ACL graph capture disallows host-to-device memcpy and device memory
malloc/free on the captured stream. Pre-load the RoPE cache before
capture so that:
- Host-to-device copies and allocations run on the non-captured stream
- Cache metadata is populated and memory pool is warmed up
- During capture, only on-device computations are recorded; host-side
and allocation branches are skipped
RotaryPositionEmbedding on CANN fails when src and dst share the same
non-contiguous buffer (inplace + view), because the operator overwrites
source data before it is fully read.
Add a branch that detects this case and uses contiguous temporary
buffers: copy src to temp, run ROPE into another temp, then copy back
to the non-contiguous dst. Fixes 20 failing ROPE tests (f32, v=1,
inplace=1).
Signed-off-by: noemotiovon <757486878@qq.com>
- Allow FLASH_ATTN_EXT when head dimension D is not a multiple of 16 by
padding Q/K/V to D_padded = GGML_PAD(D, 16), running FusedInferAttentionScoreV2,
then slicing the output back to D (ggml-cann.cpp + aclnn_ops.cpp).
- Fix aclnn_get_slope second-part offset: use ggml_type_size(dtype) instead of
sizeof(float) so ALiBi slopes are correct when dtype is F16 (e.g. GQA with
48 heads); fixes buffer overflow and large numerical errors in those cases.
* CANN: fix an issue where get_env was not fully renamed
* ci: add cann with acl group
* ci: define use_acl_graph using GitHub Action
* ci: update cann dockerfile with acl graph
This commit implements operator fusion for ADD + RMS_NORM operations
in the CANN backend to reduce memory access overhead and improve
performance. The fusion is controlled by the GGML_CANN_OPERATOR_FUSION
environment variable (default: false).
Changes:
- Implement ggml_cann_op_add_rms_norm_fused() using ACLNN AddRmsNorm
- Add ggml_cann_can_fuse() to check fusion eligibility
- Integrate fusion logic into computation graph evaluation
- Add test cases for ADD + RMS_NORM fusion
- Update documentation with new environment variable
The fusion combines ADD and RMS_NORM into a single kernel call,
which is more efficient than executing them separately.
* cann: add support for partial RoPE and Vision mode
Add support for two important RoPE variants: partial rotation (rope_dims < ne0)
and Vision mode rotation.
1. Support for partial RoPE (rope_dims < ne0):
- Split tensor into head (first rope_dims dimensions) and tail portions
- Apply rotation only to head portion using RotaryPositionEmbedding operator
- Copy unrotated tail portion directly from source to destination
- Handle both contiguous and non-contiguous tensor layouts
2. Support for Vision mode (GGML_ROPE_TYPE_VISION):
- Set rope_dims = ne0 for Vision mode to rotate entire tensor
- Vision mode pairs dimension i with dimension i+n_dims (where n_dims = ne0/2)
- No tail handling needed since entire tensor is rotated
Implementation details:
- Use has_tail flag to determine execution path: head/tail splitting when
rope_dims < ne0, or full tensor rotation when rope_dims == ne0
- Support both F32 and F16 data types with intermediate F32 conversion
- Copy non-contiguous tensors to contiguous buffers before calling
RotaryPositionEmbedding operator for compatibility
- Improve cache invalidation logic to include rope_dims and indep_sects
parameters
These enhancements enable CANN backend to handle various RoPE configurations
used in modern vision-language models and models with partial rotation.
* cann: fix review comment
* cann: fix acl_tensor_ptr usage in ASCEND_310P ROPE implementation
Fix compilation errors in the ASCEND_310P-specific ROPE operation code
by adding .get() calls when passing acl_tensor_ptr smart pointers to
functions expecting raw aclTensor* pointers.
This fixes the code that was missed in the previous refactoring commit
(8981848) which changed ggml_cann_create_tensor() return type from
aclTensor* to acl_tensor_ptr.
* cann: format code
* cann: improve device ID handling and aclnnArange checks
- Stop relying on CANN's internal device ID retrieval; use a global variable instead.
- Enforce stricter dimension validation in aclnnArange for better compatibility across CANN versions.
* cann: use thread local var
This commit applies .clang-format rules to all source files under the
ggml-cann directory to ensure consistent coding style and readability.
The .clang-format option `SortIncludes: false` has been set to disable
automatic reordering of include directives.
No functional changes are introduced.
Co-authored-by: hipudding <huafengchun@gmail.com>
This commit fixes a CPU-side memory leak issue in the CANN backend,
which occurred when intermediate aclTensorList objects were not properly
released after operator execution. The leak happened during repeated
invocations of CANN ops (e.g., FlashAttention), leading to increasing
host memory usage over time.
Proper resource cleanup (aclDestroyTensorList and related release logic)
has been added to ensure that all temporary tensors are correctly freed.
