OAID / Caffe Hrt
Licence: other
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.
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Caffe-HRT
Caffe-HRT is a project that is maintained by OPEN AI LAB, it uses heterogeneous computing infrastructure framework to speed up Caffe and provide utilities to debug, profile and tune application performance.
The release version is 0.5.0, is based on Rockchip RK3399 Platform, target OS is Ubuntu 16.04. Can download the source code from 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.
- Caffe is a fast open framework for deep learning. See also Caffe.
Documents
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.
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
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- The exact description of what happens and what you think is wrong
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