There are many disadvantages to being a balding geezer. In compensation, if you've managed to live through the second half of the twentieth century and been involved in computing, there's bearing personal witness to what happens when a technological transition goes into full-tilt exponential blow-off mode. I'm talking about Moore's Law (actually, more of an observation than a law, since it's predicated on certain physical principles and can't go on forever)—computing power available at constant cost doubling every 18 months or so. I've not only seen this happen, I've—er—profited from it; had the 80286-based IBM PC/AT and its competitors not appeared when they did, Autodesk would have been stillborn as too early to market or drowned out by competitors as we arrived too late.
When Moore's Law (or whatever) is directly connected to your career and your bank account, it's nice to have a little thermometer you can use to see how it's going as the years roll by. This repository contains two benchmarks I've used to evaluate computer performance ever since 1980. They focus on things which matter to me—floating point computation speed, evaluation of trigonometric functions, and matrix algebra. If you're interested in text searching or database retrieval speed, you should run screaming from these benchmarks. Hey, they work for me.
The original floating point benchmark, which is based upon an optical design ray tracing program I wrote in BASIC in December 1980, has been ported to many different programming languages, and may be used to evaluate the performance of these languages and different implementations of them.
Please see the following HTML documents for details and results.
All of this software is licensed under the Creative Commons Attribution-ShareAlike license. Please see LICENSE.md in this repository for details.