Nvidia adds native Python support to CUDA
Link: https://thenewstack.io/nvidia-finally-adds-native-python-support-to-cuda/
Discussion: https://news.ycombinator.com/item?id=43581584
NVIDIA finally joins the 21st century by adding #Python support to #CUDA, because who needs cutting-edge tech when you can just catch up with 2006? 
https://thenewstack.io/nvidia-finally-adds-native-python-support-to-cuda/ #NVIDIA #TheNewStack #TechNews #Subscribe #HackerNews #ngated
ffs, why does their docker only support Navi 31 and not Navi 32? 
https://hub.docker.com/r/rocm/pytorch
I just wish both #Nvidia and #AMD would stop with that whole licensing bullshit around #CUDA and #ROCm and just include that damn stuff in the default driver.
I just want to run #Codestral on my local machine so I can use it with non-public code. Will be troublesome enough to cram it into 16gb VRAM. 
#computer #Linux #AI
Ported https://salykova.github.io/sgemm-gpu to Vulkan (nice article!) 
it's 2x slower than Cuda. That one was tricky to port, (e.g. need to alias shared buffer to allow LDS/STS.128), half of it with AI, 2nd half going over lines 1-by-1
Ported the Kernel 5 from https://seb-v.github.io/optimization/update/2025/01/20/Fast-GPU-Matrix-multiplication.html to Vulkan 
It's only 15% slower than Cuda (and it works on AMD)
In both cases, it's quite difficult to reason about SPIR-V 
Digging deeper 
wasmVision 0.3.0 is out! We have some exiting new features for you such as MCP server support, and experimental GPU acceleration for vision models. Performance and stability improvements too. Go get it right now!
#wasm #computervision #opencv #golang #tinygo #rust #clang #mcp #cuda
https://github.com/wasmvision/wasmvision/releases/tag/v0.3.0
One of the best interviews on AI and GPUs I've every seen was posted earlier today. Jensen Huang is really super smart in my opinion, and I think this interview is definitely worth watching. I can understand how it was a person like him who turned NVIDIA into a company with a market cap more than 1 trillion USD.
Jensen Huang on GPUs - Computerphile
https://www.youtube.com/watch?v=G6R7UOFx1bw
NVIDIA GeForce RTX 5060 e 5060 Ti: arrivo imminente
#Aprile2025 #Componenti #CUDA #Gaming #GDDR7 #GeForce #GPU #Hardware #Leak #Notizie #Novità #NVIDIA #NVIDIARTX #PC #RTX5060 #RTX5060Ti #Rumors #SchedeGrafiche #SchedeVideo #TechNews #Tecnologia
https://www.ceotech.it/nvidia-geforce-rtx-5060-e-5060-ti-arrivo-imminente/
I had hoped that DIA-NN 2.02 could be accelerated by either ATI or nVidia GPUs, but I have tried with both types of cards to no avail.
#bioinformatic #proteomics #OpenCL #CUDA
Is there any difference between computing AI workloads in Vulkan, OpenCL and CUDA?
I know that some people say that NVIDIA doesn't support (quite well) OpenCL or Vulkan, performance is achieved by using CUDA. But what is the story for other vendors (Intel, AMD, QualComm, Apple) ?
Just got my RSS reader YOShInOn building with uv and running under WSL2 with the Cuda libraries, despite a slight version mismatch... All I gotta do is switch it from arangodb (terrible license) to postgres, and it might have a future... With sentence_transformers running under WSL2 I might even be able to deduplicate the million images in my Fraxinus image sorter
https://ashwanirathee.com/blog/2025/sort2/ #parallelcomputing #sortingalgorithms #techhumor #codinglife #HackerNews #ngated
Even now, Thrust as a dependency is one of the main reason why we have a #CUDA backend, a #HIP / #ROCm backend and a pure #CPU backend in #GPUSPH, but not a #SYCL or #OneAPI backend (which would allow us to extend hardware support to #Intel GPUs). <https://doi.org/10.1002/cpe.8313>
This is also one of the reason why we implemented our own #BLAS routines when we introduced the semi-implicit integrator. A side-effect of this choice is that it allowed us to develop the improved #BiCGSTAB that I've had the opportunity to mention before <https://doi.org/10.1016/j.jcp.2022.111413>. Sometimes I do wonder if it would be appropriate to “excorporate” it into its own library for general use, since it's something that would benefit others. OTOH, this one was developed specifically for GPUSPH and it's tightly integrated with the rest of it (including its support for multi-GPU), and refactoring to turn it into a library like cuBLAS is
a. too much effort
b. probably not worth it.
Again, following @eniko's original thread, it's really not that hard to roll your own, and probably less time consuming than trying to wrangle your way through an API that may or may not fit your needs.
6/
WgPy: GPU-accelerated NumPy-like array library for web browsers
AMD YOLO: because why not base your entire #business #strategy on a meme? 
https://geohot.github.io//blog/jekyll/update/2025/03/08/AMD-YOLO.html #AMD #YOLO #meme #CUDA #competition #HackerNews #ngated
Hot Aisle's 8x AMD #MI300X server is the fastest computer I've ever tested in #FluidX3D #CFD, achieving a peak #LBM performance of 205 GLUPs/s, and a combined VRAM bandwidth of 23 TB/s. 
The #RTX 5090 looks like a toy in comparison.
MI300X beats even Nvidia's GH200 94GB. This marks a very fascinating inflection point in #GPGPU: #CUDA is not the performance leader anymore. 
You need a cross-vendor language like #OpenCL to leverage its power.
FluidX3D on #GitHub: https://github.com/ProjectPhysX/FluidX3D
