MatrixMultiplier VS julia

Compare MatrixMultiplier vs julia and see what are their differences.

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MatrixMultiplier julia
5 98
3 36,581
- 1.5%
6.5 9.9
about 1 month ago 4 days ago
Shell Julia
GNU General Public License v3.0 only MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of MatrixMultiplier. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-07.


Posts with mentions or reviews of julia. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-15.
  • Recursion absolutely necessary for distributed computing? | 2021-10-15
    Then, if everything is pure functions, instead of iteratively mutating an array, you can recursively do calls that make new arrays that change one element at a time. But wait, doesn't that sound very inefficient compared to mutation? Well yes it does! It would satisfy the purity argument to allow a compiler to know how to auto-parallelize, but it would be making so many temporary arrays that it would likely be slower than a good explicit loop. For this reason you need compiler optimizations which would remove the intermediate arrays and transform it under the hood to mutating code (see as an example of this in the Julia compiler). This is one optimization that is needed, another is the tail-call elimination that I mentioned earlier, etc. If you have all pure functions, and if all of these optimizations are perfect, then you can match the serial code performance of C/Fortran. But that is a big if, which is why you don't see successful BLAS's written in say Haskell (GHC is a good compiler but it's hard to make this perfect).
  • The Beatles - Julia [1968]
  • Can someone explain this expression? | 2021-10-14
    Very useful discussion on currying in this issue, if you're up for that sort of reading.
  • For PHYS JAM: What would be the best language to program in? | 2021-10-13
  • New features coming in Julia 1.7 [] | 2021-10-05
    If you prefer to read the official NEWS file on GitHub: | 2021-10-05
    You can find that here:
  • New features coming in Julia 1.7 | 2021-10-04
    Agreed on the stacktraces. I think a few small tweaks can make them a thousand times easier to read | 2021-10-04
    └ (y/n) [y]:

    Surprised it defaults to [y] option, especially since packages can be pretty heavy with artifacts and lots of dependencies to precompile. One accidental extra Return and you might be sitting there for five minutes.

    > keepat!(v, i)

    Not a fan of the name. The ! indicates the mutation as the article points out, but keeponlyat! would have been much clearer and immediately obvious, and more than justifies its length IMO.

    Lots of nice quality of life improvements in this version. One that the article doesn't mention is `julia [email protected]` [1] - being able to specify a shared environment as the starting environment for the REPL.


  • Looking for an Open Source Project? Try Julia. | 2021-10-04
    If Julia has piqued your interest, take a look at the repository and Currently, the repo has approximately 3.4k open issues, so get started and pick up an issue today!
  • Common Lisp | 2021-10-02
    I agree that a language homepage should be information dense, and give the new user a clear overview without having to scroll. I think the Common Lisp homepage is an improvement over what I remember from years ago, and while it’s visually appealing it’s not as immediately useful as I’d like.

    Besides the examples Zababa offered, I’d say the home pages for Ruby, Julia, and Python are also good:

What are some alternatives?

When comparing MatrixMultiplier and julia you can also consider the following projects:

rust-numpy - PyO3-based Rust binding of NumPy C-API

NetworkX - Network Analysis in Python

Numba - NumPy aware dynamic Python compiler using LLVM

duckdf - 🦆 SQL for R dataframes, with ducks

py2many - Python to CLike languages transpiler

Dagger.jl - A framework for out-of-core and parallel execution

Lua - Lua is a powerful, efficient, lightweight, embeddable scripting language. It supports procedural programming, object-oriented programming, functional programming, data-driven programming, and data description.

DFTK.jl - Density-functional toolkit

JET.jl - scratch: experimental code analyzer for Julia, no need for additional type annotations

femtolisp - a lightweight, robust, scheme-like lisp implementation

PackageCompiler.jl - Compile your Julia Package

PyCall.jl - Package to call Python functions from the Julia language