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xc-llm-ascend/csrc/dispatch_ffn_combine/op_kernel/utils/const_args.hpp

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add `dispatch_gmm_combine` kernel (#3532) ### What this PR does / why we need it? This PR introduces the Ascend implementation of the `dispatch_ffn_combine` kernel and wires it into the vLLM-Ascend runtime, together with follow‑up fixes to ensure the kernel builds and runs correctly in CI. - Add full host and device implementation of the `dispatch_ffn_combine` kernel under `csrc/dispatch_ffn_combine`, including tiling logic, MOE routing helpers, and kernel utilities for quantized FFN dispatch. - Integrate the new kernel with the PyTorch binding (csrc/torch_binding.cpp, csrc/torch_binding_meta.cpp) and the Ascend runtime (vllm_ascend/ascend_forward_context.py, vllm_ascend/worker/model_runner_v1.py). - Extend fused MoE communication and token dispatch support in `vllm_ascend/ops/fused_moe`, adding methods/utilities needed by the new dispatch path. - Update quantization logic in vllm_ascend/quantization/w8a8_dynamic.py to support the new FFN dispatch flow. - Fix kernel build issues by adjusting `csrc/build_aclnn.sh`, CMake configuration, and include/namespace usage in the new kernel files. - Add an end‑to‑end nightly test `tests/e2e/nightly/ops/test_dispatch_ffn_combine.py` and helper utilities in `vllm_ascend/utils.py` to validate the new kernel. ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.12.0 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.12.0 --------- Signed-off-by: mojave2 <chenchen145@huawei.com> Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-12-04 23:00:59 +08:00
#ifndef CONST_ARGS_HPP
#define CONST_ARGS_HPP
constexpr static uint64_t MB_SIZE = 1024 * 1024UL;
constexpr static int32_t NUMS_PER_FLAG = 16;
[CustomOp] support TensorList for dispatchFFNCombine (#5665) ### What this PR does / why we need it? To support tensorList for dispatch_ffn_combine, to adjust eplb ### Does this PR introduce _any_ user-facing change? N/A ### How was this patch tested? Single Operator Testing - vLLM version: v0.13.0 - vLLM main: https://github.com/vllm-project/vllm/commit/2f4e6548efec402b913ffddc8726230d9311948d --------- Signed-off-by: lhchg <lhao_cheng@163.com> Co-authored-by: lihaocheng <lihaosheng1@h-partners.com>
2026-01-09 15:56:29 +08:00
constexpr static int32_t CACHE_LINE = 512;
constexpr static int32_t RESET_VAL = 0xffff;
[Kernel]: Optimize DispatchFFNCombine performance (#6468) ### What this PR does / why we need it? This PR focuses on performance optimization for the DispatchFFNCombine operator. The key optimizations include: 1. Improving communication efficiency by merging the transmission of tokens and scales; 2. Decoupling multi-core dependencies and reducing waiting bubbles in the combine process through tile-granularity communication; 3. Optimizing the full-card synchronization overhead before the umpermute operation. These optimizations aim to reduce the overall execution latency of the DispatchFFNCombine operator and enhance the runtime performance of the model inference process on Ascend devices. ### Does this PR introduce _any_ user-facing change? No. This PR only involves internal performance optimization of the DispatchFFNCombine operator and does not introduce any changes to user-facing APIs, interfaces, or behaviors. ### How was this patch tested? 1. Enable the DispatchFFNCombine operator by setting the environment variable: ``` export VLLM_ASCEND_ENABLE_FUSED_MC2=1 ``` 2. Run the standard model inference test suite with the above environment variable enabled; 4. Verify the correctness of model outputs (ensuring no functional regression) and measure the performance improvement of the DispatchFFNCombine operator (reduced latency and improved throughput). - vLLM version: v0.14.1 - vLLM main: https://github.com/vllm-project/vllm/commit/dc917cceb877dfd13f98c538c4c96158047d98bd Signed-off-by: xulei_ict <xulei292@huawei.com> Co-authored-by: xulei_ict <xulei292@huawei.com>
2026-02-09 16:30:34 +08:00
constexpr static int32_t FLAGSTRIDE = 16;
constexpr static int32_t UB_ALIGN = 32;
constexpr uint16_t CROSS_CORE_FLAG_MAX_SET_COUNT = 15;
add `dispatch_gmm_combine` kernel (#3532) ### What this PR does / why we need it? This PR introduces the Ascend implementation of the `dispatch_ffn_combine` kernel and wires it into the vLLM-Ascend runtime, together with follow‑up fixes to ensure the kernel builds and runs correctly in CI. - Add full host and device implementation of the `dispatch_ffn_combine` kernel under `csrc/dispatch_ffn_combine`, including tiling logic, MOE routing helpers, and kernel utilities for quantized FFN dispatch. - Integrate the new kernel with the PyTorch binding (csrc/torch_binding.cpp, csrc/torch_binding_meta.cpp) and the Ascend runtime (vllm_ascend/ascend_forward_context.py, vllm_ascend/worker/model_runner_v1.py). - Extend fused MoE communication and token dispatch support in `vllm_ascend/ops/fused_moe`, adding methods/utilities needed by the new dispatch path. - Update quantization logic in vllm_ascend/quantization/w8a8_dynamic.py to support the new FFN dispatch flow. - Fix kernel build issues by adjusting `csrc/build_aclnn.sh`, CMake configuration, and include/namespace usage in the new kernel files. - Add an end‑to‑end nightly test `tests/e2e/nightly/ops/test_dispatch_ffn_combine.py` and helper utilities in `vllm_ascend/utils.py` to validate the new kernel. ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.12.0 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.12.0 --------- Signed-off-by: mojave2 <chenchen145@huawei.com> Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-12-04 23:00:59 +08:00
#endif
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