* 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.
* vulkan: Update topk_moe fusion to handle gpt's late softmax
Based on #16649.
* Add ggml_check_edges
* Add sync logging to show fusion effects
* handle clamp added in #16655
* Update ggml/src/ggml-impl.h
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* hexagon: remove dspqueue callbacks and do all read processing inplace
* hexagon: there is no need to ref/deref the buffers at this point
We're not going to release the buffers without flushing the session queue.
So there is no need to inc/dec the refcounts for every request.
We also don't need to include those bufs in the response.
* hexagon: bump the thread count in the adb wrapper scripts
We can use more CPU cores now that the dedicated dspqueue polling threads are not used (ie no contention).
Also enable more agressive polling for now since we still map Flash Attention (and a few other kernels) to
the CPU and those dspqueue threads were keeping the CPU cores are higher clock freqs.
* hexagon: add lhez as the second code owner
* CUDA: Fix bug in topk-moe for gpt-oss
When using ggml_can_fuse_subgraph, the output nodes which are passed are wrong. This causes `test-backend-ops` to still fuse ndoes (because the nodes are not used elsewhere in the graph),
but it actually doesn't fuse in the actual gpt-oss
* fix for qwen3 too
* change ifndef to ifdef
