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Top 23 GPU Open-Source Projects
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Deeplearning4j
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
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FanControl.Releases
This is the release repository for Fan Control, a highly customizable fan controlling software for Windows.
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scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
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john
John the Ripper jumbo - advanced offline password cracker, which supports hundreds of hash and cipher types, and runs on many operating systems, CPUs, GPUs, and even some FPGAs
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ImageAI
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
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catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
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SaaSHub
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TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
It's opinionated, which comes with upsides and downsides. I won't blame the maintainer to keep things focused, feature creep (even for worthy features) can kill a FOSS project.
Another example is sixel support, there's a fork where it all works but is not sufficiently "proven" (code quality just as well as sixel being the best fit for the problem)
https://github.com/alacritty/alacritty/pull/4763#issuecommen...
It may be annoying but I get the reasoning, and there are other terminals.
Project mention: Can we discuss MLOps, Deployment, Optimizations, and Speed? | /r/LocalLLaMA | 2023-12-06DeepSpeed can handle parallelism concerns, and even offload data/model to RAM, or even NVMe (!?) . I'm surprised I don't see this project used more.
taichi – Productive, portable, and performant GPU programming in Python
Project mention: Nvtop: Linux Task Monitor for Nvidia, AMD and Intel GPUs | news.ycombinator.com | 2024-03-12its not a terminal app like bottom or nvtop but I use https://github.com/exelban/stats and it has iGPU stats
You might already be familiar, but a GPU.js backend can provide some speedups via good old WebGL -- no need for WebGPU just yet!
[0]: https://github.com/gpujs/gpu.js/
Project mention: That is some extremely impressive water physics, especialy for a place you only visit once. How did they do it? (MAJOR SPOILERS FOR 4.2 WORLD QUEST) | /r/Genshin_Impact | 2023-12-02It kinda reminds me of this fluid simulation website. The site is about a computer graphics technique that simulates the motion and appearance of fluids such as water, smoke or fire. You can use your mouse to move around the screen to see the simulation, also can change how the fluid simulation works by adjusting the sliders in the control panel next to it.
See also https://github.com/unifyai/ivy which I have not tried but seems along the lines of what you are describing, working with all the major frameworks
You don't really need PID, just a decent fan curve with https://github.com/Rem0o/FanControl.Releases
- have a “graphical” user interface: https://github.com/neovide/neovide
I collected a list of profilers (also memory profilers, also specifically for Python) here: https://github.com/albertz/wiki/blob/master/profiling.md
Currently I actually need a Python memory profiler, because I want to figure out whether there is some memory leak in my application (PyTorch based training script), and where exactly (in this case, it's not a problem of GPU memory, but CPU memory).
I tried Scalene (https://github.com/plasma-umass/scalene), which seems to be powerful, but somehow the output it gives me is not useful at all? It doesn't really give me a flamegraph, or a list of the top lines with memory allocations, but instead it gives me a listing of all source code lines, and prints some (very sparse) information on each line. So I need to search through that listing now by hand to find the spots? Maybe I just don't know how to use it properly.
I tried Memray, but first ran into an issue (https://github.com/bloomberg/memray/issues/212), but after using some workaround, it worked now. I get a flamegraph out, but it doesn't really seem accurate? After a while, there don't seem to be any new memory allocations at all anymore, and I don't quite trust that this is correct.
There is also Austin (https://github.com/P403n1x87/austin), which I also wanted to try (have not yet).
Somehow this experience so far was very disappointing.
(Side node, I debugged some very strange memory allocation behavior of Python before, where all local variables were kept around after an exception, even though I made sure there is no reference anymore to the exception object, to the traceback, etc, and I even called frame.clear() for all frames to really clear it. It turns out, frame.f_locals will create another copy of all the local variables, and the exception object and all the locals in the other frame still stay alive until you access frame.f_locals again. At that point, it will sync the f_locals again with the real (fast) locals, and then it can finally free everything. It was quite annoying to find the source of this problem and to find workarounds for it. https://github.com/python/cpython/issues/113939)
Yes, this is coming! Myself and others at OctoML and in the TVM community are actively working on multi-gpu support in the compiler and runtime. Here are some of the merged and active PRs on the multi-GPU (multi-device) roadmap:
Support in TVM’s graph IR (Relax) - https://github.com/apache/tvm/pull/15447
Project mention: GPU Compute in the Browser at the Speed of Native: WebGPU Marching Cubes | news.ycombinator.com | 2024-04-23Oh look it's subgroup support landing last week: https://github.com/gfx-rs/wgpu/pull/5301
Project mention: Does anyone else agree that the links to the latest development version of Open3D don't work? | /r/cscareerquestions | 2023-07-10I was going to file a bug about another issue, but I have to download the development version. This is why I want this solved quickly. None of the links seem to work: https://github.com/isl-org/Open3D/issues/6259
John The Ripper
Hi. I want to implement an image server similar to Photoprism using ImageAI to tag images based on objects and context. However I don't want to spend to much time working on the frontend, at first I were thinking about using Danbooru and use Flexbooru or the web interface on my phone. But it doesn't have any encryption or password protection (since the purpose of it is to be used as a public image board).
Project mention: CatBoost: Open-source gradient boosting library | news.ycombinator.com | 2024-03-05
Project mention: Nvtop: Linux Task Monitor for Nvidia, AMD and Intel GPUs | news.ycombinator.com | 2024-03-12
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
GPU related posts
- Tiny GPU: A minimal GPU implementation in Verilog
- Graph Data Fits in Memory
- Tinygrad: Hacked 4090 driver to enable P2P
- Deep Learning in JavaScript
- Deeplearning4j Suite Overview
- FluidX3D
- DCompute: Native execution of D on GPUs and other Accelerators
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A note from our sponsor - InfluxDB
www.influxdata.com | 25 Apr 2024
Index
What are some of the best open-source GPU projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | Pytorch | 77,783 |
| 2 | alacritty | 52,639 |
| 3 | DeepSpeed | 32,550 |
| 4 | fastai | 25,577 |
| 5 | taichi | 24,760 |
| 6 | stats | 22,032 |
| 7 | gpu.js | 14,953 |
| 8 | WebGL-Fluid-Simulation | 14,234 |
| 9 | ivy | 14,022 |
| 10 | Deeplearning4j | 13,424 |
| 11 | FanControl.Releases | 12,476 |
| 12 | neovide | 11,897 |
| 13 | scalene | 11,163 |
| 14 | tvm | 11,156 |
| 15 | wgpu | 10,910 |
| 16 | Open3D | 10,485 |
| 17 | john | 9,267 |
| 18 | pycaret | 8,406 |
| 19 | ImageAI | 8,383 |
| 20 | cupy | 7,774 |
| 21 | catboost | 7,744 |
| 22 | AlphaPose | 7,716 |
| 23 | nvtop | 7,365 |
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