scikit-cuda
jittor
scikit-cuda | jittor | |
---|---|---|
1 | 4 | |
968 | 2,995 | |
- | - | |
2.5 | 7.6 | |
7 months ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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scikit-cuda
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GPU Based Kernel-PCA
I found this lovely repo -> https://github.com/lebedov/scikit-cuda
jittor
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VSL; Vlang's Scientific Library
Would it make sense to have a backend support for OpenXLA, Apache TVM, Jittor or other similar to get free GPU, TPU and other accelerators for free ?
- Jittor: High-performance deep learning framework based on JIT and meta-operators
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Tinygrad: A simple and powerful neural network framework
Very similar idea as Jittor, convolution definitely can be break down: https://github.com/Jittor/jittor/blob/master/python/jittor/n...
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How do I deal with ML models taking soooo long to train, when I have to optimize results?
-I've found JIT quite useful: https://github.com/Jittor/jittor
What are some alternatives?
cupy - NumPy & SciPy for GPU
Res2Net-PretrainedModels - (ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
cuml - cuML - RAPIDS Machine Learning Library
shumai - Fast Differentiable Tensor Library in JavaScript and TypeScript with Bun + Flashlight
PyCUDA - CUDA integration for Python, plus shiny features
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
pyopencl - OpenCL integration for Python, plus shiny features
vsl - V library to develop Artificial Intelligence and High-Performance Scientific Computations
kernel_tuner - Kernel Tuner
StylizedNeRF - [CVPR 2022] Code for StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D mutual learning
cusim - Superfast CUDA implementation of Word2Vec and Latent Dirichlet Allocation (LDA)
nnabla - Neural Network Libraries