Compute Library v21.08

Author: Jenkins

Android.bp

@@ -1,34 +1,70 @@
+
+<br>
 <div align="center">
- <img src="https://raw.githubusercontent.com/ARM-software/ComputeLibrary/gh-pages/ACL_logo.png"><br><br>
+ <img src="https://raw.githubusercontent.com/ARM-software/ComputeLibrary/gh-pages/ACL_logo.png"/><br><br>
 </div>
 
-Release repository: https://github.com/arm-software/ComputeLibrary
+# Compute Library ![](https://img.shields.io/badge/latest_release-21.08-green)
 
-Development repository: https://review.mlplatform.org/#/admin/projects/ml/ComputeLibrary
 
-Please report issues here: https://github.com/ARM-software/ComputeLibrary/issues
+The Compute Library is a collection of low-level machine learning functions optimized for Arm® Cortex®-A and Arm® Mali™ GPUs architectures.<br>
 
-**Make sure you are using the latest version of the library before opening an issue. Thanks**
+The library provides superior performance to other open source alternatives and immediate support for new Arm® technologies e.g. SVE2.
 
-News:
+Key Features:
 
-- [Gian Marco's talk on Performance Analysis for Optimizing Embedded Deep Learning Inference Software](https://www.embedded-vision.com/platinum-members/arm/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit)
-- [Gian Marco's talk on optimizing CNNs with Winograd algorithms at the EVS](https://www.embedded-vision.com/platinum-members/arm/embedded-vision-training/videos/pages/may-2018-embedded-vision-summit-iodice)
-- [Gian Marco's talk on using SGEMM and FFTs to Accelerate Deep Learning](https://www.embedded-vision.com/platinum-members/arm/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit-iodice)
+- Open source software available under a permissive MIT license
+- Over 100 machine learning functions for CPU and GPU
+- Multiple convolution algorithms (GeMM, Winograd, FFT, Direct and indirect-GeMM)
+- Support for multiple data types: FP32, FP16, INT8, UINT8, BFLOAT16
+- Micro-architecture optimization for key ML primitives
+- Highly configurable build options enabling lightweight binaries
+- Advanced optimization techniques such as kernel fusion, Fast math enablement and texture utilization
+- Device and workload specific tuning using OpenCL tuner and GeMM optimized heuristics
 
-Related projects:
+<br>
 
-- [Arm NN SDK](https://github.com/arm-software/armnn)
+| Repository  | Link |
+| ----------- | ----------- |
+| Release     | https://github.com/arm-software/ComputeLibrary       |
+| Development | https://review.mlplatform.org/#/admin/projects/ml/ComputeLibrary        |
 
-Tutorials:
+<br>
 
-- [Tutorial: Running AlexNet on Raspberry Pi with Compute Library](https://community.arm.com/processors/b/blog/posts/running-alexnet-on-raspberry-pi-with-compute-library)
+## Documentation
+[![Documentation](https://img.shields.io/badge/documentation-21.08-green)](https://arm-software.github.io/ComputeLibrary/latest)
+
+> Note: The documentation includes the reference API, changelogs, build guide, contribution guide, errata, etc.
+
+<br>
+
+## Pre-built binaries
+All the binaries can be downloaded from [here](https://github.com/ARM-software/ComputeLibrary/releases) or from the tables below.
+
+<br>
+
+| Platform    | Operating System | Release archive (Download) |
+| ----------- | ----------- | ----------- | ----------- |
+| Raspberry Pi 4 | Linux 32bit | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-armv7a-neon.tar.gz) |
+| Raspberry Pi 4 | Linux 64bit | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-neon.tar.gz) |
+| Odroid N2 | Linux 64bit | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-neon.tar.gz) [![](https://img.shields.io/badge/build-opencl-blue)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-cl.tar.gz) [![](https://img.shields.io/badge/build-neon+cl-yellowgreen)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-neon-cl.tar.gz) |
+| HiKey960 | Linux 64bit | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-neon.tar.gz) [![](https://img.shields.io/badge/build-opencl-blue)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-cl.tar.gz) [![](https://img.shields.io/badge/build-neon+cl-yellowgreen)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-neon-cl.tar.gz) |
 
-Documentation (API, changelogs, build guide, contribution guide, errata, etc.) available at https://github.com/ARM-software/ComputeLibrary/wiki/Documentation.
+<br>
 
