* vulkan: don't hold the device mutex while compiling pipelines
We need to hold a lock while we traverse all pipelines and lazily initialize
them, but we don't need to hold it while the pipeline is being compiled. And
it doesn't need to be the same lock as the device mutex. We call load_shaders
each time a pipeline is needed, so we only need to compile that one pipeline
(and, for example, don't want to end up compiling a pipeline that another
thread should be compiling).
* remove 'needed'
Q2_K/Q3_K/Q6_K do much better when using MMVQ on Intel BMG even
though they're only 2-byte aligned, and Q3_K still wins on
NVIDIA as well.
mesa isn't all that great at coalescing back-to-back loads from
alternating arrays, so we force it instead. Further, we can do
subtraction directly on a full int32_t rather than an i8vec4
with bit twiddling because the high bit is always free to start.
On Intel BMG on mesa, the switch to MMVQ provides an immediate
~57% perf increase in tg128 for unsloth/Qwen3.5-9B-GGUF:Q3_K and
~78% perf increase in tg128 for unsloth/Qwen3.5-9B-GGUF:Q6_K.
The futher switch to block loads leads to a ~24% perf increase in
tg128 for unsloth/Qwen3.5-9B-GGUF:Q3_K and a ~48% perf increase in
tg128 for unsloth/Qwen3.5-9B-GGUF:Q6_K.
Finally, Xe2 wins on MMVQ even for small k, so we take the NVIDIA
override for K quants on Xe2 as well.
Fixes: https://github.com/ggml-org/llama.cpp/pull/23927#discussion_r3332213086
The cpu-x64-high-perf job was missing the Linux label in its runs-on
specification, causing the runner to not be discovered. All other
self-hosted Linux jobs include this label.
Assisted-by: llama.cpp:local pi
* add to support Q1_0, NVFP4, IQ2_XXS, IQ2_XS, IQ2_S, IQ3_XXS, IQ1_S, IQ1_M, IQ3_S, IQ4_NL, IQ4_XS, I32, MXFP4, Q2_K, Q3_K, Q5_K, and Q6_K in GET_ROWS OP
* correct the link
* remove redundant apple job
openvino gpu and cpu test can share the same build and machine
Update build-rpc.yml
Update build-openvino.yml
cpu any doesnt make sense as we have an arm job already, so do high perf on both x86 and arm
remove duplicate x86 vulkan
combine backend sampling
Update server.yml
run server on arm as windows is x86
* emdawn on one machine only
* fix openvino, remove cpu tag as we dont have many x64 machines with that tag
* webui: add custom CSS injection via config
register a customCSS setting in the Developer section under Custom JSON,
syncable so it rides the existing ui-config pass through. inject the value
into a single style element in the head, reactive on the setting. lets an
operator theme a prebuilt binary through --ui-config without rebuilding,
and lets a user set it from the settings panel.
* ui: address review from @niutech and @allozaur, rename custom JSON key and CSS field
* ui: address review from @allozaur, move custom CSS injection to a style tag in svelte:head
* ui: inject custom CSS through a svelte action instead of a bound element
move the textContent write into a use: action on the head style node.
the action is the idiomatic way to touch a node, so the no-dom-manipulating
lint rule is satisfied without a disable. value stays text through
textContent, never parsed as HTML.
* Update tools/ui/src/lib/constants/settings-keys.ts
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* ui: address review from @allozaur, rename custom config key to customJson with migration
rename the custom config key to customJson across the type, the chat
request builder, the settings save check and the custom tools reader,
keeping the custom API param name unchanged. add a non destructive
migration that copies the legacy custom key to customJson at startup.
only render the head style tag when custom CSS is set.
---------
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* Support `-fa auto` in llama-bench
Make the default value of `-ngl` -1, similar to other tools.
Update README with latest usage and examples
* Address review comments
* ci : disable libcommon build from xcframework
* ocd : fix name
* ci : ios-xcode change to macos-26
* cont : pin xcode
* cont : pin xcode to minor version
* vulkan: add flash attention bf16 kv support
* vulkan: bf16 FA coopmat1 support
* vulkan: bf16 FA coopmat2 support
* fix FA bf16 f32 fallback
* fix FA bf16 coopmat1 shader
* fix FA bf16 coopmat2 shader
* code cleanup
* cleanup comment change
* address feedback
* add O_TYPE for cm2 FA
* use O_TYPE for gqaStore function
* reduce BFLOAT16 ifdefs
* ci : ios use macos-15 again
* ci : add and test ccache-clear
* cont : fix
* cont : set permission
* cont : another permission
* cont : token
* cont : print key
* cont : bring back perms
* cont : test windows
* cont : add token
* cont : cleanup
* ci : make release jobs clean-up their ccache
After #23007 reclassified integrated CUDA/HIP devices as IGPU, the device
selection logic dropped the local iGPU whenever any RPC server was added,
because RPC devices made `model->devices` non-empty. On systems where the
"iGPU" is the main compute device (e.g. Strix Halo with 128 GiB of unified
memory), this caused all tensors to be allocated on the RPC peer alone and
model loading to fail.
Gate the iGPU inclusion on `gpus.empty()` instead, so RPC peers no longer
suppress the local iGPU.
closes: #23858
* CUDA: Check PTX version on host side to guard PDL dispatch
Checking on `__CUDA_ARCH_LIST__` alone is insufficient for JIT, as this
variable doesn't differentiate between compiling for say sm_90, sm_90a
or sm_90f (so forward-jittable PTX vs. arch/family-specific PTX).
Thus, one can have a bug when compiling with
`DCMAKE_CUDA_ARCHITECTURES="89;90a"`, where current code would wrongly
dispatch to PDL on sm_90/sm_120 in forward-JIT mode.
This PR fixes this issue by checking `cudaFuncAttributes::ptxVersion` of
the incoming kernel at runtime. A check on ptxVersion alone is
sufficient, as device-codes will always be >= ptxVersion (and any
violation of this would be a severe bug in CUDA/nvcc), see:
https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/#gpu-code-code-code
* Implement MurmurHash3 mixer for better hash distribution
Magic constants were taken from boost:
https://github.com/boostorg/container_hash/blob/2698b43803c012601e6bb1a6116e83767b97986c/include/boost/container_hash/detail/hash_mix.hpp#L19-L65
* Update ggml/src/ggml-cuda/common.cuh
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Address review comments, make seed non-zero
* Apply code-formatting
* Replace std::size_t -> size_t for consistency
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Jeff Bolz