DALI
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications. (by NVIDIA)
executorch
On-device AI across mobile, embedded and edge for PyTorch (by pytorch)
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| DALI | executorch | |
|---|---|---|
| 5 | 2 | |
| 4,914 | 710 | |
| 2.1% | 13.1% | |
| 9.6 | 10.0 | |
| 3 days ago | 4 days ago | |
| C++ | C++ | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
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.
DALI
Posts with mentions or reviews of DALI.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-15.
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[D] Will data augmentations work faster on TPUs?
Another option is DALI https://github.com/NVIDIA/DALI For my project while training EfficientNet2, it was a game changer. But it a way harder to implement in code than TorchVision or Kornia.
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DirectStorage - Loading data to GPU *directly* from the SSD drive, almost without using CPU
Check out https://github.com/nvidia/DALI
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mmap_ninja: Speedup your training dramatically by using memory-mapped files for your dataset
Small question if you are using GPU: How to this compare to GPUDirect Storage from Nvidia? can you have even more speedup by using both? I never toy with it, but the DALI project from Nvidia seem to tackle the same data loading problem.
- [D] Efficiently loading videos in PyTorch without extracting frames
executorch
Posts with mentions or reviews of executorch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-10-17.
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ExecuTorch: Enabling On-Device interference for embedded devices
Yes ExecuTorch is currently targeted at Edge devices. The runtime is written in C++ with 50KB binary size (without kernels) and should run in most of platforms. You are right that we have not integrated to Nvidia backend yet. Have you tried torch.compile() in PyTorch 2.0? It would do the Nvidia optimization for you without Torchscript. If you have specific binary size or edge specific request, feel free to file issues in https://github.com/pytorch/executorch/issues
What are some alternatives?
When comparing DALI and executorch you can also consider the following projects:
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
dfdx - Deep learning in Rust, with shape checked tensors and neural networks
Blurry - Blurry is an easy blur library for Android
MegEngine - MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架
vision - Datasets, Transforms and Models specific to Computer Vision
candle - Minimalist ML framework for Rust
DREAMPlace - Deep learning toolkit-enabled VLSI placement
llama - Inference code for Llama models
Daisykit - Daisykit is an easy AI toolkit with face mask detection, pose detection, background matting, barcode detection, and more. With Daisykit, you don't need AI knowledge to build AI software.
ocaml-torch - OCaml bindings for PyTorch