* docker: add OCI image labels to all published images
* docker: propagate OCI labels as manifest and index annotations
* docker: drop hardcoded org URL and revert accidental intel version bump
The OCI image url and source are now driven by build args with a sensible default. The workflow passes the actual repository url so fork builds get labels pointing at the fork instead of upstream. Also restores the IGC, compute runtime, and IGDGMM versions in the intel Dockerfile labeled stage which I accidentally bumped in the first commit.
* docker: add skip_s390x workflow_dispatch input for fast test runs
Lets maintainers and PR authors trigger the docker workflow without the s390x build target, which depends on the IBM Z runner and is by far the slowest job in the matrix. The flag filters the s390x row out of the build matrix before merge_matrix is derived, so the merge job sees a consistent shape too.
Signed-off-by: Samaresh Kumar Singh <ssam3003@gmail.com>
---------
Signed-off-by: Samaresh Kumar Singh <ssam3003@gmail.com>
* Update build doc
* Add cgraph tensor output name to OV op name
* Update openvino build instructions
* Add initial NPU support
* draft NPU support version 2: prefill + kvcache
* NPU support version 2: prefill + kvcache
* Change due to ggml cgraph changes, not correct yet
* Change due to ggml cgraph changes, llama-3.2 CPU work
* Add AMD64 to CMakeLists
* Change due to ggml cgraph changes, all device work
* Refactor: clean, fix warning
* Update clang-format
* Statful transformation for CPU GPU
* Add SwiGLU
* Fuse to SDPA
* Replace Concat with Broadcast in MulMat for GQA
* Pull out indices creation for kv cache update
* Refactor: remove past_token_len from extra_inputs
* Fix Phi3 SwiGLU and SoftMax
* Pull out sin cos from rope
* Reduce memory: free ov weights node after graph conversion
* Fix CPY due to cgraph change
* Added OpenVINO CI/CD. Updated docs
* Fix llama-cli
* Fix Phi3 ROPE; Add test-backend-ops
* Fix NPU
* Fix llama-bench; Clang-format
* Fix llama-perplexity
* temp. changes for mark decomp
* matmul in fp32
* mulmat input conversion fix
* mulmat type conversion update
* add mark decomp pass
* Revert changes in fuse_to_sdpa
* Update build.md
* Fix test-backend-ops
* Skip test-thread-safety; Run ctest only in ci/run.sh
* Use CiD for NPU
* Optimize tensor conversion, improve TTFT
* Support op SET_ROWS
* Fix NPU
* Remove CPY
* Fix test-backend-ops
* Minor updates for raising PR
* Perf: RMS fused to OV internal RMS op
* Fix after rebasing
- Layout of cache k and cache v are unified: [seq, n_head, head_size]
- Add CPY and FLASH_ATTN_EXT, flash attn is not used yet
- Skip test-backend-ops due to flash attn test crash
- Add mutex around graph conversion to avoid test-thread-safety fali in the future
- Update NPU config
- Update GPU config to disable SDPA opt to make phi-3 run
* Change openvino device_type to GPU; Enable flash_attn
* Update supports_buft and supports_op for quantized models
* Add quant weight conversion functions from genai gguf reader
* Quant models run with accuracy issue
* Fix accuracy: disable cpu_repack
* Fix CI; Disable test-backend-ops
* Fix Q4_1
* Fix test-backend-ops: Treat quantized tensors as weights
* Add NPU Q4_0 support
* NPU perf: eliminate zp
* Dequantize q4_1 q4_k q6_k for NPU
* Add custom quant type: q8_1_c, q4_0_128
* Set m_is_static=false as default in decoder
* Simpilfy translation of get_rows
* Fix after rebasing
* Improve debug util; Eliminate nop ReshapeReshape
* STYLE: make get_types_to_requant a function
* Support BF16 model
* Fix NPU compile
* WA for npu 1st token acc issue
* Apply EliminateZP only for npu
* Add GeGLU
* Fix Hunyuan
* Support iSWA
* Fix NPU accuracy
* Fix ROPE accuracy when freq_scale != 1
* Minor: not add attention_size_swa for non-swa model
* Minor refactor
* Add Q5_K to support phi-3-q4_k_m
* Requantize Q6_K (gs16) to gs32 on GPU
* Fix after rebasing
* Always apply Eliminate_ZP to fix GPU compile issue on some platforms
* kvcachefusion support
* env variable GGML_OPENVINO_DISABLE_SDPA_OPTIMIZATION added
* Fix for Phi3
* Fix llama-cli (need to run with --no-warmup)
* Fix add_sliced_mask; Revert mulmat, softmax; Remove input attention_size, iSWA model not working
* fix after rebasing
* Fix llama-3-8b and phi3-mini q4_0 NPU
* Update to OV-2025.3 and CMakeLists.txt
* Add OV CI cache
* Apply CISC review and update CI to OV2025.3
* Update CI to run OV dep install before build
* Update OV dockerfile to use OV2025.3 and update build docs
* Style: use switch in supports_ops
* Style: middle ptr and ref align, omit optional struct keyword
* NPU Unify PD (#14)
* Stateless. Fix llama-cli llama-server
* Simplify broadcast op in attention
* Replace get_output_tensor+memcpy with set_output_tensor
* NPU unify PD. Unify dynamic and static dims
* Clean placeholders in ggml-openvino.cpp
* NPU unify PD (handled internally)
* change graph to 4d, support multi sequences
* Fix llama-bench
* Fix NPU
* Update ggml-decoder.cpp
Hitting error while compiling on windows:
error C3861: 'unsetenv': identifier not found
Reason: unsetenv() is a POSIX function; it doesn’t exist on Windows. Visual Studio (MSVC) won’t recognize it.
