Energy-Languages VS RE2

Looking at the benchmark where C++ is worst compared to other languages, it's depending on the library used. I would guess if they used Google's re2 Regex library instead of Boost's, the result would be different.

https://github.com/google/re2

https://github.com/greensoftwarelab/Energy-Languages/blob/ma...

Trawling through the wayback machine, I did find that the older pages link to https://github.com/greensoftwarelab/Energy-Languages, which does seem to provide the contents of the specific programs used and the benchmarking software. Excellent.

> … not … primarily an issue with means vs medians

We're comparing averages, why would we bother so much about the cause of an outlier.

> you linked directly to the C++ code for spectral-norm

You had linked to the wrong C and C++ code for spectral-norm, I linked to the code that was actually used.

> The time ratio of the Benchmarks Game fastest C version to the slowest C++ version is over 16x.

Again, you seem to be looking at the wrong repo.

The authors of "Energy Efficiency across Programming Languages, SLE’17" provided this repo —

https://sites.google.com/view/energy-efficiency-languages

https://github.com/greensoftwarelab/Energy-Languages

https://github.com/greensoftwarelab/Energy-Languages/issues/...

The paper authors provided a repo for the source code they used: https://github.com/greensoftwarelab/Energy-Languages

The study made their own measurements. They did not re-use measurements made by the benchmarks game.

One of the JavaScript programs at least was concurrent, whereas the TypeScript equivalent was synchronous. No wonder there's a difference...

Haven't looked closely at the other problems, but it's apparent to me that the solutions are not even trying to be similar, so comparing their efficiency is near useless.

the problem in question was the k-nucleotide one, IIRC:

https://github.com/greensoftwarelab/Energy-Languages/blob/13...

I've been trying to replicate a study on energy usage (alright, it's that study on energy usage) and I've hit a bit of a snag while trying to compile the Rust components of the project. Instead of using a Cargo.toml and building with cargo, the authors have decided to use a Makefile and manually pass flags into rustc.

Here is an issue from the repo with the code they used: https://github.com/greensoftwarelab/Energy-Languages/issues/34

Looking at the benchmark where C++ is worst compared to other languages, it's depending on the library used. I would guess if they used Google's re2 Regex library instead of Boost's, the result would be different.

https://github.com/google/re2

https://github.com/greensoftwarelab/Energy-Languages/blob/ma...

That page says it just includes "some of the most common special characters", and following the link to the Examples page in turn includes a link to the full list.

Python uses backtracking, so this probably isn't O(n), especially with the ability to choose the dictionary.

But with there are non-backtracking matchers which would make this O(n). Here's re2 from https://github.com/google/re2 :

  >>> import re2

RE2 is a Google regular expression library

google's regex library: https://github.com/google/re2

I am currently working with Regex, specifically Re2, and was wondering if there is a real difference between the above expressions for repeated sub-regex.

I ported Google RE2, a regular expression library, to SPVM as Resource::Re2, and created SPVM::Regex, a wrapper for it.

I searched for I found that there is a Perl compatible regular expression called Google RE2. It is written in C++, and with Google RE2, I can use Perl-compatible regular expressions as a library.

Yes, but there is an interesting clarification here. RE2 has used the "caching" approach documented in the Ruby bug ticket linked for quite some time (since its birth?): https://github.com/google/re2/blob/954656f47fe8fb505d4818da1...

It is mentioned only briefly in Cox's article on regex matching in the wild. Look for the word "bitstate": https://swtch.com/~rsc/regexp/regexp3.html

I didn't know Perl had implemented this trick too.

The paper[1] cited in the Ruby bug ticket was published very recently. When I first read the Ruby bug ticket, I immediately wondered how they sidestepped the memory use problem. The paper's abstract seems to suggest there is some technique for doing so, as it rebuffs the idea of doing "full" memoization. Alas, I do not have access the paper. (Which is fucking ridiculous.)

[1]: https://ieeexplore.ieee.org/abstract/document/9519427