julia
awesome-lisp-companies
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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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Best Programming languages for Data Analysis📊
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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
The one you need is this which is already merged but was after the 1.10 feature freeze so it has to wait till 1.11, though you can test it with nightly builds which is available on julialang site: https://github.com/JuliaLang/julia/pull/51435
Unfortunately, the core devs are not too chatty about standalone binaries, because of how Julia's internals are set there are going to be a lot of unforeseen challenges, so they are not trying to promise how things will be rather let's wait and see how things will turnout. Since packagecompiler.jl already has C ABI and one goal discussed about binaries being easily callable from other languages and vice versa, I would bet that it will have shared libraries.
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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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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...
awesome-lisp-companies
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Why Is Common Lisp Not the Most Popular Programming Language?
Everyone, if you don't have a clue on how's Common Lisp going these days, I suggest:
https://lisp-journey.gitlab.io/blog/these-years-in-common-li... (https://www.reddit.com/r/lisp/comments/107oejk/these_years_i...)
A curated list of libraries: https://github.com/CodyReichert/awesome-cl
Some companies, the ones we hear about: https://github.com/azzamsa/awesome-lisp-companies/
and oh, some more editors besides Emacs or Vim: https://lispcookbook.github.io/cl-cookbook/editor-support.ht... (Atom/Pulsar support is good, VSCode support less so, Jetbrains one getting good, Lem is a modern Emacsy built in CL, Jupyter notebooks, cl-repl for a terminal REPL, etc)
yet no other language gives so many tools to the developer… quantum companies would disagree. https://github.com/azzamsa/awesome-lisp-companies/
(BTW: CL isn't Smalltalk which isn't uniquely that anymore, we do use source files and we can compile single-file binaries. My web app weights 35MB, starts up in 0.4s (or 0.01s without core compression))
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We need to talk about parentheses
Examples (for Common Lisp, so not citing Emacs): reddit v1, Google's ITA Software that powers airfare search engines (Kayak, Orbitz…), Postgres' pgloader (http://pgloader.io/), which was re-written from Python to Common Lisp, Opus Modus for music composition, the Maxima CAS, PTC 3D designer CAD software (used by big brands worldwide), Grammarly, Mirai, the 3D editor that designed Gollum's face, the ScoreCloud app that lets you whistle or play an instrument and get the music score,
but also the ACL2 theorem prover, used in the industry since the 90s, NASA's PVS provers and SPIKE scheduler used for Hubble and JWT, many companies in Quantum Computing, companies like SISCOG, who plans the transportation systems of european metropolis' underground since the 80s, Ravenpack who's into big-data analysis for financial services (they might be hiring), Keepit (https://www.keepit.com/), Pocket Change (Japan, https://www.pocket-change.jp/en/), the new Feetr in trading (https://feetr.io/, you can search HN), Airbus, Alstom, Planisware (https://planisware.com),
or also the open-source screenshotbot (https://screenshotbot.io), the Kandria game (https://kandria.com/),
and the companies in https://github.com/azzamsa/awesome-lisp-companies and on LispWorks and Allegro's Success Stories.
https://github.com/tamurashingo/reddit1.0/
https://www.ptc.com/en/products/cad/3d-design
https://apps.apple.com/us/app/scorecloud-express/id566535238
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A Tour of Lisps
Haven't had a lisp job, so maybe I shouldn't comment, but... I did use CL and Clojure on the job for a few things at my last two places. It's easier to find Clojure companies (and them to find you) than Common Lisp ones. You might want to peruse https://github.com/azzamsa/awesome-lisp-companies from time to time and see if any have openings. There's other resources linked too and of course there's the reddit and discord community (such as there is) hubs. You can also see if there are any meetups in your area, that's how I almost ended up at a Clojure startup some years back.
