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Top 20 gpu-programming 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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scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
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OpenCL-Wrapper
OpenCL is the most powerful programming language ever created. Yet the OpenCL C++ bindings are cumbersome and the code overhead prevents many people from getting started. I created this lightweight OpenCL-Wrapper to greatly simplify OpenCL software development with C++ while keeping functionality and performance.
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VectorVisor
VectorVisor is a vectorizing binary translator for GPUs, designed to make it easy to run many copies of a single-threaded WebAssembly program in parallel using GPUs
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simba-ps
Fast deterministic all-Python Lennard-Jones particle simulator that utilizes Numba for GPU-accelerated computation.
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ConwaysGameOfLife
A super fast GPU and more specifically WebGL based version of Conway's game of life. (by RandomGamingDev)
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taichi – Productive, portable, and performant GPU programming in Python
https://github.com/exaloop/codon/blob/develop/LICENSE
Here are some others: https://github.com/search?q=%22Business+Source+License%22+%2...
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)
For parallel programming nowadays, personally I reach for C++ Taskflow when I really care about performance, or a mix of core.async and running multiple load balanced instances when I’m doing more traditional web backend stuff in Clojure.
Sounds cool, but this requires yet another language to learn[0]. As someone who only has limited knowledge in this space, could someone tell me how comparable is the compute functionality of rust-gpu[1], where I can just write rust?
[0] https://github.com/Hugobros3/shady#language-syntax
[1] https://github.com/EmbarkStudios/rust-gpu
https://github.com/topics/datalog?l=rust ... Cozo, Crepe
Crepe: https://github.com/ekzhang/crepe :
> Crepe is a library that allows you to write declarative logic programs in Rust, with a Datalog-like syntax. It provides a procedural macro that generates efficient, safe code and interoperates seamlessly with Rust programs.
Looks like there's not yet a Python grammar for the treeedb tree-sitter: https://github.com/langston-barrett/treeedb :
> Generate Soufflé Datalog types, relations, and facts that represent ASTs from a variety of programming languages.
Looks like roxi supports n3, which adds `=>` "implies" to the Turtle lightweight RDF representation: https://github.com/pbonte/roxi
FWIW rdflib/owl-rl: https://owl-rl.readthedocs.io/en/latest/owlrl.html :
> simple forward chaining rules are used to extend (recursively) the incoming graph with all triples that the rule sets permit (ie, the “deductive closure” of the graph is computed).
ForwardChainingStore and BackwardChainingStore implementations w/ rdflib in Python: https://github.com/RDFLib/FuXi/issues/15
Fast CUDA hashmaps
Gdlog is built on CuCollections.
GPU HashMap libs to benchmark: Warpcore, CuCollections,
https://github.com/NVIDIA/cuCollections
https://github.com/NVIDIA/cccl
https://github.com/sleeepyjack/warpcore
/? Rocm HashMap
DeMoriarty/DOKsparse:
FWIW also taichi is quite popular in python and seems has some javascript related implementation (I haven't used it though), taichi.js [0]
[0] https://github.com/AmesingFlank/taichi.js
Project mention: What 8x AMD Instinct MI200 GPUs can do with a combined 512GB VRAM: Bell 222 Helicopter in FluidX3D CFD - 10 Billion Cells, 75k Time Steps, 71TB vizualized - 6.4 hours compute+rendering with OpenCL | /r/pcmasterrace | 2023-06-24In case you go with OpenCL, start here: https://github.com/ProjectPhysX/OpenCL-Wrapper
Project mention: Simba: A Python GPU-accelerated particle simulator | news.ycombinator.com | 2023-07-20
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-programming related posts
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Taichi: Accessible GPU programming, embedded in Python
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Parallelizing WebAssembly Execution on GPUs
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VectorVisor --- Accelerate (mostly) unmodified WebAssembly programs using GPUs (Made with Rust)
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What's the coolest Rust project you've seen that made you go, 'Wow, I didn't know Rust could do that!'?
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[rust-gpu] How do I run/build my own shaders locally?
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Posh: Type-Safe Graphics Programming in Rust
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Introducing posh: Type-Safe Graphics Programming in Rust
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Index
What are some of the best open-source gpu-programming projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | taichi | 24,779 |
| 2 | codon | 13,840 |
| 3 | scalene | 11,174 |
| 4 | Taskflow | 9,552 |
| 5 | rust-gpu | 6,952 |
| 6 | Emu | 1,590 |
| 7 | geomstats | 1,150 |
| 8 | cccl | 771 |
| 9 | taichi.js | 415 |
| 10 | vuh | 340 |
| 11 | ministark | 323 |
| 12 | Gpufit | 300 |
| 13 | OpenCL-Wrapper | 257 |
| 14 | Webgl-Erosion | 215 |
| 15 | moonlibs | 204 |
| 16 | VectorVisor | 137 |
| 17 | simba-ps | 69 |
| 18 | tensorexperiments | 36 |
| 19 | gpu-desktop-calculator | 7 |
| 20 | ConwaysGameOfLife | 0 |
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