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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

#91

Post by eigenspace »

retsibsi wrote: post #89
postflopclarity wrote: post #31

Earlier quoted context omitted.

I think that article has been discussed to death and there's not much value in resurrecting it on every single post that mentions Julia. ultimately if you think the language might be a fit for your use case, I'd recommend trying it out and see how you like it first-hand.

I'm one of today's lucky 10,000, so I'm glad it was linked here (and would happily read a defence of the language from one of those previous discussions, too). When the criticisms relate to correctness bugs, I don't think 'try it out and see how you like it' is sufficient. I might love the syntax and the design and so on, but that doesn't tell me whether I'm going to run into serious bugs some time in the future.

Here's a somewhat recent discussion sparked by someone who was concerned having read the blogpost: https://discourse.julialang.org/t/julia-stability-vs-rust-fo...

It got a little long and meandered a bit, but I think there's some good, nuanced discussion there.

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

#92

Post by postflopclarity »

eigenspace wrote: post #91
retsibsi wrote: post #89

Earlier quoted context omitted.

I'm one of today's lucky 10,000, so I'm glad it was linked here (and would happily read a defence of the language from one of those previous discussions, too). When the criticisms relate to correctness bugs, I don't think 'try it out and see how you like it' is sufficient. I might love the syntax and the design and so on, but that doesn't tell me whether I'm going to run into serious bugs some time in the future.

Here's a somewhat recent discussion sparked by someone who was concerned having read the blogpost: https://discourse.julialang.org/t/julia-stability-vs-rust-fo... It got a little long and meandered a bit, but I think there's some good, nuanced discussion there.

in particular, https://discourse.julialang.org/t/julia-stability-vs-rust-fo... is a very visceral example of how bugs like these arise everywhere (including python) and are in no way unique or even exaggerated in Julia.

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

#93

Post by [deleted] »

postflopclarity wrote: post #92
eigenspace wrote: post #91

Earlier quoted context omitted.

Here's a somewhat recent discussion sparked by someone who was concerned having read the blogpost: https://discourse.julialang.org/t/julia-stability-vs-rust-fo... It got a little long and meandered a bit, but I think there's some good, nuanced discussion there.

in particular, https://discourse.julialang.org/t/julia-stability-vs-rust-fo... is a very visceral example of how bugs like these arise everywhere (including python) and are in no way unique or even exaggerated in Julia.

[deleted]

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

#94

Post by penteract »

eigenspace wrote: post #50
radiator wrote: post #30

Do you think the criticism in the article "Why I no longer recommend Julia" about correctness is still valid? * there are too many correctness and composability bugs throughout the ecosystem to justify using it in just about any context where correctness matters * https://yuri.is/not-julia/

Programming languages have bugs. These things happen, and this tired article blows them totally out of proportion. Some languages are less permissive, and have a culture of searching harder for corner cases and dealing with them than others, that is true. I would expect to find less cases like this in Rust, but more cases like this in Python. Julia is an extremely flexible and permissive language, which means that ge…

> Some languages are less permissive, and have a culture of searching harder for corner cases and dealing with them than others, that is true. I would expect to find less cases like this in Rust, but more cases like this in Python.

My expectation is that when I think I've found a bug in the programming language implementation I'm using, it's actually me that's mistaken (or at least that language lawyers consider me to be mistaken). Hearing about someone who has encountered multiple bugs (in regular use, rather than running a fuzzer or being directly involved in implementing the language) makes me very wary.

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

#95

Post by [deleted] »

lalalanananana wrote: post #52
eigenspace wrote: post #49

Julia is such a great language, it's what really made me care about end enjoy programming. I think it's the modern language which has taken the most lessons from lisps, and has come up with some great ideas of its own too. There's lots to like, but I think the thing I love most about it and find it so interesting is that it's almost uniquely good at taking a piece of code and transforming it's meaning in various ways…

It was a great idea for a language. In practice though,it's hard to recommend. Great pet project for some mit professors to make a bunch of side money on top of their salaries though. Everyone else riding it is pretty much trying to niche their career rather then build something people can rely on unfortunately. It's the most unstable language I've ever used. In production I watched companies spend millions of dollar…

[deleted]

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

#96

Post by [deleted] »

[deleted] wrote: post #95
lalalanananana wrote: post #52

Earlier quoted context omitted.

