Julia Computing Raises $4.6M in Seed Funding • Hacker News Board

Re: Julia Computing Raises $4.6M in Seed Funding

#131

Post by ScottPJones » Fri, Jun 23, 2017, 12:38 AM UTC

dangjc wrote: post #129

moomin wrote: post #113

Earlier quoted context omitted.

This sounds like a small thing, but with 1-based arrays, I'd bet more on it taking share from MatLab/R than from Rust or Java.

I didn't think 1 based arrays would be a big deal, but whenever I try to port code from Julia to almost any other environment (C++, python/numpy, scala, JS), it becomes one of the hardest things to reason about quickly and correctly.

1-based arrays, and column-major layout of arrays annoyed me at first, however, one of the beautiful things is that much of Julia is written in Julia. If you want 0-based (or arbitrary based!) arrays, then simply use the https://github.com/JuliaArrays/OffsetArrays.jl package, and PermutedDimArrays have been added to Base, to handle some of the issues of dealing with row-major (and other sorts of memory layout) matrices.

Re: Julia Computing Raises $4.6M in Seed Funding

#132

Post by wedesoft » Fri, Jun 23, 2017, 7:37 AM UTC

maimaiml wrote: post #112

flavio81 wrote: post #103

Earlier quoted context omitted.

Maybe it is terrible for you... But good enough for doing numerical computing for the NASA and for Raytheon. The NASA used it for complete command of the Deep Space 1 spacecraft. "The Remote Agent" wasn't just entirely written in Common Lisp, it also won the NASA's Software of the Year Award... https://ti.arc.nasa.gov/tech/asr/planning-and-scheduling/rem... "It's one small step in the history of space flight. But it…

> Maybe it is terrible for you... It is. I know of the examples you mention (and some of them like planning may not really involve much numerical work) but the fact is that unless you're doing things by scratch (like starting from GEMM), numerical libraries are often badly documented, slow or otherwise incomplete (or a mixture thereof). You can disagree with me, but Tamas Papp who maintained a bunch CL libraries seem…

Have done exactly that using GOOPS which is Guile's equivalent of CLOS:

  scheme@(guile-user)> (use-modules (aiscm sequence) (aiscm element))
  scheme@(guile-user)> (define a (arr (1 2 3) (4 5 6)))
  scheme@(guile-user)> (get a)
  $1 = #>>>:
  ((1 2 3)
   (4 5 6))
  scheme@(guile-user)> (get a 1)
  $2 = #>>:
  (4 5 6)
  scheme@(guile-user)> (get a 0 1)
  $3 = 4
  scheme@(guile-user)> (get (get a 1) 0)
  $4 = 4

That's the whole point of macros: To be able to create embedded domain specific (mini) languages.

[1]: https://github.com/wedesoft/aiscm

Re: Julia Computing Raises $4.6M in Seed Funding

#133

Post by moomin » Fri, Jun 23, 2017, 12:25 PM UTC

ScottPJones wrote: post #131

dangjc wrote: post #129

Earlier quoted context omitted.

I didn't think 1 based arrays would be a big deal, but whenever I try to port code from Julia to almost any other environment (C++, python/numpy, scala, JS), it becomes one of the hardest things to reason about quickly and correctly.

1-based arrays, and column-major layout of arrays annoyed me at first, however, one of the beautiful things is that much of Julia is written in Julia. If you want 0-based (or arbitrary based!) arrays, then simply use the https://github.com/JuliaArrays/OffsetArrays.jl package, and PermutedDimArrays have been added to Base, to handle some of the issues of dealing with row-major (and other sorts of memory layout) matric…

Doesn't this mean that instead you're now dealing with inconsistent data representations?

Re: Julia Computing Raises $4.6M in Seed Funding

#134

Post by andyferris » Tue, Jun 27, 2017, 3:35 AM UTC

tnecniv wrote: post #76

Fomite wrote: post #54

Earlier quoted context omitted.

For non-CS scientific computing users, "a high performance language with easy syntax" is a big feature.

It's why the horror that is MATLAB exists. I'm looking forward to replacing MATLAB with the much more ergonomic Julia soon though.

Yes, do it! It was an easy transition years ago, now Julia seems light-years ahead.