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Anyone knows what Mojo is doing that Julia cannot do? I appreciate that Julia is currently limited by its ecosystem (although it does interface nicely with Pyth

by Cynddl 1y ago

Anyone knows what Mojo is doing that Julia cannot do? I appreciate that Julia is currently limited by its ecosystem (although it does interface nicely with Python), but I don't see how Mojo is any better then.

bobajeff 1y ago
I've looked into making Python modules with Julia and it doesn't look like that is very well supported right now. Where as it's a core feature of Mojo.
- dunefox 1y ago
  Shouldn't something like this work? https://github.com/JuliaPy/PythonCall.jl https://github.com/JuliaPy/PythonCall.jl
  - bobajeff 1y ago
    That might work but can't seem to find much information on using it to create a pip installable module though.
jakobnissen 1y ago
Mojo to me looks significantly lower level, with a much higher degree of control. Also, it appears to be more robust. Julia is notoriously fickle in both semantics and performance, making it unsuitable for foundational software the way Mojo strives for.
- Archit3ch 1y ago
  > Also, it appears to be more robust. Sure, Mojo the language is more robust. Until its investors decide to 10x the licensing Danegeld.
thetwentyone 1y ago
Especially because Julia has pretty user friendly and robust GPU capabilities such as JuliaGPU and Reactant[2] among other generic-Julia-code to GPU options. 1: https://enzymead.github.io/Reactant.jl/dev/ https://enzymead.github.io/Reactant.jl/dev/ 2: https://enzymead.github.io/Reactant.jl/dev/ https://enzymead.github.io/Reactant.jl/dev/
- jb1991 1y ago
  I get the impression that most of the comments in this thread don't understand what a GPU kernel is. These high-level languages like Python and Julia are not running on the kernel, they are calling into other kernels usually written in C++. The goal is different with Mojo, it says at the top of the article: > write state of the art kernels You don't write kernels in Julia.
  - adgjlsfhk1 1y ago
    Julia's GPU stack doesn't compile to C++. it compiles Julia straight to GPU assembly.
  - jakobnissen 1y ago
    Im pretty sure Julia does JIT compilation of pure Julia to the GPU: https://github.com/JuliaGPU/GPUCompiler.jl https://github.com/JuliaGPU/GPUCompiler.jl
    - actionfromafar 1y ago
      ” you should use one of the packages that builds on GPUCompiler.jl, such as CUDA.jl, AMDGPU.jl, Metal.jl, oneAPI.jl, or OpenCL.jl” Not sure how that organization compares to Mojo.
  - ssfrr 1y ago
    It doesn’t make sense to lump python and Julia together in this high-level/low-level split. Julia is like python if numba were built-in - your code gets jit compiled to native code so you can (for example) write for loops to process an array without the interpreter overhead you get with python. People have used the same infrastructure to allow you to compile Julia code (with restrictions) into GPU kernels
Alexander-Barth 1y ago
I guess that the interoperability with Python is a bit better. But on the other hand, the PythonCall.jl (allowing calling python from julia) is quite good and stable. In Julia, you have quite good ML frameworks (Lux.jl and Flux.jl). I am not sure that you have mojo-native ML frameworks which are similarly usable.
jb1991 1y ago
Isn't Mojo designed for writing kernels? That's what it says at the top of the article: > write state of the art kernels Julia and Python are high-level languages that call other languages where the kernels exist.
- Sukera 1y ago
  No, you can write the kernels directly in Julia using KernelAbstractions.jl [1]. [1] https://juliagpu.github.io/KernelAbstractions.jl/stable/ https://juliagpu.github.io/KernelAbstractions.jl/stable/
  - deleted 1y ago
    [deleted]
hansvm 1y ago
[0] https://danluu.com/julialang/ https://danluu.com/julialang/
ubj 1y ago
> Anyone knows what Mojo is doing that Julia cannot do? First-class support for AoT compilation. https://docs.modular.com/mojo/cli/build https://docs.modular.com/mojo/cli/build Yes, Julia has a few options for making executables but they feel like an afterthought.
MohamedMabrouk 1y ago
* Compiling arbitrary Julia code into a native standalone binary (a la rust/C++) with all its consequcnes.

