So I've installed RipX Daw and checked the "About" section on the software and I see that it says "Ripper GPU Hardware Acceleration Not Available".
My Hardware:
MB: Naf93-Q77
CPU: I7-3770k
RAM: 32 GB DDR3
GPU: GTX 980 Ti - (2816 CUDA Cores)
OS: WIndows 10 Pro 22H2 with latest updates as of this post.
So naturally I checked here and found out that I needed the NVIDIA CUDA Toolkit 11, SO I installed it (3 times!)
2nd time around on installing the CUDA Toolkit, I noticed it said certain components of the toolkit were not going to be installed because I didn't have VISUAL STUDIO installed (Or certain components I guess?) So I hit continue anyway. STILL NO hardware acceleration.
3rd time install of CUDA Toolkit and I went and downloaded and installed VISUAL STUDIO, then again installed the CUDA toolkit and still NO HARDWARE acceleration. Still noticed it said that there was no VISUAL STUDIO and that certain components would not install, but I continued.
I scoured the internet and found an AIO Visual Studio install from different years (Which is what the toolkit specified 2015, 2017, 2019) so I installed all of them just in case. REINSTALLED CUDA toolkit 11, and.. NOTHING!!
Still says "Ripper GPU Hardware Acceleration Not Available"/
WHAT IS GOING ON???
What exactly are the requirements on ones computer for this to run properly? (though I could still rip, I would like to know how much faster it is with and without hardware acceleration since I am considering upgrading my GPU)
And why the hell is your installer so SLOW AND use so much resources?
This is what Nvidia Toolkit 11 says on installation "
(Though I have installed VS from the link provided on the toolkit and have reinstalled it several times.)
@alxjm69 I'm afraid RipX DAW's GPU hardware acceleration requires a GPU with at least 8GB of VRAM and your GPU only has 6GB of VRAM.
It isn’t necessary to install Visual Studio. Upon receiving the message that says, 'No supported version of Visual Studio was found', you should check 'I understand' and click 'Next'.
Where did you see that the GTX 980 Ti is supported for the GPU hardware acceleration? The list of supported GPUs on the following page of our website hasn’t changed since at least as far back as December 2023.
@dave You guys HAD listed the GTX as a supported card (Months ago and maybe even last year when I first looked into your program), and looking at the site, it doesn't even say a "minimum" of video memory.
CUDA (computer power) should work with any amount of RAM on the cards.
Had the GTX NOT been listed, I wouldn't have bought your program and wouldn't have needed to check your specs if I knew it would change. Cousre, I still think you have a great product.
@dave Anyway... is a 3060 or 3060 ti supported or ONLY the ones listed on your site?
Was thinking of getting a 1 slot workstation card but you guys don't have support for it?
@alxjm69 I've checked with our web development team and they have confirmed that the GTX 980 has never been listed on our website. (It's also possible to check this by viewing old versions of our website with the Internet Archive's WayBack Machine.)
It is a requirement of RipX DAW that the GPU have at least 8GB of VRAM.
@alxjm69 The list on our website is not exhaustive and it is not possible for us to test with every GPU. However, from looking at the specs of the GeForce RTX 3060 and the GeForce RTX 3060 Ti, the GPU hardware acceleration should work with either one of those.
@dave I'm aware you're the CEO/Founder so,.. if I were to mod the GTX 980 to 8GB or more of RAM, then the program would work with hardware acceleration?
Does the software look for the amount of ram the video card has or do you guys have black/white list of GPUs that the installer looks for?
@alxjm69 I'm not the CEO/founder - we just have the same surname. I've checked with our development team and they've advised as follows:
It looks for the amount of RAM. However, it also needs to have a ‘compute capability’ of at least 6.1 (which all the 8GB cards seem to have).
Unfortunately, the GTX 980 has a compute capability of 5.2 according to this table:
And is that value assigned by some INF file from the rippx software, and if so would I be able to modify it? Simply asking because it would still be able to work just albeit slower.
The most important thing for me would be to use my existing video card even though it takes up two slots, or get a one slot card, and yet I also would like to know how much of a difference in terms of percentage each card contributes.
@dave OK... so digging into how RipsX works, you guys use DEMUCS (Open Source) and from the original owner/creatpr of the program on Github, he says one can use a GPU with as little as 3GB (would be slower as I mentioned)..
From the GitHub page:
Memory requirements for GPU acceleration
If you want to use GPU acceleration, you will need at least 3GB of RAM on your GPU for demucs. However, about 7GB of RAM will be required if you use the default arguments. Add --segment SEGMENT to change size of each split. If you only have 3GB memory, set SEGMENT to 8 (though quality may be worse if this argument is too small). Creating an environment variable PYTORCH_NO_CUDA_MEMORY_CACHING=1 can help users with even smaller RAM such as 2GB (I separated a track that is 4 minutes but only 1.5GB is used), but this would make the separation slower.
If you do not have enough memory on your GPU, simply add -d cpu to the command line to use the CPU. With Demucs, processing time should be roughly equal to 1.5 times the duration of the track."
So let's make this happen so users don't have to upgrade unless they REALLY NEED to and can AFFORD it.
@alxjm69 The compute capability refers to the available instruction set on the chip as well as the memory, which is required for the version of CUDA we need to link to. It was very difficult and time consuming to get this to work at all and I’m afraid it’s currently not on our roadmap to support older GPUs.
In order for RipX DAW to use GPU hardware acceleration, CUDA Toolkit and necessary Visual Studio components must be installed correctly. In your case, the problem is most likely due to the lack of Visual Studio elements required for CUDA to work correctly. Make sure you have a full version of Visual Studio with the required C++ extensions (2015, 2017, 2019) installed. Also, make sure your video card and drivers are fully compatible with CUDA Toolkit 11. It worked for me and my games got better performance.
