How not to lie with statistics: the correct way to summarize benchmark results
Communications of the ACM - The MIT Press scientific computation series
Computer benchmarking: paths and pitfalls
IEEE Spectrum
Engineering Design of the Convex C2
Computer
Characterizing computer performance with a single number
Communications of the ACM
An introduction to operating systems (2nd ed.)
An introduction to operating systems (2nd ed.)
Squeezing the most out of an algorithm in CRAY FORTRAN
ACM Transactions on Mathematical Software (TOMS)
Dhrystone: a synthetic systems programming benchmark
Communications of the ACM
How to measure useful, sustained performance
State of the Practice Reports
| Hi-index | 0.00 |
The choice of a computer system depends on many factors of which one of the most important criterion is the performance. In scientific/engineering environments where high-speed (mini)supercomputers are widely used, performance evaluation process is very complex due to the multidimensional nature of a computer's performance. Many of these computers are able to do scalar, vector and parallel processing.In this report different performance evaluation and analysis methods for high-speed computers have been developed. Attention has been paid to the compilers, program development, scalar, vector and parallel floating point computation and I/O. A method how to calculate single performance numbers has been presented and with this method the overall performances of computers can be estimated. A throughput test has been developed to measure the multiprogramming support of the operating system and hardware as well as the overheads in context switching, paging and swapping.These methods have been used to evaluate in practice the performances of some recently announced high-speed computers: Alliant FX/80, Ardent Titan, Convex C2, ETA-10P, FPS Model 500, and Stellar GS1000 and GS2000. Most of the results have been compared to those of a conventional scalar computer, VAX 8700.