einshape | Tullio.jl | |
---|---|---|
1 | 4 | |
90 | 584 | |
- | - | |
0.0 | 5.2 | |
over 1 year ago | 5 months ago | |
Python | Julia | |
Apache License 2.0 | MIT License |
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einshape
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A basic introduction to NumPy's einsum
Einops looks nice! It reminds me of https://github.com/deepmind/einshape which is another attempt at unifying reshape, squeeze, expand_dims, transpose, tile, flatten, etc under an einsum-inspired DSL.
Tullio.jl
- A basic introduction to NumPy's einsum
- Generic GPU Kernels
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Julia: Faster than Fortran, cleaner than Numpy
Julia ships with OpenBLAS, in some cases there are pure-Julia "blas-like" routine that can be as fast:
https://github.com/mcabbott/Tullio.jl
What are some alternatives?
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Zygote.jl - 21st century AD
cadabra2 - A field-theory motivated approach to computer algebra.
CUDA.jl - CUDA programming in Julia.
Einsum.jl - Einstein summation notation in Julia
ForwardDiff.jl - Forward Mode Automatic Differentiation for Julia
einsum - Einstein Summation for Arrays in R
TensorOperations.jl - Julia package for tensor contractions and related operations
JuliaInterpreter.jl - Interpreter for Julia code
futhark - :boom::computer::boom: A data-parallel functional programming language
DaemonMode.jl - Client-Daemon workflow to run faster scripts in Julia
julia-numpy-fortran-test - Comparing Julia vs Numpy vs Fortran for performance and code simplicity