b10052

ggml-org/llama.cppb10052Jul 16, 2026by github-actions[bot]

AI Summary

Major overhaul of Hexagon L2 cache handling, introducing dirty bit tracking, threaded flushing, and various MUL_MAT and workqueue improvements.

Key Highlights

  • Reworked L2 cache handling with lazy flushing and dirty bit tracking.
  • Introduced threaded L2 flushes and dedicated main threads.
  • Improved tensor alias handling, DMA queue support, and workqueue APIs.

Full Release Notes

<details open>

hexagon: L2 cache handling rework (dirty bit tracking with lazy flushing) and more MUL_MAT updates (#25762)

* hex-mm: fix artificial limit in the solver that restricted number of act-prep threads

* hex-mm: fix warning

* hex-prof: do not apply --top to the timeline report

* hmx-mm: add suport for tiled act-processing to better distribute hvx work

* hex-l2: add tracing for l2flush events

* workqueue: redo the legacy workpool api to match hmx-queue and dma-queue

* hmx-mm: fix f32 activation buffer alignmnet for nhvx=5,6,7

* hex-work: minor cleanup for work-queue apis

* hex-work: further cleanup of the work-queue api

* hex-l2: optimize l2flushes at the opbatch level

* hex-work: remove unused mask

* hex-work: no need to drop hvx ctx in the work-queue

* hex-work: add explicit wakeup/suspend and make threads spin

* hex-bufs: mark any non-weight tensor as compute

* hex-dma: dma-queue support for alias queues and cached dma

* hex-l2: track tensor aliases and delay or skip flushes as much as possible

* hex-l2: simplify tensor alias handling

* hex-l2: handle overlapping views as a circular list of aliases

* hex-tens: add flags helper

* hex-l2: add helper for marking tensors clearn/dirty

* hex-l2: mark binary and rope outputs as l2-clean and keep the rest as is for now

* hex-l2: proper support for handling all tensor overlap scenarios

* hex-trace: instrument matmul init code and cleanup trace checks

* hex-thread: introduce dedicated main thread with explicit stack and priority

* hex-l2: track dirty state as bitmap and introduce threaded flush

* hex-trace: remove redundant checks for ctx != null

* hex-l2: allocate entire context as one buffer and l2fetch it after big flushes

* hex-l2: disable tensor clearing in binary and rope for now seems to cause issues with fusion

* hmx-mm: update act proc to use fastdivs and fix DMA overflow

* hmx-mm: make MUL_MAT_ID kernels robust to multi-chunk cases (start_row>0)

* hex-queue: remove obsolete queue interfaces and flush hmx-queue at the end of the op-batch

* hex-queue: dont use early wakeup for small op-batches

* hex-tensors: properly cap max_tensors in op-batches and dirty_map

* hex-l2: make sure threaded l2flush does proper rounding

* hex-l2: factor out htp_tensor_flush for reuse (if needed)

* hex-l2: optimize tensor flushes by coalescing flush-all

* hex-l2: optimize multi-threaded flush

* hex-drv: futureproof version checks

* hexagon: fix errors and warnings on windows

* hex-main: update main thread to only use dspqueue_read, dspqueue_peek is not available on some platforms

* hex-main: add fallback mode for dspqueue with callbacks

* hex-main: introduce fallback mode for using dspqueue callbacks for full op processing

* hex-main: remove early wakeup, not helping and seems to cause some errors with certain batch sizes

* hex-l2: make sure to use invalidate version of flushall

* hex-l2: dont try to trace early l2flush at the start of op-batch

* hex-main: remove offset_ctx that must be zero anyway

* hex-hmx: fix hmx_queue_depth to use idx_write - idx_read

* hex-hmx: use atomic_load for idx_read/write

* hex-main: add static assert to make sure n_threads are aligned

</details>

**Website:**
- <https://llama.app>

**macOS/iOS:**
- [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-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/b10052/llama-b10052-bin-macos-x64.tar.gz)
- [iOS XCFramework](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-xcframework.zip)

**Linux:**
- [Ubuntu x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-x64.tar.gz)
- [Ubuntu arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-arm64.tar.gz)
- [Ubuntu s390x (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-s390x.tar.gz)
- [Ubuntu x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-vulkan-x64.tar.gz)
- [Ubuntu arm64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-vulkan-arm64.tar.gz)
- [Ubuntu x64 (ROCm 7.2)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-rocm-7.2-x64.tar.gz)
- [Ubuntu x64 (OpenVINO)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-openvino-2026.2.1-x64.tar.gz)
- [Ubuntu x64 (SYCL FP32)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-sycl-fp32-x64.tar.gz)
- [Ubuntu x64 (SYCL FP16)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-ubuntu-sycl-fp16-x64.tar.gz)

**Android:**
- [Android arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-android-arm64.tar.gz)

**Windows:**
- [Windows x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-cpu-x64.zip)
- [Windows arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-cpu-arm64.zip)
- [Windows arm64 (OpenCL Adreno)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-opencl-adreno-arm64.zip)
- [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-cuda-12.4-x64.zip) - [CUDA 12.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/b10052/cudart-llama-bin-win-cuda-12.4-x64.zip)
- [Windows x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-cuda-13.3-x64.zip) - [CUDA 13.3 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/b10052/cudart-llama-bin-win-cuda-13.3-x64.zip)
- [Windows x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-vulkan-x64.zip)
- [Windows x64 (OpenVINO)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-openvino-2026.2.1-x64.zip)
- [Windows x64 (SYCL)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-sycl-x64.zip)
- [Windows x64 (HIP)](https://github.com/ggml-org/llama.cpp/releases/download/b10052/llama-b10052-bin-win-hip-radeon-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/b10052/llama-b10052-ui.tar.gz)