Hi, I wonder if ARM Compute Library can be built and run on ARM v7l
processors, qith subset of the functionalities as SVE not supported on
v7l? Thanks for info
Hello,
The 23.08 release of Compute Library is out and comes with a collection of improvements and new features.
Source code and prebuilt binaries are available at: https://github.com/ARM-software/ComputeLibrary/releases/tag/v23.08
[https://opengraph.githubassets.com/6f01aff4f7ab61ec8b32d60f2ac777cf469f2c19…]<https://github.com/ARM-software/ComputeLibrary/releases/tag/v23.08>
Release v23.08 · ARM-software/ComputeLibrary<https://github.com/ARM-software/ComputeLibrary/releases/tag/v23.08>
Public major release Documentation (API, changelogs, build guide, contribution guide, errata, etc.) available here: https://arm-software.github.io/ComputeLibrary/v23.08/github.com
Highlights of the release:
* Rewrite CLArgMinMaxLayer for axis 0 and enable S64 output.
* Add multi-sketch support for dynamic fusion.
* Break up arm_compute/core/Types.h and utils/Utils.h a bit to reduce unused code in each inclusion of these headers.
* Add Fused Activation to CLMatMul.
* Implement FP32/FP16 opencl::kernels::ClMatMulNativeMMULKernel using the MMUL extension.
* Use MatMul in fully connected layer with dynamic weights when supported.
* Optimize CPU depthwise convolution with channel multiplier.
* Add support in CpuCastKernel for conversion of S64/U64 to F32.
* Add new OpenCL™ kernels:
opencl::kernels::ClMatMulNativeMMULKernel support for FP32 and FP16, with batch support
* Enable transposed convolution with non-square kernels on CPU and GPU.
* Add support for input data type U64/S64 in CLCast.
* Add new Compute Kernel Writer (CKW) subproject that offers a C++ interface to generate tile-based OpenCL code in just-in-time fashion.
* Port the following kernels in the experimental Dynamic Fusion interface to use the new Compute Kernel Writer interface with support for FP16/FP32 only:
experimental::dynamic_fusion::GpuCkwActivation
experimental::dynamic_fusion::GpuCkwCast
experimental::dynamic_fusion::GpuCkwDirectConv2d
experimental::dynamic_fusion::GpuCkwElementwiseBinary
experimental::dynamic_fusion::GpuCkwStore
IMPORTANT NOTICE: The contents of this email and any attachments are confidential and may also be privileged. If you are not the intended recipient, please notify the sender immediately and do not disclose the contents to any other person, use it for any purpose, or store or copy the information in any medium. Thank you.
