AMD GPU Inference
71–80 of 102 posts
Re: AMD GPU Inference
#72On Ubuntu 24.04 (and Debian Unstable¹), the OS-provided packages should be able to get llama.cpp running on ROCm on just about any discrete AMD GPU from Vega onwards²³⁴. No docker or HSA_OVERRIDE_GFX_VERSION required. The performance might not be ideal in every case⁵, but I've tested a wide variety of cards: # install dependencies sudo apt -y update sudo apt -y upgrade sudo apt -y install git wget hipcc libhipblas-de…
Re: AMD GPU Inference
#73What's the best bang-for-your-buck AMD GPU these days? I just bought 2 used 3090s for $750ish refurb'd on eBay. Curious what others are using for running LLMs locally.
Personal experience: It's not even worth it. AMD (i)GPU breaks with every pytorch, ROCm, xformers, or ollama updates. You'll sleep more compfortably at night.
Re: AMD GPU Inference
#74What's the best bang-for-your-buck AMD GPU these days? I just bought 2 used 3090s for $750ish refurb'd on eBay. Curious what others are using for running LLMs locally.
Re: AMD GPU Inference
#75Earlier quoted context omitted.
I suspected that, but any binaries being that large just seems wrong, I mean the whole thing is 35 time larger than my entire OS install. Do you know what is included in ROCm that could be so big? Does it include training datasets or something?
Here's the big files in my /opt/rocm/lib which is most of it: 4.8G hipblaslt 1.6G libdevice_conv_operations.a 2.0G libdevice_gemm_operations.a 1.4G libMIOpen.so.1.0.60200 1.1G librocblas.so.4.2.60200 1.6G librocsolver.so.0.2.60200 1.4G librocsparse.so.1.0.60200 1.5G llvm 3.5G rocblas 2.0G rocfft The biggest one just to pick on one is hipblaslt is "a library that provides general matrix-matrix operations. It has a fle…
Re: AMD GPU Inference
#76On Ubuntu 24.04 (and Debian Unstable¹), the OS-provided packages should be able to get llama.cpp running on ROCm on just about any discrete AMD GPU from Vega onwards²³⁴. No docker or HSA_OVERRIDE_GFX_VERSION required. The performance might not be ideal in every case⁵, but I've tested a wide variety of cards: # install dependencies sudo apt -y update sudo apt -y upgrade sudo apt -y install git wget hipcc libhipblas-de…
are there AMD cards with more than 24GB VRAM on the market right now at consumer friendly prices?
Re: AMD GPU Inference
#77Re: AMD GPU Inference
#78The rise of generated slop ml libraries is staggering. This library is 50% print statements. And where it does branch, it doesn't even need to. Defines two environment variables and sets two flags on torch.
Expectation management is a huge part of any team/organization, I think
Re: AMD GPU Inference
#79Earlier quoted context omitted.
related: https://www.nonbios.ai/post/deploying-large-405b-models-in-f... tldr: uses the latest rocm 6.2 to run full precision inference for llama 405b on a single node 8 x MI300x AMD GPU How mature do you think Rocm 6.2-AMD stack is compared to Nvidia ?
this uses vllm?
Re: AMD GPU Inference
#80On Ubuntu 24.04 (and Debian Unstable¹), the OS-provided packages should be able to get llama.cpp running on ROCm on just about any discrete AMD GPU from Vega onwards²³⁴. No docker or HSA_OVERRIDE_GFX_VERSION required. The performance might not be ideal in every case⁵, but I've tested a wide variety of cards: # install dependencies sudo apt -y update sudo apt -y upgrade sudo apt -y install git wget hipcc libhipblas-de…
are there AMD cards with more than 24GB VRAM on the market right now at consumer friendly prices?
$3,600 - 61 TFLOPS - AMD Radeon Pro W7900
$4,200 - 38.7 TFLOPS - NVidia RTX A6000 48GB Ampere
$7,200 - 91.1 TFLOPS - NVidia RTX A6000 48GB Ada