taichi

The creator is working here https://www.meshy.ai/ even before that I think they switched to a private fork as they were doing the bulk of the work. https://github.com/taichi-dev/taichi/discussions/8506 Assume all of this is wrong.

> Edit: Python has no JIT There are quite a few JITs: JIT-compiler for Python https://pypy.org/ Python enhancement proposal for JIT in CPython https://peps.python.org/pep-0744/ And there are several JIT-compilers for various subsets of Python, usually with focus on numerical code and often with GPU support, for example Numba https://numba.pydata.org/numba-doc/dev/user/jit.html Taichi Lang https://github.com/taichi-dev/taichi

Same here! Not a physics engine per se, but I've been eyeing Taichi Lang (https://github.com/taichi-dev/taichi) as a potential next stop for running this on a much larger scale. My assumption has been that any physics engine that does soft-body physics would work in this regard, just at a much higher sampling rate than one would normally use in a gaming scenario. This simulation is actually only running at 22050hz, rather than today's standard 44100hz sampling rate.

It is a nice physics engine, it uses Taichi (https://github.com/taichi-dev/taichi) to compile Python code to CUDA/GPU (similar to what Warp Sim does, https://github.com/NVIDIA/warp)

> What's Taichi's take on NVIDIA's Warp? > Overall the biggest distinction as of now is that Taichi operates at a slightly higher level. E.g. implict loop parallelization, high level spatial data structures, direct interops with torch, etc. > We are trying to implement support for lower level programming styles to accommodate such things as native intrinsics, but we do think of those as more advanced optimization techniques, and at the same time we strive for easier entry and usage for beginners or people not so used to CUDA's programming model – https://github.com/taichi-dev/taichi/discussions/8184

I was playing around with taichi a little bit for a project. Taichi lives in a similar space, but has more than an NVIDIA backend. But its development has stalled, so I’m considering switching to warp now. It’s quite frustrating that there’s seemingly no long-lived framework that allows me to write simple numba-like kernels and try them out in NVIDIA GPUs and Apple GPUs. Even with taichi, the Metal backend was definitely B-tier or lower: Not offering 64 bit ints, and randomly crashing/not compiling stuff. Here’s hoping that we’ll solve the GPU programming space in the next couple years, but after ~15 years or so of waiting, I’m no longer holding my breath. https://github.com/taichi-dev/taichi

The haughtiness is not for nothing. Since Dec 2023, they made a lame excuse that Pytorch didn't support 3.12: https://github.com/taichi-dev/taichi/issues/8365#issuecommen... Later, even when Pytorch added support for 3.12, nothing changed (so far) in Taichi.

Hn people are so haughty https://github.com/taichi-dev/taichi/pull/8522

ETH Zurich is using it for their physics sim courses, University of Utah is using it for simulations (SIGGRAPH 2022), OPPO (they make smart devices running Android), Kuaishou uses it for liquid and gas simulation on GPUs. Lots of GPU accelerated sim stuff. https://www.taichi-lang.org/ https://www.researchgate.net/publication/337118128_Taichi_a_... https://github.com/taichi-dev/taichi

Look at Taichi at Github. This library for Python seems not very popular and unaware. Maybe, because it is a Chinese development, but Taichi is simple and compiles directly down to kernels on CUDA, GPU, Metal, Vulkan and has batteries included. Beats the fastest Mojo implementation of the Mandelbrot set about 260 times faster. https://github.com/taichi-dev/taichi

There is a SDF renderer in Taichi Lang examples: https://github.com/taichi-dev/taichi/blob/master/python/taic... Not so short as OP's version(46 lines vs 171 lines), but it renders a nice looking image: https://github.com/taichi-dev/taichi-release-tests/blob/mast...