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vuda
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VkFFT discussion
VkFFT reviews and mentions
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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
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A note from our sponsor - InfluxDB
influxdata.com | 19 Apr 2025
Stats
DTolm/VkFFT is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of VkFFT is C++.