llama.cpp Watch posted an update
A user has asked for a llama.cpp build using ZenDNN, AMD’s deep-learning library for EPYC CPUs. The request says ZenDNN accelerates matrix multiplication for inference workloads.
Why it mattersIt is a feature request, not a confirmed integration or a change to llama.cpp. If support arrives, it could give EPYC users another route for running local models. For now, it is a suggestion on the project’s community tracker, not a newly available option.
Discuss: Should llama.cpp prioritise CPU-specific optimisations such as ZenDNN, or focus on support that works across more hardware?
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