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Julia Computing raises $24M Series A

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11–20 of 246 posts

Re: Julia Computing raises $24M Series A

#11
post #4

The article mentions a circuit simulation package named JuliaSPICE, but I can't find any intonation on it. Can someone please provide a link?

For the earliest details, see the press release from our DARPA project: https://juliacomputing.com/media/2021/03/darpa-ditto/ . This is being done in a way where a fully usable software is the result, so that those accelerations are not just a one-off prototype but a product that everyone else can use by the end. For more details, wait until next week's JuliaCon.

Re: Julia Computing raises $24M Series A

#12

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.

Short answer is that it is (imo) by far the best language for writing generic and fast math. Multiple dispatch allows you to write math using normal notation and not have to jump through hoops to do so.

Re: Julia Computing raises $24M Series A

#13
post #4

The article mentions a circuit simulation package named JuliaSPICE, but I can't find any intonation on it. Can someone please provide a link?

There's not really much public about it yet. There'll be a technical talk about it at JuliaCon and we're talking to initial potential customers about it, but it's not quite ready for the wider community yet. If you want some of the technical details, I talked about it a bit in this earlier thread https://news.ycombinator.com/item?id=26425659 about the DARPA funding for our neural surrogates work in circuits (which wi…

Oh, I suppose I should add if you're looking to use something like this in a commercial setting, please feel free to reach out. Either directly to me, or just email info@ and you'll get routed to the right place.

Re: Julia Computing raises $24M Series A

#14

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.

It’s a solid combination of performance, easy syntax and flexible environment. A big drawback of Python is that any performant code is actually written in a lower level language, with foreign function calls.

That’s not to say that there are no disadvantages to Julia. I personally see Julia as a beefed up, new and improved R.

Re: Julia Computing raises $24M Series A

#15

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...

Re: Julia Computing raises $24M Series A

#16

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.

Composability via dispatch-oriented programming, e.g. [1]

It also pretty much solved my version of the two-language problem, but that means different things to different people so ymmv.

[1] https://www.youtube.com/watch?v=kc9HwsxE1OY

Re: Julia Computing raises $24M Series A

#17
post #8

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.

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 analyses in recent months" from the Director Head of Clinical Pharmacology and Pharmacometrics at Moderna Therepeutics during 2020 (for details, see the full approved press release from the Pumas.ai website). JuliaSim is another major product which is being released soon, along with JuliaSPICE publicly in the pipeline.

But indeed, Julia Computing differentiates itself from something like MATLAB or Mathematica by leveraging a strong open source community on which these products are developed. These products add a lot of the details that are generally lacking in the open source space, such as strong adherents to file formats, regulatory compliance and validation, GUIs, etc. which are required to take such a product from "this guy can use it" to a fully marketable product usable by non-computational scientists. I will elaborate a bit more on this at JuliaCon next week in my talk on the release of JuliaSim.

Re: Julia Computing raises $24M Series A

#18

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.

Re: Julia Computing raises $24M Series A

#20

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.

There really aren't that many languages out there trying to be on the cutting edge of JIT for scientific computing with a great REPL experience. There are a few areas where developers have to prototype in a language like Python or MATLAB to design their systems, generate test data, and even just plot stuff during debugging then rewrite in C/C++ for speed. It's an enormous time sink that is prone to errors, and leads to terrible SWE culture.

If Julia can provide both the REPL/debugging experience of a language like Python or MATLAB with a fast enough JIT to use in production it would be an enormous boon to productivity and robustness.

There are a few limiting factors but I don't think they're absolute.

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