LocalLLaMA
Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.
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Is BLAS faster with CPU only than Vulkan with CPU+iGPU? After failing to make work the SYCL backend in llama.cpp apparently because of a Debian driver issue I ended up using the Vulkan backend but after many tests offloadding to the iGPU doesn't seem to make much difference.
Uh, that's a complicated question. I don't know whether BLAS or Vulkan or SyCL are faster on an iGPU. I think I read many different takes on that. And I suppose it probably changed since I last tested it. People are optimizing the code all the time and it probably also depends on the processor generation and things like that. All I can say setting up SyCL is a hassle and requires like 10GB of development libraries. And I didn't see any noticeable improvement in speed. Either I did something wrong or it's not worth it on my computer. And Vulkan made everything slower on my 8th generation laptop's iGPU. But I'm not sure if that applies generally. But I'm currently sticking to the default backend, I believe that's BLAS. But again on KoboldCPP they replaced OpenBLAS with NoBLAS(?) recently and I haven't kept up to date and it's just too many options... ๐ I don't have any good advice. Maybe try all the options and see which is the fastest... Seems to me using the iGPU likely makes it slower, not faster.