It was a great idea for a language. In practice though,it's hard to recommend. Great pet project for some mit professors to make a bunch of side money on top of their salaries though. Everyone else riding it is pretty much trying to niche their career rather then build something people can rely on unfortunately. It's the most unstable language I've ever used. In production I watched companies spend millions of dollar…

[deleted]

[deleted]

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

#97

Post by empyrrhicist »

guiriduro wrote: post #36
prof-dr-ir wrote: post #24

Julia is fantastic if you do numerical work and want to write out your inner loops explicitly without sacrificing too much performance, either for pedagogical reasons or because you want to fiddle with the algorithm. It is a lot of fun to start from an empty file, add maybe an import LinearAlgebra, and develop things like a convolutional neural network or a Markov-chain Monte Carlo algorithm completely from scratch.…

Julia also has some of the nicest GPU abstraction frameworks of any language, achieving pretty low friction portability over a decent subset of CUDA, Metal, ROCm and CPU. KernelAbstractions.jl, AcceleratedKernels.jl etc.

This is one of my favorite things about it. Very pleasant to use.

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

#98

Post by Someone »

Joel_Mckay wrote: post #46
Someone wrote: post #41

Earlier quoted context omitted.

> Julia is the first language I've seen in years that implicitly abstracts parallelism cleanly. What do you mean by “implicitly”? A single dot is short but not implicit. I also do not see https://docs.julialang.org/en/v1/manual/parallel-computing/ s mention that such map calls (can) run on multiple threads.

The abstraction does not require a lot of understanding/bodges to get performant code by amateurs: https://cuda.juliagpu.org/stable/tutorials/introduction/ But I agree the shared memory Distributed Computing part of Julia still needs a lot of work. Spawning binary image instances over ssh is too fragile. =3

> The abstraction does not require a lot of understanding/bodges to get performant code by amateurs

I agree the change is simple, and didn’t question that; I questioned the “implicitly” in the claim

> Julia is the first language I've seen in years that implicitly abstracts parallelism cleanly.

(Aside: I think scala does this even nicer. There, adding `.par` can make code run multi-threaded. See https://docs.scala-lang.org/overviews/parallel-collections/o...)

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

#99

Post by kkylin »

eigenspace wrote: post #49

Julia is such a great language, it's what really made me care about end enjoy programming. I think it's the modern language which has taken the most lessons from lisps, and has come up with some great ideas of its own too. There's lots to like, but I think the thing I love most about it and find it so interesting is that it's almost uniquely good at taking a piece of code and transforming it's meaning in various ways…

There's understandably been a focus on speed, but what I really like about Julia is being able to write clear code: it has a lot of the flexibility and expressiveness that I like in Lisps, but with better numerical libraries than most Lisps/Schemes, and I really like prototyping algorithms in it. To me (an applied mathematician) it is just a nice tool for thinking in. Not having to compromise too much on speed is a big bonus.

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

#100

Post by tonyarkles »

Joel_Mckay wrote: post #26
tonyarkles wrote: post #16

Earlier quoted context omitted.

I'm currently split between Python and Julia, having used R happily in the past for data analysis and Matlab for this and that in my EE program. For me, Julia crushes one niche that the rest of them are not good at: making the math look like the math. https://docs.sciml.ai/ModelingToolkit/stable/tutorials/nonli... If you've used something like SciPy or symbolic Matlab or Maxima or whatever, it always feels like I'm v…

Julia is fun, but is still mostly an academic language. Very few shops will use it in the private sector. Python is also more common as a prototype integration language, and rarely seen in industrial areas. If you are an EE that wants to remain employed... than make sure you have documented hours with C/C++, Verilog on Zynq, and ladder logic for Rockwell automation products. Best of luck =3

Oh, my friend, I’m in my 40s now and while I’ve never touched ladder logic (mostly on purpose), I can honestly say I’ve been writing C since the last century and C++ only a few years less. I remember, with pain in my heart, what C++ looked like before C++11, C++14, and C++17. C++03 had just come out when I started and lots of features even there weren’t really all that baked in the toolchains at them time :).

Zynq is super cool and strongly agree that it’s worth looking into, although starting with just a naked little FPGA board might be more approachable. On the other hand, if you’re sufficiently capable with both embedded Linux and Verilog to successfully implement a piece of hardware in the PL and build a driver and userspace for it in the PS, you’re definitely miles ahead of most candidates.

TI/Octavo chips with the PRUs are kind of similar; not that they’re asynchronous logic like the Zynq PL is, but they’re similarly powerful as far as doing hard real-time deterministic jobs driven by an attached Linux core.

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