Towards a Statistical Methodology to Evaluate Program Speedups and their Optimisation Techniques

The community of program optimisation and analysis, code performance evaluation, parallelisation and optimising compilation has published since many decades hundreds of research and engineering articles in major conferences and journals. These articles study efficient algorithms, strategies and techniques to accelerate programs execution times, or optimise other performance metrics (MIPS, code size, energy/power, MFLOPS, etc.). Many speedups are published, but nobody is able to reproduce them exactly. The non-reproducibility of our research results is a dark point of the art, and we cannot be qualified as {\it computer scientists} if we do not provide rigorous experimental methodology. This article provides a first effort towards a correct statistical protocol for analysing and measuring speedups. As we will see, some common mistakes are done by the community inside published articles, explaining part of the non-reproducibility of the results. Our current article is not sufficient by its own to deliver a complete experimental methodology, further efforts must be done by the community to decide about a common protocol for our future experiences. Anyway, our community should take care about the aspect of reproducibility of the results in the future.