Energy-Languages
julia
Energy-Languages | julia | |
---|---|---|
37 | 350 | |
668 | 44,534 | |
0.4% | 0.4% | |
0.0 | 10.0 | |
7 months ago | about 17 hours ago | |
C | Julia | |
MIT License | MIT License |
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Energy-Languages
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C Is the Greenest Programming Language
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...
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General Availability of the AWS SDK for Rust
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.
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Java consumes 38x less energy than Python
> … 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
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Racket: The Lisp for the Modern Day
https://github.com/greensoftwarelab/Energy-Languages/issues/...
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Is your language eco friendly?
The paper authors provided a repo for the source code they used: https://github.com/greensoftwarelab/Energy-Languages
- Reasons you prefer Golang over Java?
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I don't hate it. But I can't deny it.
The study made their own measurements. They did not re-use measurements made by the benchmarks game.
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Energy Efficiency across Programming Languages [pdf]
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...
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How to install libraries into a common directory so that they can be targeted by an -L flag to rustc?
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.
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Greenest programming languages: a reason to support JavaScript over TypeScript
Here is an issue from the repo with the code they used: https://github.com/greensoftwarelab/Energy-Languages/issues/34
julia
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Top Paying Programming Technologies 2024
34. Julia - $74,963
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Optimize sgemm on RISC-V platform
I don't believe there is any official documentation on this, but https://github.com/JuliaLang/julia/pull/49430 for example added prefetching to the marking phase of a GC which saw speedups on x86, but not on M1.
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Dart 3.3
3. dispatch on all the arguments
the first solution is clean, but people really like dispatch.
the second makes calling functions in the function call syntax weird, because the first argument is privileged semantically but not syntactically.
the third makes calling functions in the method call syntax weird because the first argument is privileged syntactically but not semantically.
the closest things to this i can think of off the top of my head in remotely popular programming languages are: nim, lisp dialects, and julia.
nim navigates the dispatch conundrum by providing different ways to define free functions for different dispatch-ness. the tutorial gives a good overview: https://nim-lang.org/docs/tut2.html
lisps of course lack UFCS.
see here for a discussion on the lack of UFCS in julia: https://github.com/JuliaLang/julia/issues/31779
so to sum up the answer to the original question: because it's only obvious how to make it nice and tidy like you're wanting if you sacrifice function dispatch, which is ubiquitous for good reason!
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Julia 1.10 Highlights
https://github.com/JuliaLang/julia/blob/release-1.10/NEWS.md
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Best Programming languages for Data Analysis📊
Visit official site: https://julialang.org/
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Potential of the Julia programming language for high energy physics computing
No. It runs natively on ARM.
julia> versioninfo() Julia Version 1.9.3 Commit bed2cd540a1 (2023-08-24 14:43 UTC) Build Info: Official https://julialang.org/ release
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Rust std:fs slower than Python
https://github.com/JuliaLang/julia/issues/51086#issuecomment...
So while this "fixes" the issue, it'll introduce a confusing time delay between you freeing the memory and you observing that in `htop`.
But according to https://jemalloc.net/jemalloc.3.html you can set `opt.muzzy_decay_ms = 0` to remove the delay.
Still, the musl author has some reservations against making `jemalloc` the default:
https://www.openwall.com/lists/musl/2018/04/23/2
> It's got serious bloat problems, problems with undermining ASLR, and is optimized pretty much only for being as fast as possible without caring how much memory you use.
With the above-mentioned tunables, this should be mitigated to some extent, but the general "theme" (focusing on e.g. performance vs memory usage) will likely still mean "it's a tradeoff" or "it's no tradeoff, but only if you set tunables to what you need".
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Eleven strategies for making reproducible research the norm
I have asked about Julia's reproducibility story on the Guix mailing list in the past, and at the time Simon Tournier didn't think it was promising. I seem to recall Julia itself didnt have a reproducible build. All I know now is that github issue is still not closed.
https://github.com/JuliaLang/julia/issues/34753
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Julia as a unifying end-to-end workflow language on the Frontier exascale system
I don't really know what kind of rebuttal you're looking for, but I will link my HN comments from when this was first posted for some thoughts: https://news.ycombinator.com/item?id=31396861#31398796. As I said, in the linked post, I'm quite skeptical of the business of trying to assess relative buginess of programming in different systems, because that has strong dependencies on what you consider core vs packages and what exactly you're trying to do.
However, bugs in general suck and we've been thinking a fair bit about what additional tooling the language could provide to help people avoid the classes of bugs that Yuri encountered in the post.
The biggest class of problems in the blog post, is that it's pretty clear that `@inbounds` (and I will extend this to `@assume_effects`, even though that wasn't around when Yuri wrote his post) is problematic, because it's too hard to write. My proposal for what to do instead is at https://github.com/JuliaLang/julia/pull/50641.
Another common theme is that while Julia is great at composition, it's not clear what's expected to work and what isn't, because the interfaces are informal and not checked. This is a hard design problem, because it's quite close to the reasons why Julia works well. My current thoughts on that are here: https://github.com/Keno/InterfaceSpecs.jl but there's other proposals also.
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Getaddrinfo() on glibc calls getenv(), oh boy
Doesn't musl have the same issue? https://github.com/JuliaLang/julia/issues/34726#issuecomment...
I also wonder about OSX's libc. Newer versions seem to have some sort of locking https://github.com/apple-open-source-mirror/Libc/blob/master...
but older versions (from 10.9) don't have any lockign: https://github.com/apple-oss-distributions/Libc/blob/Libc-99...
What are some alternatives?
SGDK - SGDK - A free and open development kit for the Sega Mega Drive
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
gdnative - Rust bindings for Godot 3
NetworkX - Network Analysis in Python
racket-binfmt - A binary format parser generator DSL with support for limited context-sensitivity.
Lua - Lua is a powerful, efficient, lightweight, embeddable scripting language. It supports procedural programming, object-oriented programming, functional programming, data-driven programming, and data description.
Programming - This repo contains my Projects and practice code of various languages which I have learned during my Graduation in Computer engineering.
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
OTA_update_STM32_using_ESP32 - Program STM32Fxx MCUs Over-the-Air using ESP32
Numba - NumPy aware dynamic Python compiler using LLVM
rust - Rust for the xtensa architecture. Built in targets for the ESP32 and ESP8266
F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp