geni-performance-benchmark
OffsetArrays.jl
| geni-performance-benchmark | OffsetArrays.jl | |
|---|---|---|
| 3 | 7 | |
| 27 | 192 | |
| - | 1.0% | |
| 4.1 | 6.0 | |
| over 3 years ago | 17 days ago | |
| Clojure | Julia | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
geni-performance-benchmark
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PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
Clojure has a high performance data frame library that leverages new JVM vector API and high quality apache arrow protocol.
Talk related - https://youtu.be/5mUGu4RlwKE
https://github.com/zero-one-group/geni-performance-benchmark
- LLVM!
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Clojure High Performance Data Processing System
How often have you seen a Clojure system that soundly beats C, Julia, Python, Spark, and R systems in a data processing benchmark?
OffsetArrays.jl
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Why I am switching my programming language to 1-based array indexing.
Well, there is OffsetArrays in Julia, but it has acquired a reputation as a poison pill because most code assumes the 1-based indexing and it's easy to forget to convert the indexing and screw up the code.
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The Julia language has a number of correctness flaws
Similar correctness issues are a big part of the reason that, several years ago, I submitted a series of pull requests to Julia so that its entire test suite would run without memory errors under Valgrind, save for a few that either (i) we understood and wrote suppressions for, or (ii) we did not understand and had open issues for. Unfortunately, no one ever integrated Valgrind into the CI system, so the test suite no longer fully runs under it, last time I checked. (The test suite took nearly a day to run under Valgrind on a fast desktop machine when it worked, so is infeasible for every pull request, but could be done periodically, e.g. once every few days.)
Even a revived effort on getting core Julia tests to pass under Valgrind would not do much to help catch correctness bugs due to composing different packages in the ecosystem. For that, running in testing with `--check-bounds=yes` is probably a better solution, and much quicker to execute as well. (see e.g. https://github.com/JuliaArrays/OffsetArrays.jl/issues/282)
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-🎄- 2021 Day 6 Solutions -🎄-
You might be interested in OffsetArrays.jl.
- PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
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Why does Julia adopt 1-based index?
Counting starts at one, as do most vector/matrix/tensor indices. If it bothers you too much, see OffsetArrays.jl and Arrays with custom indices.
- some may hate it, some may love it
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Evcxr: A Rust REPL and Jupyter Kernel
No need for another version, Julia supports custom indices by default. Check out https://docs.julialang.org/en/v1/devdocs/offset-arrays/ and https://github.com/JuliaArrays/OffsetArrays.jl
What are some alternatives?
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
StarWarsArrays.jl - Arrays indexed as the order of Star Wars movies
HTTP.jl - HTTP for Julia
TwoBasedIndexing.jl - Two-based indexing
tablecloth - Dataset manipulation library built on the top of tech.ml.dataset
Optimization.jl - Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
tech.ml.dataset - A Clojure high performance data processing system
TailRec.jl - A tail recursion optimization macro for julia.
functorch - functorch is JAX-like composable function transforms for PyTorch.
julia - The Julia Programming Language
StatsBase.jl - Basic statistics for Julia