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Julia Computing raises $24M Series A

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Re: Julia Computing raises $24M Series A

#21

Post by NeutralForest »

axpy906 wrote: post #18
djhaskin987 wrote: post #2

Can someone please explain to me, a mere mortal, what is the big deal with Julia. Why use it, when there are so many other good languages out there with more community/support? Honest question.

My understanding is that it runs faster than native python and R. That said with Numba and other libraries, see no point.

It's easier to write Julia code than to deal with Numba tbh and the ecosystem around Julia makes the code composable which is often not the case if you write Numba code and have to deal with other libraries.

Re: Julia Computing raises $24M Series A

#23

Post by p_j_w »

KenoFischer wrote: post #3

I guess this would be a good place to mention that we're hiring for lots of positions, so if you would like to help build JuliaHub, or work on compilers, or come play with SDRs, please take a look at our job openings :) : https://juliacomputing.com/jobs/

>or come play with SDRs

This sounds like an absolute dream!

Re: Julia Computing raises $24M Series A

#24

Post by codekilla »

ChrisRackauckas wrote: post #17
Kranar wrote: post #8

Earlier quoted context omitted.

I think your question presupposes a lot of assumptions that may not be right. For one, I don't know that Julia is like a "big deal", certainly Python is the big deal in this field and I doubt Julia is looking to displace it wholesale. That said, Julia is a great addition to the scientific computing landscape because of its performance compared to other languages and its use of modern programming features. Python is j…

Julia Computing is not a services company. There are commercial products built off of this stack which are the core of Julia Computing. For example, https://pumas.ai/ is a product for pharmacology modeling and simulation, and runs on the JuliaHub cloud platform of Julia Computing. It is already a big deal in the industry, with the quote everyone refers to "Pumas has emerged as our 'go-to' tool for most of our analyse…

Wanted to ask if JuliaDB is something that might get more development attention? Or will that remain a community project? (I see it’s been in need of a release for awhile.)

Re: Julia Computing raises $24M Series A

#25

Post by coldtea »

djhaskin987 wrote: post #2

Can someone please explain to me, a mere mortal, what is the big deal with Julia. Why use it, when there are so many other good languages out there with more community/support? Honest question.

>Why use it, when there are so many other good languages out there with more community/support? Honest question.

Such a question seems sort of in bad faith (or loaded), since the selling points of Julia have been hammered time and again on HN and elsewhere, and are prominent on its website. It's a 1 minute search to find them, and if someone is already aware that there's this thing called Julia to the point that they think it's made to be "a big deal", they surely have seen them.

So, what could the answer to the question above be? Some objective number that shows Julia is 25.6% better than Java or Rust or R or whatever?

But first, who said it's a "big deal"? It's just a language that has some development action, seems some adoption, and secured a modest fundng for its company. That's not some earth shattering hype (if you want to see that, try to read about when Java was introduced. Or, to a much lesser degree, Ada, for that matter).

You use a language because you've evaluated it for your needs and agree with the benefits and tradeoffs.

Julia is high level and at the same time very fast for numerical computing allowing you to keep a clean codebase that's not a mix of C, C++, Fortran and your "real" language, while still getting most of the speed and easy parallelization. It also has special focus on support for that, for data science, statistics, and science in general. It's also well designed.

On the other hand, it has slow startup/load times, incomplete documentation, smaller ecosystem, and several smaller usability issues.

Re: Julia Computing raises $24M Series A

#26

Post by tfehring »

axpy906 wrote: post #18
djhaskin987 wrote: post #2

Can someone please explain to me, a mere mortal, what is the big deal with Julia. Why use it, when there are so many other good languages out there with more community/support? Honest question.

My understanding is that it runs faster than native python and R. That said with Numba and other libraries, see no point.

Numba is great for pure functions on primitive types but it breaks down when you need to pass objects around. PyPy is fantastic for single-threaded applications but doesn't play nicely with multiprocessing or distributed computing IME. Numpy helps for stuff you can vectorize, but there's a lot of stuff you can't (or can but shouldn't); it also brings lots of minor inconveniences by virtue of not being a native type - e.g., the code to JSON serialize a `Union[Sequence[float], np.ndarray]` isn't exactly Pythonic.

Re: Julia Computing raises $24M Series A

#27

Post by danuker »

axpy906 wrote: post #18
djhaskin987 wrote: post #2

Can someone please explain to me, a mere mortal, what is the big deal with Julia. Why use it, when there are so many other good languages out there with more community/support? Honest question.

My understanding is that it runs faster than native python and R. That said with Numba and other libraries, see no point.

> runs faster than native python and R

That's a bit of an understatement. It's about as fast as C and Rust (ignoring JIT compilation time).

https://julialang.org/benchmarks/

Re: Julia Computing raises $24M Series A

#28

Post by ChrisRackauckas »

codekilla wrote: post #24
ChrisRackauckas wrote: post #17

Earlier quoted context omitted.

Julia Computing is not a services company. There are commercial products built off of this stack which are the core of Julia Computing. For example, https://pumas.ai/ is a product for pharmacology modeling and simulation, and runs on the JuliaHub cloud platform of Julia Computing. It is already a big deal in the industry, with the quote everyone refers to "Pumas has emerged as our 'go-to' tool for most of our analyse…

Wanted to ask if JuliaDB is something that might get more development attention? Or will that remain a community project? (I see it’s been in need of a release for awhile.)

It is not in our current set of major products. That said, informal office discussions mentioned JuliaDB as recently as last week, so it's not forgotten. If there's a demonstrated market, say a need for new high-performance cloud data science tools as part of the pharmaceutical domains we work in, then something like JuliaDB could possibly be revived in the future (of course, this is no guarantee).

Re: Julia Computing raises $24M Series A

#29

Post by darksaints »

I'm sure there is some good in there to have some solid funding for additional development, but now that it's a commercial venture, I'm terrified to see the revenue model. The moment you build your profit platform on top of someone else's profit platform, you become someone else's servant.

Re: Julia Computing raises $24M Series A

#30

Post by notafraudster »

leephillips wrote: post #15
djhaskin987 wrote: post #2

Can someone please explain to me, a mere mortal, what is the big deal with Julia. Why use it, when there are so many other good languages out there with more community/support? Honest question.

If you are doing very high-performance numerical work, your choices¹ are Fortran, C, C++, or Julia. Julia is way more fun to program in than the other choices. Also, it has some properties² that make code re-use and re-combination especially easy. 1 https://www.hpcwire.com/off-the-wire/julia-joins-petaflop-cl... 2 https://arstechnica.com/science/2020/10/the-unreasonable-eff...

What's the argument against using R and dropping into RCpp for very limited tasks? I (helped) write a very widely used R modelling package and while I wasn't doing anything on the numerical side, we seemed to get great performance from this approach -- and workflow-wise it wasn't too dissimilar to 25 years ago where I had to occasionally drop in X86 assembly to speed up C code!

(Not a hater of Julia at all, very much think it's a cool language and an increasingly vibrant ecosystem and have been consistently impressed when Julia devs have spoke at events I've attended)

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