| Tullio.jl | einshape | |
|---|---|---|
| 4 | 1 | |
| 583 | 90 | |
| - | - | |
| 5.2 | 0.0 | |
| 5 months ago | over 1 year ago | |
| Julia | Python | |
| MIT License | Apache License 2.0 |
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Tullio.jl
- A basic introduction to NumPy's einsum
- Generic GPU Kernels
-
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
einshape
-
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.
What are some alternatives?
Zygote.jl - 21st century AD
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
CUDA.jl - CUDA programming in Julia.
cadabra2 - A field-theory motivated approach to computer algebra.
ForwardDiff.jl - Forward Mode Automatic Differentiation for Julia
Einsum.jl - Einstein summation notation in Julia
TensorOperations.jl - Julia package for tensor contractions and related operations
einsum - Einstein Summation for Arrays in R
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