Summary of Rich McLaughlin benchmarks

Quick overview

This document summarizes the benchmarks from Rich McLaughlin's research group in computational fluid dynamics at the University of Utah Mathematics Department.

The benchmark results are available in two series of tables.

Each table contains rows of results ordered in decreasing performance. Each row contains the

Important disclaimer

Please remember that there is no answer to the commonly-asked question: ``What is the fastest machine?''.

Within the collection of benchmarks of which these are members, it is often possible to pick a single benchmark which rates a particular machine the fastest, and yet, on other benchmarks, the same machine may perform poorly with respect to competing models.

Particularly on modern RISC architectures, performance can be extremely sensitive to the quality of compiler optimizations; in at least one case, a speedup of a factor of fifty was seen over a range of compiler options on the same system.

The benchmarking of these programs has investigated a substantial number of compilation options and optimization levels, but it is possible that new releases of compilers, or alternative compilers, might improve the results significantly. We make reasonable efforts to keep our compiler and operating systems up-to-date with vendor software releases, but particularly with older machine models, or machines obtained on a short-term loan for evaluation purposes, it is frequently impossible to rerun the benchmarks after such new releases.

It is imperative with computer benchmarking to examine a range of benchmark programs, where those programs are chosen to represent the kinds of numerical computation that are important to you, before coming to a conclusion about which machine is best for your jobs.

Many other factors besides benchmark performance should affect computer purchasing decisions, including at least these:

Brief benchmark descriptions

All of the benchmark programs described in this document are written in highly-portable Fortran 77, and all represent real research programs using real data; they are not loop kernels or toy implementations. Program code sizes are given below.

eulshdp

[200 lines of Fortran code]

This is the double-precision version of a random-walk simulation.

eulshdp

[200 lines of Fortran code]

This is the double-precision version of a random-walk simulation.