Model Releases
b10814
opencl: extend the elementwise and data‐movement op coverage (#27633) opencl: add extended elementwise unary ops (sgn, step, elu, hardswish, hardsigmoid, floor, ceil, round, trunc) Adds nine GGML_UNAR
opencl: extend the elementwise and data‐movement op coverage (#27633) opencl: add extended elementwise unary ops (sgn, step, elu, hardswish, hardsigmoid, floor, ceil, round, trunc) Adds nine GGML_UNARY_OP_* elementwise ops that were falling back to CPU on the OpenCL backend, following the same variant shape as the existing ABS op: f32, f32_4 (vec4), f16, f16_4 (vec4), and stride-addressed f32_nc / f16_nc for non-contiguous inputs. New kernels/unary_ext.cl (macro-generated), a shared ggml_cl_unary_ext dispatch helper mirroring ggml_cl_abs, the supports_op cases, and the compute-forward cases. Values are computed in float (the f16 variants read/write half and convert), so the conditional ops (step, elu) match the CPU reference; the vec4 forms use select() for the branch. Validated with test-backend-ops on Adreno 840 and 850 (E17): all nine ops pass every case including the vec4 and non-contiguous variants (8/8 or 14/14). opencl: dispatch a contiguous f32 copy over the whole device kernel_cpy_f32_f32 maps one workgroup to each (i01,i02,i03) row and strides the row across that workgroup's lanes, and the host launches ne01*MIN(64,ne00) work items. A tensor with few long rows therefore runs on a single workgroup. The mamba2 and gated-delta-net recurrent state cache is one row of 524288 floats, copied once per layer per graph, and lands on 64 work items. When both sides are contiguous the copy is a linear move, so dispatch it over the whole device: one work item per float4. Gated on ggml_is_contiguous for both tensors and equal element counts, so copies already spread over many rows keep the existing path. The kernel is created optionally, so a driver that rejects it falls back rather than aborting. vload4/vstore4 rather than a float4 cast: they require only the scalar type's alignment, and these buffers carry an arbitrary 4-byte view offset. CPY, DUP and CONT are 217/217 on Adreno 840 and 740 with the path enabled and disabled. GGML_OPENCL_CPY_FLAT=0 forces the old kernel. opencl: support all easy-copy types in CONCAT CONCAT was F32-only. Extend it to every "easy-copy" type -- any non-quantized type with a block size of 1 and an element size of 1, 2, 4 or 8 bytes, i.e. f16/bf16/i8/i16/i32/i64 as well as f32. The kernels are keyed by element SIZE rather than by type, which is what CUDA already does for the same op: one kernel per byte width (b1/b2/b4/b8) plus the packed b4 fast path, instead of one per ggml type. supports_op gates on the same property, so a new type of a supported width is picked up with no further work. Validated with test-backend-ops on Adreno 840 / A8X and X2-90 / X2E. Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45331746 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu arm64 (CPU) Ubuntu s390x (CPU) Ubuntu x64 (Vulkan) Ubuntu arm64 (Vulkan) Ubuntu x64 (ROCm 10.0) Ubuntu x64 (OpenVINO) Ubuntu x64 (SYCL FP32) Ubuntu x64 (SYCL FP16) Android: Android arm64 (CPU) Windows: Windows x64 (CPU) Windows arm64 (CPU) Windows arm64 (OpenCL Adreno) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.3 DLLs Windows arm64 (CUDA 13) (preview) - CUDA 13.4 DLLs Windows x64 (Vulkan) Windows x64 (OpenVINO) Windows x64 (SYCL) Windows x64 (ROCm 10.0) openEuler: DISABLED openEuler x86 (310p) openEuler x86 (910b, ACL Graph) openEuler aarch64 (310p) openEuler aarch64 (910b, ACL Graph) UI: UI
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Source: llama.cpp Releases | 2026-09-04