compares to similar software, known problems or shortfalls with the software, and reference documentation. It is primarily intended for users of the iPSC/860 at Langley Research Center and is appropriate for both the experienced and novice user

Parallel Grid Generation Algorithm for Distributed Memory Computers

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A Root Finding Algorithm for Parallel Architecture Machines

In this thesis a parallel algorithm for determining the zeros of any given analytic function is described. Parallelism is achieved by modifying the traditional bisection algorithm for architecture machines. Given any user supplied function f(X), continuous on the interval Ao ≤ x ≤ B0, and the tolerance of accuracy an algorithm of determining up to ten roots, with error of approximation less than or equal to tolerance, on parallel systems like Distributed Array Processor (OAP) and N-cube is considered. A variation of the bisection method has been adapted for this purpose. At each level of iteration a single new approximation to the root in question is found. At any stage results achieved should be considerably more accurate than the results achieved by the use of any iterative method on a serial machine because of localization of the approximation. This has been made possible by the use of much smaller intervals than the interval used for bisection algorithms, in determining the root. A performance comparison of speed of the approximation process using an algorithm on the DAP and and the N-cube is presented

Performance Comparison of a Set of Periodic and Non�Periodic Tridiagonal Solvers on SP2 and Paragon Parallel Computers

Various tridiagonal solvers have been proposed in recent years for di�erent par� allel platforms. In this paper � the performance of three tridiagonal solvers � namely� the parallel partition LU algorithm � the parallel diagonal dominant algorithm � and the reduced diagonal dominant algorithm � is studied. These algorithms are designed for distributed�memory machines and are tested on an Intel Paragon and an IBM SP2 machines. Measured results are reported in terms of execution time and speedup. An� alytical study are conducted for di�erent communication topologies and for di�erent tridiagonal systems. The measured results match the analytical results closely. In ad� dition to address implementation issues � performance considerations such as problem sizes and models of speedup are also discussed