-Binaries available at https://github.com/ARM-software/ComputeLibrary/releases.
+| Architecture    | Operating System | Release archive (Download) |
+| ----------- | ----------- | ----------- | ----------- |
+| armv7 | Android | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-armv7a-neon.tar.gz) [![](https://img.shields.io/badge/build-opencl-blue)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-armv7a-cl.tar.gz) [![](https://img.shields.io/badge/build-neon+cl-yellowgreen)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-armv7a-neon-cl.tar.gz) |
+| armv7 | Linux | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-armv7a-neon.tar.gz) [![](https://img.shields.io/badge/build-opencl-blue)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-armv7a-cl.tar.gz) [![](https://img.shields.io/badge/build-neon+cl-yellowgreen)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-armv7a-neon-cl.tar.gz) |
+| arm64-v8a | Android | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-arm64-v8a-neon.tar.gz) [![](https://img.shields.io/badge/build-opencl-blue)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-arm64-v8a-cl.tar.gz) [![](https://img.shields.io/badge/build-neon+cl-yellowgreen)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-arm64-v8a-neon-cl.tar.gz) |
+| arm64-v8a | Linux | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-neon.tar.gz) [![](https://img.shields.io/badge/build-opencl-blue)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-cl.tar.gz) [![](https://img.shields.io/badge/build-neon+cl-yellowgreen)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8a-neon-cl.tar.gz) |
+| arm64-v8.2-a | Android | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-arm64-v8.2-a-neon.tar.gz) [![](https://img.shields.io/badge/build-opencl-blue)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-arm64-v8.2-a-cl.tar.gz) [![](https://img.shields.io/badge/build-neon+cl-yellowgreen)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-android-arm64-v8.2-a-neon-cl.tar.gz) |
+| arm64-v8.2-a | Linux | [![](https://img.shields.io/badge/build-neon-orange)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8.2-a-neon.tar.gz) [![](https://img.shields.io/badge/build-opencl-blue)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8.2-a-cl.tar.gz) [![](https://img.shields.io/badge/build-neon+cl-yellowgreen)](https://arm-software.github.io/ComputeLibrary/releases/download/v21.08/arm_compute-v21.08-bin-linux-arm64-v8.2-a-neon-cl.tar.gz) |
 
-### Supported Architectures/Technologies
+<br>
+
+
+## Supported Architectures/Technologies
 
 - Arm® CPUs:
     - Arm® Cortex®-A processor family using Arm® Neon™ technology
@@ -41,32 +77,52 @@ Binaries available at https://github.com/ARM-software/ComputeLibrary/releases.
 
 - x86
 
-### Supported Systems
+<br>
+
+## Supported Systems
 
 - Android™
 - Bare Metal
 - Linux®
 - macOS®
 - Tizen™
 
-## License and Contributions
+<br>
 
-The software is provided under MIT license. Contributions to this project are accepted under the same license.
+## Resources
+- [Tutorial: Running AlexNet on Raspberry Pi with Compute Library](https://community.arm.com/processors/b/blog/posts/running-alexnet-on-raspberry-pi-with-compute-library)
+- [Gian Marco's talk on Performance Analysis for Optimizing Embedded Deep Learning Inference Software](https://www.embedded-vision.com/platinum-members/arm/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit)
+- [Gian Marco's talk on optimizing CNNs with Winograd algorithms at the EVS](https://www.embedded-vision.com/platinum-members/arm/embedded-vision-training/videos/pages/may-2018-embedded-vision-summit-iodice)
+- [Gian Marco's talk on using SGEMM and FFTs to Accelerate Deep Learning](https://www.embedded-vision.com/platinum-members/arm/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit-iodice)
 
-### Public mailing list
-For technical discussion, the ComputeLibrary project has a public mailing list: [email protected]
-The list is open to anyone inside or outside of Arm to self subscribe.  In order to subscribe, please visit the following website:
-https://lists.linaro.org/mailman/listinfo/acl-dev
+<br>
+
+## How to contribute
+
+Contributions to the Compute Library are more than welcome. If you are interested on contributing, please have a look at our [how to contribute guidelines](https://arm-software.github.io/ComputeLibrary/latest/contribution_guidelines.xhtml).
 
 ### Developer Certificate of Origin (DCO)
-Before the ComputeLibrary project accepts your contribution, you need to certify its origin and give us your permission. To manage this process we use the Developer Certificate of Origin (DCO) V1.1 (https://developercertificate.org/)
+Before the Compute Library accepts your contribution, you need to certify its origin and give us your permission. To manage this process we use the Developer Certificate of Origin (DCO) V1.1 (https://developercertificate.org/)
 
 To indicate that you agree to the the terms of the DCO, you "sign off" your contribution by adding a line with your name and e-mail address to every git commit message:
 
 ```Signed-off-by: John Doe <[email protected]>```
 
 You must use your real name, no pseudonyms or anonymous contributions are accepted.
 
+### Public mailing list
+For technical discussion, the ComputeLibrary project has a public mailing list: [email protected]
+The list is open to anyone inside or outside of Arm to self subscribe.  In order to subscribe, please visit the following website:
+https://lists.linaro.org/mailman/listinfo/acl-dev
+
+<br>
+
+## License and Contributions
+
+The software is provided under MIT license. Contributions to this project are accepted under the same license.
+
+<br>
+
 ## Trademarks and Copyrights
 
 Android is a trademark of Google LLC.
@@ -79,3 +135,4 @@ Mac and macOS are trademarks of Apple Inc., registered in the U.S. and other
 countries.
 
 Tizen is a registered trademark of The Linux Foundation.
+