* CANN: improve ACL graph matching
Record `ne` and `nb` information for src tensors and include them in the
graph matching check. This enhances the robustness of ACL graph matching
by preventing incorrect matches when src tensors share the same data
address but differ in shape or stride.
* CANN: add op_params match
* CANN: Fix ggml_cann_set_device to avoid redundant device switches
- Added a check to skip aclrtSetDevice if the current device is already set.
- Prevents unnecessary context switches while keeping thread/device consistency.
* CANN: add device default id
* CANN: Add ROPE sin/cos cache for reuse
Introduce sin/cos caching mechanism in ROPE to avoid redundant
computation across layers. The cache is built on the first layer
per device and reused by subsequent layers if parameters match.
- Added sin_cache / cos_cache pointers and position_length tracking
- Introduced cache validity flags and properties:
(ext_factor, theta_scale, freq_scale, attn_factor, is_neox)
- Accelerates ROPE by eliminating repeated sin/cos generation
This change reduces overhead in multi-layer scenarios while
preserving correctness by verifying parameter consistency.
Co-authored-by: hipudding <huafengchun@gmail.com>
* fix typo
Signed-off-by: noemotiovon <757486878@qq.com>
---------
Signed-off-by: noemotiovon <757486878@qq.com>
Co-authored-by: hipudding <huafengchun@gmail.com>
* CANN: implement LRU cache for ACL graphs in CANN backend
- Introduce ggml_cann_graph_lru_cache to store multiple ggml_cann_graph objects.
- Graphs are loaded on demand and evicted using LRU policy when capacity is exceeded.
- Updated push, move_to_front, and clear methods to manage cached graphs efficiently.
- Ensures reuse of graphs, reducing graph reconstruction overhead in CANN backend.
* fix typo
* The LRU cache capacity can be configured via an env variable
Signed-off-by: noemotiovon <757486878@qq.com>
* refactory acl graph
* refactory && fix review comments
Signed-off-by: noemotiovon <757486878@qq.com>
---------
Signed-off-by: noemotiovon <757486878@qq.com>
Fixes#15330
Adjust the allocation size of acl_rstd. The parameter `dims` is set to 3 according to the CANN documentation.
Co-authored-by: Yuchuan <yuchuan-cao@users.noreply.github.com>
* [CANN] Support eager execution mode under ACL graph compilation
Add support for running operators in eager mode while ACL graph
compilation is enabled. This allows bypassing graph execution
and directly submitting ops, which is useful for debugging and
reducing graph build overhead in certain scenarios.
Signed-off-by: noemotiovon <757486878@qq.com>
* fix typo
Signed-off-by: noemotiovon <757486878@qq.com>
* rename to acl_graph_mode
Signed-off-by: noemotiovon <757486878@qq.com>
---------
Signed-off-by: noemotiovon <757486878@qq.com>
* CANN(flash-attn): refactor mask handling and improve performance
1. Refactored the mask computation in Flash Attention, unified the logic without separating prefill and decode.
2. Optimized performance in non-alibi scenarios by reducing one repeat operation.
3. Updated operator management to explicitly mark unsupported cases on 310P devices and when dim is not divisible by 16.
Signed-off-by: noemotiovon <757486878@qq.com>
* [CANN]: fix review
Signed-off-by: noemotiovon <757486878@qq.com>
* [CANN]: Optimization FA BNSD to BSND
Signed-off-by: noemotiovon <757486878@qq.com>
---------
Signed-off-by: noemotiovon <757486878@qq.com>
* feat(cann): add optional support for ACL Graph execution
This commit adds support for executing ggml computational graphs using
Huawei's ACL graph mode via the USE_CANN_GRAPH flag. The support can be
enabled at compile time using the CMake option:
-DUSE_CANN_GRAPH=ON
By default, ACL graph execution is **disabled**, and the fallback path
uses node-by-node execution.
Key additions:
- CMake option to toggle graph mode
- Graph capture and execution logic using
- Tensor property matching to determine whether graph update is required
- Safe fallback and logging if the environment variable LLAMA_SET_ROWS
is unset or invalid
This prepares the backend for performance improvements in repetitive graph
execution scenarios on Ascend devices.
Signed-off-by: noemotiovon <757486878@qq.com>
* Fix review comments
Signed-off-by: noemotiovon <757486878@qq.com>
* remane USE_CANN_GRAPH to USE_ACL_GRAPH
Signed-off-by: noemotiovon <757486878@qq.com>
* fix typo
Signed-off-by: noemotiovon <757486878@qq.com>
---------
Signed-off-by: noemotiovon <757486878@qq.com>
* [CANN] Support ELU and CONV_TRANSPOSE_1D
* [CANN]Modification review comments
* [CANN]Modification review comments
* [CANN]name adjustment
* [CANN]remove lambda used in template
* [CANN]Use std::func instead of template
* [CANN]Modify the code according to the review comments
---------
Signed-off-by: noemotiovon <noemotiovon@gmail.com>
