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author | xuhaibing <hxu@openailab.com> | 2017-09-24 23:15:59 +0800 |
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committer | GitHub <noreply@github.com> | 2017-09-24 23:15:59 +0800 |
commit | 1dc332ae97ae5b1c8129b4ea7748d99161863813 (patch) | |
tree | edc338a35979e94884e2c6aa5db16ab415c65085 | |
parent | 3a246fe89fc038d82c4f83c725f5c889128449e2 (diff) | |
download | caffeonacl-1dc332ae97ae5b1c8129b4ea7748d99161863813.tar.gz caffeonacl-1dc332ae97ae5b1c8129b4ea7748d99161863813.tar.bz2 caffeonacl-1dc332ae97ae5b1c8129b4ea7748d99161863813.zip |
Update release_notes.md
-rw-r--r-- | acl_openailab/release_notes.md | 9 |
1 files changed, 4 insertions, 5 deletions
diff --git a/acl_openailab/release_notes.md b/acl_openailab/release_notes.md index 78a91f32..9bc4c4b9 100644 --- a/acl_openailab/release_notes.md +++ b/acl_openailab/release_notes.md @@ -9,12 +9,11 @@ The release version is 0.3.0, is based on Rockchip RK3399 Platform, target OS is * Caffe is a fast open framework for deep learning. See also [Caffe](https://github.com/BVLC/caffe).
## 1.1 CaffeOnACL :
-- Hardware platform : Rockchip RK3399. See also [RK3399 SoC](http://www.rock-chips.com/plus/3399.html)
-- Software platform : Ubuntu 16.04
+The release is validated on [Rockchip RK3399](http://www.rock-chips.com/plus/3399.html), Operation system is Ubuntu 16.04.
-- Installation Guide : Refer to [Installation](installation.md)
-- User Manual : Refer to [User Manual](https://github.com/OAID/CaffeOnACL/blob/master/acl_openailab/user_manual.pdf)
-- Performance Report : Refer to [Performance Report](https://github.com/OAID/CaffeOnACL/blob/master/acl_openailab/performance_report.pdf)
+* [Installation instructions](https://github.com/OAID/CaffeOnACL/blob/master/acl_openailab/installation.md)
+* User Manual : Refer to [User Manual](https://github.com/OAID/CaffeOnACL/blob/master/acl_openailab/user_manual.pdf)
+* Performance Report : Refer to [Performance Report](https://github.com/OAID/CaffeOnACL/blob/master/acl_openailab/performance_report.pdf)
## 1.2 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
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