4 ms·
I love a good benchmark, thanks for putting this together! However, I have a bit of feedback. First, the graph is misleading, stacking times with languages tha
by keyle 3y ago
I love a good benchmark, thanks for putting this together! However, I have a bit of feedback.
First, the graph is misleading, stacking times with languages that have half the implementation, they appear faster, until you dig in. I'd suggest producing an alternate graph that shows only the implemented puzzles in every language, or make a unique graph for every language:puzzle.
Second, the examples are taken from rosetta code and are not necessarily what would be the best implementation, or even close to the best implementation, for benchmarking purposes.
Finally, those examples should be reproduced across various hardware platforms, I'm on arm64 Darwin myself, but you might find different results on Intel platforms due to the various compiler optimizations available based on the hardware.
More benchmarks would be interesting to see, such as actual real world operations, e.g. opening a file, reading it, parsing json, opening a socket server, etc.
- WhereIsTheTruth 3y agoThere is one for data processing here: https://github.com/jinyus/related_post_gen https://github.com/jinyus/related_post_gen
- cm2187 3y agoAlso it may or may not be relevant to not exclude the warm up time for JIT languages. If it is for a calculation you will do continuously, including the warm up time may bias the results materially (I know for .net it can be significant).
- attractivechaos 3y agoClarification: the examples are not taken from Rosetta code. Only the n-queens algorithm is inspired by (but still different from) an Rosetta code implementation; otherwise this benchmark has nothing to do with Rosetta code.