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b11936

llama : kq_mask의 형태와 무관하게 k-pool 스파스 선택을 구축합니다(#31243) * llama : kq_mask의 형태와 무관하게 k-pool 스파스 선택을 구축합니다 qwen4exp (QSA) 및 glm5-next는 캐시 셀을 인덱스로 선택하며 더 이상 kq_mask 값을 읽지 않지만, 여전히 밀집형 kq_mask와 마찬가지로 선택을 형성합니다. 대신 캐시 셀에 대해 [n_kv, n_tokens] 크기의 선택을 생성하고, 주석 처리 직전에 K 뷰의 스트림으로 분할합니다. 이를 통해 밀집형 마스크가 스파스 계층을 건드리지 않은 채 레이아웃(예: 시퀀스별 행 목록)을 변경할 수 있습니다. * 댓글 개선 공동 작성자: Georgi Gerganov * llama : 사용되지 않는 build_fused_top_k_mask 인수를 제거하고, 잡다한 사항을 검토합니다 --------- 공동 작성자: Georgi Gerganov **웹사이트:** - **인증서:** - **macOS/iOS:** - [macOS Apple Silico

번역 서비스가 일시 중지되어 원문을 표시합니다.

llama : build the k-pool sparse selection independently of the kq_mask shape (#31243)

* llama : build the k-pool sparse selection independently of the kq_mask shape

qwen4exp (QSA) and glm5-next pick cache cells by index and no longer read the kq_mask values, but they still shaped the selection like the dense kq_mask. Build the selection as [n_kv, n_tokens] over the cache cells instead, and split it into the streams of the K view right before the attention.

This lets the dense mask change its layout (e.g. per-sequence row lists) without touching the sparse layers.

* improve comment

Co-authored-by: Georgi Gerganov

* llama : drop the unused build_fused_top_k_mask args, review nits

---------

Co-authored-by: Georgi Gerganov

**Website:**

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**Attestations:**

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**macOS/iOS:**

- [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-macos-arm64.tar.gz)

- macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED](https://github.com/ggml-org/llama.cpp/pull/23780)

- [macOS Intel (x64)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-macos-x64.tar.gz)

- [iOS XCFramework](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-xcframework.zip)

**Linux:**

- [Ubuntu x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-ubuntu-x64.tar.gz)

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- [Ubuntu arm64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-ubuntu-vulkan-arm64.tar.gz)

- [Ubuntu x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-ubuntu-cuda-12.8-x64.tar.gz) - [CUDA 12.8 libraries](https://github.com/ggml-org/llama.cpp/releases/download/b11936/cudart-llama-b11936-bin-ubuntu-cuda-12.8-x64.tar.gz)

- [Ubuntu x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-ubuntu-cuda-13.4-x64.tar.gz) - [CUDA 13.4 libraries](https://github.com/ggml-org/llama.cpp/releases/download/b11936/cudart-llama-b11936-bin-ubuntu-cuda-13.4-x64.tar.gz)

- [Ubuntu arm64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-ubuntu-cuda-13.4-arm64.tar.gz) - [CUDA 13.4 libraries](https://github.com/ggml-org/llama.cpp/releases/download/b11936/cudart-llama-b11936-bin-ubuntu-cuda-13.4-arm64.tar.gz)

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**Android:**

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- [Android arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-android-arm64-snapdragon.tar.gz) - [setup guide](https://github.com/ggml-org/llama.cpp/blob/master/docs/backend/snapdragon/README.md)

**Windows:**

- [Windows x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-cpu-x64.zip)

- [Windows arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-cpu-arm64.zip)

- [Windows arm64 (OpenCL Adreno)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-opencl-adreno-arm64.zip)

- [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-cuda-12.4-x64.zip) - [CUDA 12.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/b11936/cudart-llama-bin-win-cuda-12.4-x64.zip)

- [Windows x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-cuda-13.4-x64.zip) - [CUDA 13.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/b11936/cudart-llama-bin-win-cuda-13.4-x64.zip)

- [Windows arm64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-cuda-13.4-arm64.zip) - [CUDA 13.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/b11936/cudart-llama-bin-win-cuda-13.4-arm64.zip)

- [Windows x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-vulkan-x64.zip)

- [Windows arm64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-vulkan-arm64.zip)

- [Windows x64 (OpenVINO)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-openvino-2026.4.1-x64.zip)

- [Windows x64 (SYCL)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-sycl-x64.zip)

- [Windows x64 (ROCm 10.0)](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-bin-win-rocm-10.0-x64.zip)

**openEuler:**

- [DISABLED](https://github.com/ggml-org/llama.cpp/pull/23705)

- openEuler x86 (310p)

- openEuler x86 (910b, ACL Graph)

- openEuler aarch64 (310p)

- openEuler aarch64 (910b, ACL Graph)

**UI:**

- [UI](https://github.com/ggml-org/llama.cpp/releases/download/b11936/llama-b11936-ui.tar.gz)

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