* webui: recognize AsciiDoc files as valid text files
* webui: add an updated static webui build
* webui: add the updated dependency list
* webui: re-add an updated static webui build
This also reverts commit 742dbb8379.
* vulkan: fuse mul_mat+add and mul_mat_id+add_id
The fusion is only applied for the mat-vec mul paths.
* Apply suggestions from code review
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* fix 32b build
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Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* CUDA: Remove unneded bias/gate dims in fused mmvq
Pointed out
[here](https://github.com/ggml-org/llama.cpp/pull/16847#discussion_r2476798989)
that only a single value is needed per target col per thread
* Apply suggestions from code review
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Fix "Error 991-D: extra braces are nonstandard" during compilation
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Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* CUDA: Volta tensor core support for MMF
* more generic checks for hardware support
* Update ggml/src/ggml-cuda/mmf.cuh
Co-authored-by: Aman Gupta <amangupta052@gmail.com>
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Co-authored-by: Aman Gupta <amangupta052@gmail.com>
* Experimenting crash fix
* added assert for aborting and fixed comment
* changed to check if a pipeline is empty or not
* Moved function in class definition
* replaced with is_empty
* Modified is_empty to check only unaligned pipelines
* respect input size when getting/setting tensor data
allows partial repacking/copying when get tensor size is smaller than the actual tensor
* Removed duplicate repack_mxfp4_mxfp4x4x2 function
* Added GGUF mappings for CogVLM model
* Add tensor mapping for CogVLM visual encoder
* Add CogVLM to conversion script, no vision part yet
* Added CogVLM vision model to conversion script
* Add graph for CogVLM CLIP model
* Add graph for CogVLM
* Fixes for CogVLM. Now compiles.
* Model now runs
* Fixes for cogvlm graph
* Account for graph context change after rebase
* Changes for whitespace
* Changes in convert script according to comments
* Switch CogVLM LLM graph to merged QKV tensor
* Use rope_type variable instead of direct definition
* Change CogVLM CLIP encoder to use SWIGLU
* Switch CogVLM CLIP to use merged QKV
* Apply rebase edits and remove ggml_cont call that is now unnecessary
* clean up
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Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
This is realised by loading them into registers before computation of
the dot-product, effectively batching them together with said
dot-product. As a lot of threads are alive here, the warp scheduler has
enough threads available to effectively hide the cost of additionally
loading those two floats.
This pattern appears in a lot of models, the rope operation is applied right
before storing into the KV cache (usually on the K tensor).
Add a path to some of the rope shaders that computes the destination address
based on the set_rows tensor. Compile variants of the shader with D_TYPE of
f16 (the usual KV cache type).
Add a src3 operand to ggml_vk_op_f32 - sometimes rope uses three srcs and needs
the fourth for the row indices.
Add fused_ops_write_mask to indicate which intermediate tensors need to write
their results to memory. Skipping writing the roped K value helps to allow more
nodes to run concurrently.
Add logic to ggml_vk_graph_optimize to make ROPE+VIEW+SET_ROWS consecutive. It
rarely starts out that way in the graph.
Add new backend tests.
