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How an MIT research project became the Julia programming language

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Re: How an MIT research project became the Julia programming language

#111

Post by harshreality »

bee_rider wrote: post #48
drhagen wrote: post #37

When I was a grad student at MIT, my desk was across the hall from the Julia people. We even shared a lunch table. Julia is most famous for its optimizing compiler, but many people may not notice the careful work that went into designing the language itself. Matlab this was not! I remember one long conversation where one of them was teaching me about the different types of normalization of unicode. They had to pick o…

I don’t know if experience has just damaged my brain or what, but I really like matlab’s syntax for what it is. Nice for writing 100 line experiments or using in the REPL. Sort of like the Python of linear algebra, haha. It also has a nice feature where you start getting headaches to let you know you’ve tried to extend it past its comfort zone. Julia seems to sit in this area between Matlab and Fortran where I can’t…

Julia might just be the closest thing at the moment to Matlab without being a Matlab clone. I think you're overestimating the learning curve. It has a REPL, with tab completion and ? for high-quality help (without resorting to a browser or llm).

Re: How an MIT research project became the Julia programming language

#112

Post by fhn »

cmontella wrote: post #77

I did some Julia benchmarking over the weekend against a bunch of languages if anyone is interested. The workload is an EKF on an Apple M1, I'm trying to do as many as possible in parallel: https://raw.githubusercontent.com/mech-lang/mech/codex/taich... Compared against Taichi, Halide, Futhark, Rust', Lua, LuaJIT, Numpy and pure scalar Python. Julia holds up great it can run basically as fast as you'd like! (These ar…

I'd like to see how Mojo performs here

Re: How an MIT research project became the Julia programming language

#113

Post by lalalanananana »

AnonHP wrote: post #62

Is Julia any good for general purpose (non-scientific) use? I guess it probably may not have as many libraries as Python. So what do the library and third party package coverage look like in comparison to languages like Python, Go, etc.?

Strong avoid outside of academic use. It's been this way for more than a decade.

Re: How an MIT research project became the Julia programming language

#114

Post by lalalanananana »

patagurbon wrote: post #90
postflopclarity wrote: post #78

Earlier quoted context omitted.

I don't have any financial interest in Julia so I'm a bit confused about the reference to "share holders." I'm just a user. I'm sure there are lots of smart people who found that the language didn't suit their needs. there are also lots of smart people who love using Julia. both things can be true at the same time.

There are no language share holders, and note that this account was created an hour ago just to post vague nonspecific gripes about Julia. There are some real issues in the ecosystem. Specifically there is a high proportion of “gradware” because much like other scientific languages there is a high proportion of graduate students doing their projects and then moving on. The language also encourages relying on packages…

There are vc investments and other corporate sponsors which heavily dictate the language and it's ecosystem.

Re: How an MIT research project became the Julia programming language

#115

Post by klaff »

AnonHP wrote: post #62

Is Julia any good for general purpose (non-scientific) use? I guess it probably may not have as many libraries as Python. So what do the library and third party package coverage look like in comparison to languages like Python, Go, etc.?

Can you give an example of general purpose use? It's not great if you want to make a standalone program and distribute it to other users. It's awesome if you are doing exploratory stuff, quickly exploring different ideas or algorithms. The ecosystem has a lot of high quality stuff but where it lacks you can of course call out to python or R or other languages.

Re: How an MIT research project became the Julia programming language

#116

Post by klaff »

lalalanananana wrote: post #113
AnonHP wrote: post #62

Is Julia any good for general purpose (non-scientific) use? I guess it probably may not have as many libraries as Python. So what do the library and third party package coverage look like in comparison to languages like Python, Go, etc.?

Strong avoid outside of academic use. It's been this way for more than a decade.

Is your ex named Julia?

Re: How an MIT research project became the Julia programming language

#117

Post by smasher164 »

myrmidon wrote: post #29

Julia is really fun to use, and I think they are onto something with the type system: Complex types interact much better across module boundaries than in most other languages; here's a good talk on this by one of the creators: https://www.youtube.com/watch?v=kc9HwsxE1OY The biggest drawback of the language in my view is that Julia is an LLVM toolchain "pretending" to be an interpreted language (it is, technically), t…

Yeah I think if Julia had a plain interpreted mode or a base template JIT that could tier up to LLVM's, they could drive that execution latency down a lot.

Re: How an MIT research project became the Julia programming language

#118

Post by patagurbon »

lalalanananana wrote: post #114
patagurbon wrote: post #90

Earlier quoted context omitted.

There are no language share holders, and note that this account was created an hour ago just to post vague nonspecific gripes about Julia. There are some real issues in the ecosystem. Specifically there is a high proportion of “gradware” because much like other scientific languages there is a high proportion of graduate students doing their projects and then moving on. The language also encourages relying on packages…

There are vc investments and other corporate sponsors which heavily dictate the language and it's ecosystem.

They dictate what their employees are paid to work on, there are no VC investments in The Julia Programming Language

It’s true that MIT and a few other organizations have more influence than others simply because they employ more developers with time/scope to work on the language. Just like every programming language.

But this becomes less true all the time. And most of the direction that is “paid for” is an unadulterated good: JuliaC ahead of time compilation has been requested for over a decade and has made enormous progress.

Re: How an MIT research project became the Julia programming language

#119

Post by eigenspace »

smasher164 wrote: post #117
myrmidon wrote: post #29

Julia is really fun to use, and I think they are onto something with the type system: Complex types interact much better across module boundaries than in most other languages; here's a good talk on this by one of the creators: https://www.youtube.com/watch?v=kc9HwsxE1OY The biggest drawback of the language in my view is that Julia is an LLVM toolchain "pretending" to be an interpreted language (it is, technically), t…

Yeah I think if Julia had a plain interpreted mode or a base template JIT that could tier up to LLVM's, they could drive that execution latency down a lot.

Julia does have an interpreter, but due to the multiple disptach semantics and the type system, it's a rather slow interpreter.

There's some exciting work that was presented in Juliacon 2026 though on an upcoming tiered JIT and this should reduce latency a lot, as you suggest.

It's kinda one of those mid-hanging fruits that has been known about for a long time, but not seriously tackled till now.

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