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oc2 | julia | |
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13 | 350 | |
602 | 44,510 | |
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0.0 | 10.0 | |
4 months ago | 5 days ago | |
Java | Julia | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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oc2
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What are your guys' creative ways to cover cable holes?
There's OpenComputers II for 1.18.2, but unfortunately it appears to have been "abandoned".
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Running actual Minecraft in Minecraft might actually be possible in a few years (kinda)
There is this mod called OpenComputers II, which is a spiritual successor of the original OpenComputers mod but for newer versions of Minecraft. OpenComputers II uses a library mod called Sedna to emulate a RISC-V CPU within Minecraft and run an actual Linux virtual machine inside the game. Well recently, Android has announced that they are adding support for the RISC-V architecture. Considering the fact that Android uses the Linux kernel (or at least a modified version of it), along with it being able to run Minecraft Bedrock natively (as we all know), running actual Minecraft in Minecraft might not be as far off as we think.
- Open Computers II for 1.16.5?
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What are your favourite mods that haven't been updated past 1.12.2?
Hey pal, Open computers II
- [No Identification] I want to change the font for a program I use but its using a png based font system. What is it called when this is how fonts are stored? Is there an easy way to convert a TTF to this format?
- Being 500x faster than python still means it's 10x slower than C
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Looking for a highly resource constrained target to run Rust on. Any ideas?
I've seen a few rust projects compiling for this RISC-V emulator inside Minecraft: https://github.com/fnuecke/oc2
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Mekanism 1.18.2 Released
Support for Open Computers 2 exposing everything that we expose to CC: Tweaked (minus the utility methods to convert between energy types)
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Do you guys actually use ComputerCraft in your projects?
The OC dev is developing OC2 for 1.16.5 and newer.
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ComputerCraft/Open Computers Centered Server?
Waiting for this to get pushed through. https://github.com/fnuecke/oc2/pull/58
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?
atsamd - Target atsamd microcontrollers using Rust
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
NIDAS - Networked Information Display & Automation Software
NetworkX - Network Analysis in Python
forge-c64
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.
PythonIsNotSlow - Simple program to benchmark C vs pure Python vs Numpy vs Cython.
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
Primes - Prime Number Projects in C#/C++/Python
Numba - NumPy aware dynamic Python compiler using LLVM
fonts-for-games
F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp