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Julia Computing raises $24M Series A

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Re: Julia Computing raises $24M Series A

#191

Post by mbauman »

enriquto wrote: post #188
oscardssmith wrote: post #166

Earlier quoted context omitted.

The key to make multiple dispatch work well is that you shouldn't have to think about what method gets called. For this to work out, you need to make sure that you only add a method to a function if it does the "same thing" (so don't use >> for printing for example). To Dr the benefit of this in action, consider that in Julia 1im+2//3 (the syntax for sqrt(-1)+2 thirds) works and gives you a complex rational number (2…

> make sure that you only add a method to a function if it does the "same thing" But this only concerns when I'm writing the code myself. If I read some code and I see a few nested function calls, there's a combinatorial explosion of possible types that gives me vertigo. > complex and rational numbers can be constructed using anything that has arithmetic defined. seriously? this does not seem right, it cannot be like…

There's no hidden dirty magic, but you're right: Complex numbers require `Real` components and Rationals require `Integer` numerators and denominators. Both `Real` and `Integer` are simply abstract types in the numeric type tree, but you're free to make your own. You can see how this works directly in their docstrings — it's that type parameter in curly braces that defines it, and `
    help?> Complex
    search: Complex complex ComplexF64 ComplexF32 ComplexF16 completecases
    
      Complex{T

Re: Julia Computing raises $24M Series A

#192

Post by leephillips »

spenczar5 wrote: post #174
leephillips wrote: post #74

Earlier quoted context omitted.

I’m aware that there is plenty of serious computation done with these tools. I don’t want to overstate; I merely meant that, for a fresh project, Julia is now a better choice for a large-scale simulation. Note that no combination of any of the faster implementations of Python + Numpy libraries has ever been used at the most demanding level of scientific computation. That has always been Fortran, with some C and C++,…

> Note that no combination of any of the faster implementations of Python + Numpy libraries has ever been used at the most demanding level of scientific computation. That has always been Fortran, with some C and C++, and now Julia. This still seems like an overstatement, but maybe it depends on what you mean by "most demanding level." I work on systems for the Rubin Observatory, which is going to be the largest astro…

By a large-scale calculation I have in mind something like this: https://arxiv.org/pdf/2006.09368.pdf, which is in your field of astronomy. It uses about a billion dark-matter elements and was run on the Cobra supercomputer at Max Planck, which has about 137,000 CPU cores. It used the AREPO code, which is a C program that uses MPI. If you know of any calculation in this class using Python I would be interested to hear about it. But generally one doesn’t have one’s team write a proposal for time on a national supercomputing center and then, if it is approved, when your 100-hour slot is finally scheduled, upload a Python script to the cluster. But strange things happen.

EDIT: Yes, numba is impressive.

Re: Julia Computing raises $24M Series A

#193

Post by snicker7 »

spywaregorilla wrote: post #123

I played with Julia a bit in grad school. Although I didn't end up using it much after that I thought it was a lovely language. Forget python, I hope Julia manages to kill off Matlab and its weird stranglehold on various pockets of academia. Congrats to the team here.

For satellite seperation dynamics modeling, NASA switched from MATLAB (Simulink) to Julia and got a 15,000x performance boost.

https://www.youtube.com/watch?v=tQpqsmwlfY0

Re: Julia Computing raises $24M Series A

#194

Post by systemvoltage »

amkkma wrote: post #161
systemvoltage wrote: post #157

Earlier quoted context omitted.

I’m a tortured soul, my opinions might be biased and I hope things improve with Julia. We absolutely cannot upgrade Julia version right now, dozens of repos full of complicated scientific code. Management doesn’t care as far as it barely runs. I don’t think it’s fair to blame Julia for it but it just shows how much more it needs to go. That should be looked at as a positive thing. I have one more complain to Julia co…

>I’ve seen a cult-like behavior in Julia community that is borderline toxic. Sorry, it’s the truth and needs to be said. Speed isn’t everything and people are magnetized by the benchmarks on the Julia website, especially non-software engineers. I think all languages have this dynamic...I've seen it with python and R. To some extent it's fed by what we perceive as criticisms from people defending their favorite incumb…

Agreed and thanks for being charitable for the Julia community. It’s an interesting thing to balance: push and market the language, navigate haters and naysayers while also deeply respecting feedback and criticisms. We can all do better.

Re: Julia Computing raises $24M Series A

#195

Post by aDfbrtVt »

KenoFischer wrote: post #124
p_j_w wrote: post #116

Earlier quoted context omitted.

Understandable if you can't answer this question, but how much work have you guys done with SDRs and arrays?