Proposed fix: Use _putenv_s() (Windows equivalent)
This is supported by MSVC and achieves the same effect: it removes the environment variable from the process environment.
This keeps cross-platform compatibility.
* Update ggml-decoder.cpp
* Update ggml-decoder.cpp
* Update ggml-decoder.cpp
* Update ggml-decoder.cpp
* Update ggml-decoder.cpp
* Remove the second decoder for node. Moving the function into the model decoder
* Fix error for naive
* NPU prefill chunking
* NPU fix llama-bench
* fallback naive run with accuracy issue
* NPU support llma-perplexity -b 512 --no-warmup
* Refactor: split ov_graph_compute for dynamic and static
* remove unused API GgmlOvDecoder::get_output_stride(const std::string & name)
* minor update due to ov 2025.4
* remove unused API GgmlOvDecoder::get_output_names()
* remove unused API get_output_shape(const std::string & name)
* Modified API GgmlOvDecoder::get_output_type(const std::string & name)
* Removed API GgmlOvDecoder::get_output_op_params(const std::string & name)
* Removed API get_output_ggml_tensor(const std::string & name)
* Removed API m_outputs
* Removed m_output_names
* Removed API GgmlOvDecoder::get_input_names()
* Removed API GgmlOvDecoder::get_input_stride(const std::string& name)
* Removed API get_input_type
* Removed API get_input_type
* Removed API GgmlOvDecoder::get_input_shape(const std::string & name)
* Removed API GgmlOvDecoder::get_input_op_params(const std::string & name)
* Fix error for decoder cache
* Reuse cached decoder
* GPU remove Q6_K requantization
* NPU fix wrong model output shape
* NPU fix q4 perf regression
* Remove unused variable nodes
* Fix decoder can_reuse for llama-bench
* Update build.md for Windows
* backend buffer: allocate on host
* Use shared_buffer for GPU NPU; Refactor
* Add ov_backend_host_buffer; Use cached remote context
* Put kvcache on GPU
* Use ggml_aligned_malloc
* only use remote tensor for kvcache
* only use remote tensor for kvcache for GPU
* FIX: use remote tensor from singleton
* Update build.md to include OpenCL
* NPU always requant to q4_0_128
* Optimize symmetric quant weight extraction: use single zp
* Use Q8_0_C in token embd, lm_head, and for 5 and 6 bits quant
* Update build.md
* Support -ctk f32
* Initial stateful graph support
* Update ggml/src/ggml-openvino/ggml-decoder.cpp
Co-authored-by: Yamini Nimmagadda <yamini.nimmagadda@intel.com>
* code cleanup
* npu perf fix
* requant to f16 for Q6 embed on NPU
* Update ggml/src/ggml-openvino/ggml-decoder.cpp
* Update ggml/src/ggml-openvino/ggml-openvino-extra.cpp
* Create OPENVINO.md in llama.cpp backend docs
* Update OPENVINO.md
* Update OPENVINO.md
* Update OPENVINO.md
* Update build.md
* Update OPENVINO.md
* Update OPENVINO.md
* Update OPENVINO.md
* kq_mask naming fix
* Syntax correction for workflows build file
* Change ov backend buffer is_host to false
* Fix llama-bench -p -n where p<=256
* Fix --direct-io 0
* Don't put kvcache on GPU in stateful mode
* Remove hardcode names
* Fix stateful shapes
* Simplification for stateful and update output shape processing
* Remove hardcode names
* Avoid re-compilation in llama-bench
* Extract zp directly instead of bias
* Refactor weight tensor processing
* create_weight_node accept non-ov backend buffer
* remove changes in llama-graph.cpp
* stateful masking fix (#38)
Fix for stateful accuracy issues and cl_out_of_resources error in stateful GPU with larger context sizes.
