The Nas Parallel Benchmarks

A new set of benchmarks has been developed for the performance evaluation of highly parallel supercom puters. These consist of five "parallel kernel" bench marks and three "simulated application" benchmarks. Together they mimic the computation and data move ment characteristics of large-scale computational fluid dynamics applications. The principal distinguishing feature of these benchmarks is their "pencil and paper" specification—all details of these benchmarks are specified only algorithmically. In this way many of the difficulties associated with conventional bench- marking approaches on highly parallel systems are avoided.

[1]  H. Lomax.  Stable implicit and explicit numerical methods for integrating quasi-linear differential equations with parasitic-stiff and parasitic-saddle eigenvalues , 1968 .

[2]  Marshall C. Pease,et al.  An Adaptation of the Fast Fourier Transform for Parallel Processing , 1968, JACM.

[3]  O. Axelsson.  A generalized SSOR method , 1972 .

[4]  R. F. Warming,et al.  On the construction and application of implicit factored schemes for conservation laws , 1978 .

[5]  P. Cassen.  Solid convection in the terrestrial planets; Workshop, NASA Ames Research Center, Moffett Field, Calif., December 12, 13, 1977, Review Papers and Contributions , 1979 .

[6]  T. Pulliam,et al.  A diagonal form of an implicit approximate-factorization algorithm , 1981 .

[7]  T. Coakley.  Numerical method for gas dynamics combining characteristic and conservation concepts , 1981 .

[8]  J. Steger,et al.  Flux vector splitting of the inviscid gasdynamic equations with application to finite-difference methods , 1981 .

[9]  A. Jameson,et al.  Numerical solution of the Euler equations by finite volume methods using Runge Kutta time stepping schemes , 1981 .

[10]  E. Krause.  Eighth international conference on numerical methods in fluid dynamics , 1982 .

[11]  Paul N. Swarztrauber,et al.  FFT algorithms for vector computers , 1984, Parallel Comput..

[12]  T. Chan,et al.  Nonlinearly Preconditioned Krylov Subspace Methods for Discrete Newton Algorithms , 1984 .

[13]  David H. Bailey,et al.  The NAS kernel benchmark program , 1985 .

[14]  F. H. Mcmahon,et al.  The Livermore Fortran Kernels: A Computer Test of the Numerical Performance Range , 1986 .

[15]  Ramesh C. Agarwal,et al.  Fourier Transform and Convolution Subroutines for the IBM 3090 Vector Facility , 1986, IBM J. Res. Dev..

[16]  T. Pulliam.  Efficient solution methods for the Navier-Stokes equations , 1986 .

[17]  Jack J. Dongarra,et al.  Performance of various computers using standard linear equations software in a Fortran environment , 1987, SGNM.

[18]  I. Duff,et al.  Direct Methods for Sparse Matrices , 1987 .

[19]  David H. Bailey.  A High-Performance FFT Algorithm for Vector Supercomputers , 1987, PPSC.

[20]  Jack J. Dongarra,et al.  The LINPACK Benchmark: An Explanation , 1988, ICS.

[21]  P. Olsson,et al.  Boundary modifications of the dissipation operators for the three-dimensional Euler equations , 1989 .

[22]  Geoffrey C. Fox,et al.  The Perfect Club Benchmarks: Effective Performance Evaluation of Supercomputers , 1989, Int. J. High Perform. Comput. Appl..

[23]  D. Kwak,et al.  LU-SGS implicit algorithm for three-dimensional incompressible Navier-Stokes equations with source term , 1989 .

[24]  George Cybenko,et al.  Supercomputer performance evaluation and the Perfect Benchmarks , 1990, ICS '90.

[25]  Supercomputer performance evaluation and the Perfect Benchmarks , 1990, ICS.

[26]  David H. Bailey,et al.  NAS parallel benchmark results , 1992, Proceedings Supercomputing '92.

[27]  Performance of Various Computers Using Standard Linear Equations Software , 1993, Progress In Electromagnetics Research.