I should have taken strategy notes after talking to a guy at my last job who got management buy-in to rewrite a lot of Java code (for android) to Kotlin and have all new code for android be in Kotlin (before that was considered the sensible default). I think that's in general a better approach for a lot of would-be paid lispers: don't wait for or look for the lisp job, make the lisp job. Whether that's doing work where the customer doesn't care what language the thing is made in, or introducing it (some have even snuck it in -- the original clojure.jar got a lot of early success that way) to an existing work place. What I somewhat remember from my conversation was that if you can make a good technical case and have at least one other person supporting you (ideally your entire dev team as was his case), it's a lot easier to sell. No one raised bogus concerns about increasing the hiring difficulty or effort learning the new system. (I say bogus because engineers are learning all the time, and huge swathes of the industry have already had to do things like migrate from ObjC to Swift, or the various versions of JavaScript and later TypeScript + all the framework churn, switching IDEs; learning and change are quite common and a non-issue.) From other Lisp company reports, getting a new hire up to speed to be productive with the team using Common Lisp is a matter of a week or two, a small portion of the overall onboarding time a lot of new jobs have. Mastery takes longer, of course, but that's different.
If I had stayed longer at my last job I would have continued to flesh out a better demo for interactive selenium webdriver tests for our main Java application after injecting ABCL into it, it seemed like the easiest vector to get more interest from my team and other teams. It kind of sucks when you're debugging a broken test and finally hit an exception but now you have to start over again (especially if you stepped too far in the debugger), especially with heavy webdriver tests that can take a long time. The Lisp debugging experience is so much better... And when writing the test from scratch, it's very interactive, you type code and execute it and verify the browser did what you intended. When you're done you run it again from scratch to verify.
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All of Mark Watson's Lisp Books
> but there doesn't seem to be one that really stands out as pragmatic, industrial
disagree ;) This industrial language is Common Lisp.
Some industrial uses:
- http://www.lispworks.com/success-stories/index.html
- https://github.com/azzamsa/awesome-lisp-companies/
- https://lisp-lang.org/success/
Example companies: Intel's programmable chips, the ACL2 theorem prover (https://royalsocietypublishing.org/doi/10.1098/rsta.2015.039...), urban transportation planning systems (SISCOG), Quantum Computing (HRL Labs, Rigetti…), big data financial analysis (Ravenpack, they might be hiring), Google, Boeing, the NASA, etc.
ps: Python competing? strong disagree^^
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Steel Bank Common Lisp
Hey there, newer member of the first group here. Please see https://github.com/azzamsa/awesome-lisp-companies/ to update your meta-comment. So, is CL used in the industry today, yes or no?
Personal note: I much prefer to maintain a long-living software in Common Lisp rather than in Python, thank you very much. May all the new programmers learn easily and all the teams have lots of ~~burden~~ work with Python, good for them.
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Racket: The Lisp for the Modern Day
Common Lisp has many industrial uses though.
(https://github.com/azzamsa/awesome-lisp-companies/
https://lisp-lang.org/success/
http://www.lispworks.com/success-stories/index.html
such as
https://www.cs.utexas.edu/users/moore/acl2/ (theorem prover used by big corp©)
https://allegrograph.com/press_room/barefoot-networks-uses-f... (Intel programmable chip)
quantum compilers https://news.ycombinator.com/item?id=32741928
etc, etc, etc)
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Why Lisp Syntax Works
A few more that we know of, using CL today: https://github.com/azzamsa/awesome-lisp-companies/
Others: https://lisp-lang.org/success/
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How to Understand and Use Common Lisp
yes
https://github.com/azzamsa/awesome-lisp-companies
industrial theorem prover, design of Intel chips, quantum compilers...
and little me, being more productive and having more fun than with python to deploy boring tools (read a DB, format the data, send to FTP servers, show a web interface...).
What are some alternatives?
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
NetworkX - Network Analysis in Python
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.
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
Numba - NumPy aware dynamic Python compiler using LLVM
F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
LUA - A programming language based upon the lua programming language
PackageCompiler.jl - Compile your Julia Package
femtolisp - a lightweight, robust, scheme-like lisp implementation
JLD2.jl - HDF5-compatible file format in pure Julia