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Heterogeneous Run Time version of Caffe. Added heterogeneous capabilities to the Caffe, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original Caffe architecture which users deploy their applications seamlessly.
| Date | Stars |
|---|---|
| 2026-07-31 | 269 |
| 2026-08-06 | 269 |
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# Caffe-HRT [](LICENSE) Caffe-HRT is a project that is maintained by **OPEN** AI LAB, it uses heterogeneous computing infrastructure framework to speed up [Caffe](http://caffe.berkeleyvision.org/) and provide utilities to debug, profile and tune application performance. The release version is 0.5.0, is based on [Rockchip RK3399](http://www.rock-chips.com/plus/3399.html) Platform, target OS is Ubuntu 16.04. Can download the source code from [OAID/Caffe-HRT](https://github.com/OAID/Caffe-HRT) * The ARM Computer Vision and Machine Learning library is a set of functions optimised for both ARM CPUs and GPUs using SIMD technologies. See also [Arm Compute Library](https://github.com/ARM-software/ComputeLibrary). * Caffe is a fast open framework for deep learning. See also [Caffe](https://github.com/BVLC/caffe). ### Documents * [Installation instructions](acl_openailab/installation.md) * [User Manuals PDF](acl_openailab/user_manual.pdf) * [Performance Report PDF](acl_openailab/performance_report.pdf) * [Accuracy Report PDF](acl_openailab/accuracy_report.pdf) ### Arm Compute Library Compatibility Issues : There are some compatibility issues between ACL and Caffe Layers, we bypass it to Caffe's original layer class as the workaround solution for the below issues * Normalization in-channel issue * Tanh issue * Softmax supporting multi-dimension issue * Group issue Performance need be fine turned in the future # Release History The Caffe based version is [793bd96351749cb8df16f1581baf3e7d8036ac37](https://github.com/BVLC/caffe/tree/793bd96351749cb8df16f1581baf3e7d8036ac37). ### Version 0.5.0 - Jan 31, 2018 Support Arm Compute Library version 17.12 ### Version 0.4.1 - Nov 23, 2017 Support Arm Compute Library version 17.10 ### Version 0.4.0 - Oct 11, 2017 Support Arm Compute Library version 17.09 ### Version 0.3.0 - Aug 26, 2017 Support Arm Compute Library version 17.06 with 4 new layers added * Batch Normalization Layer * Direct convolution Layer * Locally Connect Layer * Concatenate layer ### Version 0.2.0 - Jul 2, 2017 Fix the issues: * Compatible with Arm Compute Library version 17.06 * When OpenCL initialization fails, even if Caffe uses CPU-mode,it doesn't work properly. ### Version 0.1.0 - Jun 2, 2017 Initial version supports 10 Layers accelerated by Arm Compute Library version 17.05 : * Convolution Layer * Pooling Layer * LRN Layer * ReLU Layer * Sigmoid Layer * Softmax Layer * TanH Layer * AbsVal Layer * BNLL Layer * InnerProduct Layer # Issue Report Encounter any issue, please report on [issue report](https://github.com/OAID/Caffe-HRT/issues). Issue report should contain the following information : * The exact description of the steps that are needed to reproduce the issue * The exact description of what happens and what you think is wrong
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e5e334ee852f6789, llm:Description: 'Heterogeneous Run Time version of Caffe... speed up Deep Learning on Arm-based heterogeneous embedded platform'; topics include 'caffe', 'cnn', 'dnn', 'machine-learning', 'artificial-intelligence', 'arm-gpu', 'arm-neon'
matched fp:e5e334ee852f6789, llm:Description: 'Heterogeneous Run Time version of Caffe... speed up Deep Learning on Arm-based heterogeneous embedded platform'; topics include 'caffe', 'cnn', 'dnn', 'machine-learning', 'artificial-intelligence', 'arm-gpu', 'arm-neon'
matched fp:e5e334ee852f6789, llm:Description: 'Heterogeneous Run Time version of Caffe... speed up Deep Learning on Arm-based heterogeneous embedded platform'; topics include 'caffe', 'cnn', 'dnn', 'machine-learning', 'artificial-intelligence', 'arm-gpu', 'arm-neon'
matched fp:e5e334ee852f6789, llm:Description: 'Heterogeneous Run Time version of Caffe... speed up Deep Learning on Arm-based heterogeneous embedded platform'; topics include 'caffe', 'cnn', 'dnn', 'machine-learning', 'artificial-intelligence', 'arm-gpu', 'arm-neon'