Performance is not a central focus of this project, but it is necessary to decide on some metrics to determine if the performance is acceptable or not acceptable. Otherwise it is unclear how to evaluate proposed changes that affect performance. Additionally, it helps to guide our development priorities toward or away from performance depending on how close we are to our performance cutoff.
I propose that we choose
- some common algorithms to measure performance
- some existing language(s) to compare with SLVM
- some threshold like '10x'
At which point we can easily decide that SLVM performance is acceptable IFF its performance on those chosen algorithms is within '10x' of the chosen language(s)
https://github.com/attractivechaos/plb2 has some helpful discussion on the topic of comparing performance across languages. We might choose to use some of the algorithms from this project, which would make some language comparisons quite easy.
Performance is not a central focus of this project, but it is necessary to decide on some metrics to determine if the performance is acceptable or not acceptable. Otherwise it is unclear how to evaluate proposed changes that affect performance. Additionally, it helps to guide our development priorities toward or away from performance depending on how close we are to our performance cutoff.
I propose that we choose
At which point we can easily decide that SLVM performance is acceptable IFF its performance on those chosen algorithms is within '10x' of the chosen language(s)
https://github.com/attractivechaos/plb2 has some helpful discussion on the topic of comparing performance across languages. We might choose to use some of the algorithms from this project, which would make some language comparisons quite easy.