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Nvidia Warp: A Python framework for high performance GPU simulation and graphics

(github.com)
490 points jarmitage | 1 comments | 14 Jun 24 13:28 UTC | HN request time: 0.208s | source
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w-m ◴[14 Jun 24 14:58 UTC] No.40681522[source]▶
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

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szvsw ◴[14 Jun 24 15:51 UTC] No.40681931[source]▶
I’ve been in love with Taichi for about a year now. Where’s the news source on development being stalled? It seemed like things were moving along at pace last summer and fall at least if I recall correctly.
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w-m ◴[14 Jun 24 15:58 UTC] No.40681980[source]▶
https://github.com/taichi-dev/taichi/discussions/8506
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1. szvsw ◴[14 Jun 24 16:17 UTC] No.40682128[source]▶
Ha, interesting timing, last post 6Hr ago. Sounds like they are dogfooding it at least which is good. And I would agree with the assessment that 1.x is fairly feature complete, at least from my experience using it (scientific computing). And good to hear that they are planning on pushing support patches for eg python 3.12 cuda 12 etc