SGDK VS Energy-Languages

Examples: - Someone I know created machine-optimized library in c and asm to accelerate compression, erasure coding, and encryption on Intel Xeon CPUs (https://github.com/intel/isa-l) which runs those ops WAY faster than the standard linux libraries. - My friend is making a retro SEGA genesis game using a C and asm dev kit (https://github.com/Stephane-D/SGDK)

Genesis fortunately has a really mature homebrew SDK that uses C https://github.com/Stephane-D/SGDK . People have made plenty of homebrew titles over the years for these consoles and distributed them freely, sold the roms, or programmed new cartridges.

If you are specifically looking into the Genesis you should look into SGDK, the sega development toolkit https://github.com/Stephane-D/SGDK.

There's a lot of retro dev happening now across the board. SGDK has led to a big interest in making Genesis/Megadrive games. Jo Engine is increasing interest in the Saturn, etc. I'm also attempting to help contribute by writing a book on Neo Geo development (it has a long ways to go)

https://github.com/Stephane-D/SGDK

https://www.jo-engine.org/

a Saturn homebrew showcase - https://www.youtube.com/watch?v=NqKKExcTaKo

https://neobook.mattgreer.dev

Could this be useful from the megadrive SDK? https://github.com/Stephane-D/SGDK/wiki/Tuto-Maths

I had the same idea for the same reason. I have not started anything yet but I was going to try developing a Sega Genesis/Megadrive game using an SDK like https://github.com/Stephane-D/sgdk

The MD version was developed with SGDK .

> … 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

You seem to be looking at the wrong source code. The authors provided this repo —

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

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

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

The difference between JS and TS seems to be different implementations of a single benchmark.

The huge increase is the result of a different implementation for fannkuch-redux, causing a 16x performance difference that accounts for the skew.

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

They have separate "compile" and "run" Make targets for all of their tests, which they documented on their Github, and you can see in the Makefiles: https://github.com/greensoftwarelab/Energy-Languages

You misunderstand - the discrepancy is caused by an implementation bug in their experiment, the study did not count compilation time.

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...

The code from this study is here: https://github.com/greensoftwarelab/Energy-Languages

From looking at the code snippets, the big issue with this study becomes clear - it doesn't reflect how languages like Python are used in practice.

In practice, the "hot loops" of Python are in c/c++/fortran/cython/numba/... i.e. Python code usually makes use of a vast ecosystem of optimized science/maths/data science libraries. Whereas the study code is mainly using pure Python.