openpbs
VkFFT
| openpbs | VkFFT | |
|---|---|---|
| 3 | 37 | |
| 673 | 1,443 | |
| 0.4% | - | |
| 7.2 | 8.1 | |
| 11 days ago | about 1 month ago | |
| C | C++ | |
| GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
openpbs
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How to Install OpenPBS v20.0.1 into Gentoo Linux
Following the Gentoo Linux styles, all software used this time are built and installed from the source codes. Installation of OpenPBS on other operating systems except Gentoo is described in openpbs/INSTALL on GitHub.
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A PBS question.
So the one in GitHub (https://github.com/openpbs/openpbs) is abandoned or still going on?
VkFFT
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[P] - VkFFT now supports quad precision (double-double) FFT computation on GPU
Hello, I am the creator of the VkFFT - GPU Fast Fourier Transform library for Vulkan/CUDA/HIP/OpenCL/Level Zero and Metal. In the latest update, I have added support for quad-precision double-double emulation for FFT calculation on most modern GPUs. I understand that modern ML is going in the opposite low-precision direction, but I still think that it may be useful to have this functionality at least for some prototyping and development of concepts.
- VkFFT now supports quad precision (double-double) FFT computation on GPU
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VkFFT: Vulkan/CUDA/Hip/OpenCL/Level Zero/Metal Fast Fourier Transform Library
Not quite what I asked for, but close enough for now...
https://github.com/DTolm/VkFFT/discussions/126
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Implementing complex numbers (and FFT) elegantly with just algebraic datatypes (no machine floats)
Source - I have made a somewhat functional programming-like FFT library (https://github.com/DTolm/VkFFT/tree/develop) which also operates on abstract data containers. Maybe it can be interesting to you from the algorithmic point of view.
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how does Vulkan compare to CUDA?
VkFFT is a use-case I've heard of where Vulkan-Compute is faster than its Cuda and OpenCL counter-part: https://github.com/DTolm/VkFFT
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VkFFT now supports Apple Metal API - M1 Pro GPU FFT benchmarking
Hello, I am the creator of the VkFFT - GPU Fast Fourier Transform library for Vulkan/CUDA/HIP/OpenCL and Level Zero. In the latest update, I have added support for Apple Metal API, which will allow VkFFT to run natively on modern Apple SoC. I have tested it on MacBook Pro with an M1 Pro 8c CPU/14c GPU SoC single precision on 1D batched FFT test of all systems from 2 to 4096. Achieved bandwidth is calculated as 2*system size divided by the time taken per FFT - minimum memory that has to be transferred between DRAM and GPU:
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Any good compute shader tutorials?
Another possible project to look at is https://github.com/DTolm/VkFFT
- VkFFT now supports Rader's algorithm - A100 and MI250 benchmarks: Part 2
- VkFFT now supports Rader's algorithm - A100 and MI250 benchmarks
What are some alternatives?
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