Pre-release / continuous build: this is an experimental build, not a stable release.
llama: fix k-pool scatter data race on shared sequences (#29994) * llama: re-pool each shared k-pool rep once With shared cells every pool is re-pooled, and since the pooled keys are always scattered, the pools a seq_cp shares between sequences wrote the same rep row from several scatter entries, a data race on the CPU backend. Mark each rep once: the sharing sequences read the same row through pool_cells. * llama: assert whole-sequence seq_cp in the hybrid idx memory The recurrent state is always copied whole whatever the range, and a k-pool cell shared by a partial copy could carry two pool groupings with a single pooled row. Every caller copies whole sequences, so reject partial ranges instead of supporting them. * llama: drop the k-pool cache_safe mode With whole-sequence seq_cp, sequences sharing cells share their pools too, so the pooled row of a shared rep is valid for all of them. Mark each rep once in every ubatch instead of re-pooling everything while cells are shared, which removes the sharing scan and the stale-all workarounds in seq_rm, state_read and state_drop. seq_cp now only stales the destination.Website: - https://llama.app
Attestations: - https://github.com/ggml-org/llama.cpp/attestations/53070668
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