This project is just starting, so I have hardware sitting on my desk and have used it a bit, but other than that not much.

What kind of HW do you have? I did some work with the NI version of the USRP B210 using C++ and was pretty impressed with the quality of the FW and libraries. I hope to give it a try with Julia and UHDBindings.jl

Re: Julia Computing raises $24M Series A

#196

Post by jpeloquin »

oscardssmith wrote: post #166
enriquto wrote: post #153

Earlier quoted context omitted.

can you show a simple example of that? I tend to see multiple dispatch as a mental burden, (e.g.: when I see a function call, where will it be dispatched? the answer dependa on the types that I'm juggling, that may not even be visible at that point...)

The key to make multiple dispatch work well is that you shouldn't have to think about what method gets called. For this to work out, you need to make sure that you only add a method to a function if it does the "same thing" (so don't use >> for printing for example). To Dr the benefit of this in action, consider that in Julia 1im+2//3 (the syntax for sqrt(-1)+2 thirds) works and gives you a complex rational number (2…

> The key to make multiple dispatch work well is that you shouldn't have to think about what method gets called. For this to work out, you need to make sure that you only add a method to a function if it does the "same thing" (so don't use >> for printing for example).

Thanks for writing this. I think it is an important concept for getting started with Julia. When I tried Julia, I was initially confused and concerned about the subtyping hierarchy, which as far as I understand is undocumented. "Apart from a partial description in prose in Bezanson [2015], the only specification of subtyping is 2,800 lines of heavily optimized, undocumented C code." [0]. Assurance that users can safely ignore the subtyping hierarchy if we maintain semantic equivalence between methods, and that this actually works out in practice, makes it easier to commit to using the language.

[0] https://dl.acm.org/doi/10.1145/3276483

Re: Julia Computing raises $24M Series A

#197

Post by spywaregorilla »

helmholtz wrote: post #177
mint2 wrote: post #158

Earlier quoted context omitted.

Matlab, the SAS of academia and certain engineering fields.

I won't hear of it. Matlab is great. Superb at manipulating matrices, great for getting started with differential equations, world-class plotting library, and massively forgiving. All the things a computational engineer like me needs. I would never use it for producing software meant for distribution, but people mainly hate on it because it's 'cool', without realising that it excels at what it does. I fucking love ma…

https://diffeq.sciml.ai/stable/tutorials/ode_example/

Diffeq are one of those things that Julia is a particularly good choice for that benefits strongly from its types and what not. Give it a shot if you do a lot of this.

Julia syntax resembles matlab more than python or R.

Re: Julia Computing raises $24M Series A

#198

Post by glial »

spywaregorilla wrote: post #197
helmholtz wrote: post #177

Earlier quoted context omitted.

I won't hear of it. Matlab is great. Superb at manipulating matrices, great for getting started with differential equations, world-class plotting library, and massively forgiving. All the things a computational engineer like me needs. I would never use it for producing software meant for distribution, but people mainly hate on it because it's 'cool', without realising that it excels at what it does. I fucking love ma…

https://diffeq.sciml.ai/stable/tutorials/ode_example/ Diffeq are one of those things that Julia is a particularly good choice for that benefits strongly from its types and what not. Give it a shot if you do a lot of this. Julia syntax resembles matlab more than python or R.

Thanks, I'll give it a shot. Matlab's syntax for matrices is, naturally, great.

Re: Julia Computing raises $24M Series A

#199

Post by xiaodai »

maybelsyrup wrote: post #187
helmholtz wrote: post #177

Earlier quoted context omitted.

I won't hear of it. Matlab is great. Superb at manipulating matrices, great for getting started with differential equations, world-class plotting library, and massively forgiving. All the things a computational engineer like me needs. I would never use it for producing software meant for distribution, but people mainly hate on it because it's 'cool', without realising that it excels at what it does. I fucking love ma…

I know little about Matlab, but I know a lot about SAS, where it's the default analytical environment in public health practice and research. SAS is trash, and a ripoff to boot. R has made good inroads, giving SAS a tiny bit of pressure, but frankly it needs more. Bring on Julia! And python and anything else.

that's why SAS developed Viya so you can run Python and R code.

Re: Julia Computing raises $24M Series A

#200

Post by xiaodai »

trenchgun wrote: post #88
ampdepolymerase wrote: post #81

Earlier quoted context omitted.

Those two niches don't pay. They are effectively useless outside of the occasional evangelism on HN.

Money does not create code, humans do.

Money don't do jobs, humans do.

You see the logical fallacy in ur argument now?

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