Thrust VS Whisper

this is frankly starting to sound a lot like the ridiculous "blue bubbles" discourse.

AMD's products have generally failed to catch traction because their implementations are halfassed and buggy and incomplete (despite promising more features, these are often paper features or career-oriented development from now-departed developers). all of the same "developer B" stuff from openGL really applies to openCL as well.

http://richg42.blogspot.com/2014/05/the-truth-on-opengl-driv...

AMD has left a trail of abandoned code and disappointed developers in their wake. These two repos are the same thing for AMD's ecosystem and NVIDIA's ecosystem, how do you think the support story compares?

https://github.com/HSA-Libraries/Bolt

https://github.com/NVIDIA/thrust

in the last few years they have (once again) dumped everything and started over, ROCm supported essentially no consumer cards and rotated support rapidly even in the CDNA world. It offers no binary compatibility support story, it has to be compiled for specific chips within a generation, not even just "RDNA3" but "Navi 31 specifically". Etc etc. And nobody with consumer cards could access it until like, six months ago, and that still is only on windows, consumer cards are not even supported on linux (!).

https://geohot.github.io/blog/jekyll/update/2023/06/07/a-div...

This is on top of the actual problems that still remain, as geohot found out. Installing ROCm is a several-hour process that will involve debugging the platform just to get it to install, and then you will probably find that the actual code demos segfault when you run them.

AMD's development processes are not really open, and actual development is silo'd inside the company with quarterly code dumps outside. The current code is not guaranteed to run on the actual driver itself, they do not test it even in the supported configurations.

it hasn't got traction because it's a low-quality product and nobody can even access it and run it anyway.

For a higher level GPU interface, Thrust provides "standard library"-like functions that run in parallel on the GPU (Nvidia only)

For GPGPU, I like thrust. C++-idiomatic way of writing CUDA code, passing between host and device, etc.

Users should work with higher level primitives like tasks, parallel loops, asynchronous functions etc. Think TBB, Thrust, Taskflow, lparallel for CL, etc.

I've been using WhisperDesktop ( https://github.com/Const-me/Whisper ) with great success on a 3090 for fast & accurate transcription of often poor quality euro-english hours long multispeaker audio files. If there's an easy way to compare I'm certainly going to give this a try.

Why would you want OpenCL? Pretty sure D3D11 compute shaders gonna be adequate for a Torch backend, and they even work on Linux with Wine: https://github.com/Const-me/Whisper/issues/42 Native Vulkan compute shaders would be even better.

Why would you want unified address space? At least in my experience, it’s often too slow to be useful. DMA transfers (CopyResource in D3D11, copy command queue in D3D12, transfer queue in VK) are implemented by dedicated hardware inside GPUs, and are way more efficient.

https://github.com/ggerganov/whisper.cpp

https://github.com/Const-me/Whisper

I had fun with both of these. They will both do realtime transcription. Bit you will have to download the training data sets…

Gamers don’t care about FP64 performance, and it seems nVidia is using that for market segmentation. The FP64 performance for RTX 4090 is 1.142 TFlops, for RTX 3090 Ti 0.524 TFlops. AMD doesn’t do that, FP64 performance is consistently better there, and have been this way for quite a few years. For example, the figure for 3090 Ti (a $2000 card from 2022) is similar to Radeon RX Vega 56, a $400 card from 2017 which can do 0.518 TFlops.

And another thing: nVidia forbids usage of GeForce cards in data centers, while AMD allows that. I don’t know how specifically they define datacenter, whether it’s enforceable, or whether it’s tested in courts of various jurisdictions. I just don’t want to find out answers to these questions at the legal expenses of my employer. I believe they would prefer to not cut corners like that.

I think nVidia only beats AMD due to the ecosystem: for GPGPU that’s CUDA (and especially the included first-party libraries like BLAS, FFT, DNN and others), also due to the support in popular libraries like TensorFlow. However, it’s not that hard to ignore the ecosystem, and instead write some compute shaders in HLSL. Here’s a non-trivial open-source project unrelated to CAE, where I managed to do just that with decent results: https://github.com/Const-me/Whisper That software even works on Linux, probably due to Valve’s work on DXVK 2.0 (a compatibility layer which implements D3D11 on top of Vulkan).

Currently, I use a GUI for Whisper AI (https://github.com/Const-me/Whisper) to upload MP3s of interviews to get text transcripts. However, I'm hoping to find another tool that would recognize and split out the text per speaker.

Does such a thing exist?

I just used Whisper over the weekend to transcribe 5 hours of meeting, worked nicely and it can be run on a single GPU locally. https://github.com/ggerganov/whisper.cpp

There are a few wrappers available with GUI like https://github.com/Const-me/Whisper