by Cynddl 1y ago

bobajeff 1y ago

I've looked into making Python modules with Julia and it doesn't look like that is very well supported right now. Where as it's a core feature of Mojo.

dunefox 1y ago
Shouldn't something like this work? https://github.com/JuliaPy/PythonCall.jl https://github.com/JuliaPy/PythonCall.jl
- bobajeff 1y ago
  That might work but can't seem to find much information on using it to create a pip installable module though.

jakobnissen 1y ago

Mojo to me looks significantly lower level, with a much higher degree of control. Also, it appears to be more robust. Julia is notoriously fickle in both semantics and performance, making it unsuitable for foundational software the way Mojo strives for.

Archit3ch 1y ago
> Also, it appears to be more robust. Sure, Mojo the language is more robust. Until its investors decide to 10x the licensing Danegeld.

thetwentyone 1y ago

Especially because Julia has pretty user friendly and robust GPU capabilities such as JuliaGPU and Reactant[2] among other generic-Julia-code to GPU options. 1: https://enzymead.github.io/Reactant.jl/dev/ https://enzymead.github.io/Reactant.jl/dev/ 2: https://enzymead.github.io/Reactant.jl/dev/ https://enzymead.github.io/Reactant.jl/dev/

jb1991 1y ago
I get the impression that most of the comments in this thread don't understand what a GPU kernel is. These high-level languages like Python and Julia are not running on the kernel, they are calling into other kernels usually written in C++. The goal is different with Mojo, it says at the top of the article: > write state of the art kernels You don't write kernels in Julia.
- adgjlsfhk1 1y ago
  Julia's GPU stack doesn't compile to C++. it compiles Julia straight to GPU assembly.
- jakobnissen 1y ago
  Im pretty sure Julia does JIT compilation of pure Julia to the GPU: https://github.com/JuliaGPU/GPUCompiler.jl https://github.com/JuliaGPU/GPUCompiler.jl
  - actionfromafar 1y ago
    ” you should use one of the packages that builds on GPUCompiler.jl, such as CUDA.jl, AMDGPU.jl, Metal.jl, oneAPI.jl, or OpenCL.jl” Not sure how that organization compares to Mojo.
- ssfrr 1y ago
  It doesn’t make sense to lump python and Julia together in this high-level/low-level split. Julia is like python if numba were built-in - your code gets jit compiled to native code so you can (for example) write for loops to process an array without the interpreter overhead you get with python. People have used the same infrastructure to allow you to compile Julia code (with restrictions) into GPU kernels

Alexander-Barth 1y ago

I guess that the interoperability with Python is a bit better. But on the other hand, the PythonCall.jl (allowing calling python from julia) is quite good and stable. In Julia, you have quite good ML frameworks (Lux.jl and Flux.jl). I am not sure that you have mojo-native ML frameworks which are similarly usable.

jb1991 1y ago

Isn't Mojo designed for writing kernels? That's what it says at the top of the article: > write state of the art kernels Julia and Python are high-level languages that call other languages where the kernels exist.

Sukera 1y ago
No, you can write the kernels directly in Julia using KernelAbstractions.jl [1]. [1] https://juliagpu.github.io/KernelAbstractions.jl/stable/ https://juliagpu.github.io/KernelAbstractions.jl/stable/
- deleted 1y ago
  [deleted]

hansvm 1y ago

[0] https://danluu.com/julialang/ https://danluu.com/julialang/

ubj 1y ago

> Anyone knows what Mojo is doing that Julia cannot do? First-class support for AoT compilation. https://docs.modular.com/mojo/cli/build https://docs.modular.com/mojo/cli/build Yes, Julia has a few options for making executables but they feel like an afterthought.

MohamedMabrouk 1y ago

* Compiling arbitrary Julia code into a native standalone binary (a la rust/C++) with all its consequcnes.