* Fix test-backend-ops crash glu, get_rows, scale, rms_norm, add
* hardcoded name handling for rope_freqs.weight
* Suppress logging and add error handling to allow test-backend-ops to complete
* Fix MUL_MAT with broadcast; Add unsupported MUL_MAT FLASH_ATTN cases
* Use bias instead of zp in test-backend-ops
* Update OV in CI, Add OV CI Tests in GH Actions
* Temp fix for multithreading bug
* Update OV CI, fix review suggestions.
* fix editorconfig-checker, update docs
* Fix tabs to spaces for editorconfig-checker
* fix editorconfig-checker
* Update docs
* updated model link to be GGUF model links
* Remove GGML_CPU_REPACK=OFF
* Skip permuted ADD and MUL
* Removed static variables from utils.cpp
* Removed initializing non-existing variable
* Remove unused structs
* Fix test-backend-ops for OV GPU
* unify api calling
* Update utils.cpp
* When the dim is dynamic, throw an error, need to is stastic forst
* Add interface compute_model_outputs(), which get the model output through computing the node use count & status in the cgraph to avoid the flag using
* No need to return
* Fix test-backend-ops for OV GPU LNL
* Fix test-thread-safety
* use the shape from infer request of output tensor create to avoid issue
* fix dynamic output shape issue
* fix issue for the unused node in tests
* Remove unused lock
* Add comment
* Update openvino docs
* update to OV release version 2026.0
* add ci ov-gpu self hosted runner
* fix editorconfig
* Fix perplexity
* Rewrite the model inputs finding mechanism (#54)
* Rewrite the model inputs finding logistic
* Put stateful shape handle in get input shape
* Put the iteration logistic in func
* Added ggml-ci-intel-openvino-gpu and doc update
* .hpp files converted to .h
* fix ggml-ci-x64-intel-openvino-gpu
* Fix for stateful execution bug in llama-bench
* Minor updates after stateful llama-bench fix
* Update ggml/src/ggml-openvino/utils.cpp
Co-authored-by: Yamini Nimmagadda <yamini.nimmagadda@intel.com>
* Remove multiple get_shape calls
* Bring back mutex into compute
* Fix VIEW op, which slice the input node
* Added token_len_per_seq existence check before slicing masks and moved node retrieval inside guarded block to prevent missing-key access
* Temp. fix for test requant errors
* Update to OV ggml-ci to low-perf
* ci : temporary disable "test-llama-archs"
* ci : cache v4 -> v5, checkout v4 -> v6, fix runner tag
* docs : update url
* Fix OV link in docker and Update docs
---------
Co-authored-by: Ravi Panchumarthy <ravi.panchumarthy@intel.com>
Co-authored-by: Cavus Mustafa <mustafa.cavus@intel.com>
Co-authored-by: Arshath <arshath.ramzan@intel.com>
Co-authored-by: XuejunZhai <Xuejun.Zhai@intel.com>
Co-authored-by: Yamini Nimmagadda <yamini.nimmagadda@intel.com>
Co-authored-by: Xuejun Zhai <Xuejun.Zhai@intel>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This was disabled in #9340 due to compiler crash, but seems to build now as confirmed by the latest comments in #11913.
I've also managed to build the image with `docker build -f .devops/rocm.Dockerfile .` (for all three stages, `full`, `server` and `light`).
A quick attempt at trying to build an arm64 image failed. Since none of the other images are build for arm, I only enabled the amd64 one.
The `runs_on` option was added to match the other entries.
* ci : create git tags for released docker images
When releasing a docker image for build number X, we should also create
the corresponding git tag. This allows users to easily checkout the
corresponding source tree for given docker image.
* Update .github/workflows/docker.yml
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update .github/workflows/docker.yml
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Apply suggestion from @CISC
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* feat: add Dockerfiles for each platform that user ./server instead of ./main
* feat: update .github/workflows/docker.yml to build server-first docker containers
* doc: add information about running the server with Docker to README.md
* doc: add information about running with docker to the server README
* doc: update n-gpu-layers to show correct GPU usage
* fix(doc): update container tag from `server` to `server-cuda` for README example on running server container with CUDA
Enables the GPU enabled container images to be built and pushed
alongside the CPU containers.
Co-authored-by: canardleteer <eris.has.a.dad+github@gmail.com>
Aldehir Rojas