added link to ai artifacts
@@ -18,9 +18,12 @@ and customized installation/recompilation, usage, evaluation and multi-objective
of various TensorFlow implementations (CPU,CUDA,OpenCL) across diverse platforms
from mobile devices and IoT to supercomputers and TPU cloud.
-See [cKnowledge.org/ai](http://cKnowledge.org/ai), [shared optimization statistics](http://cKnowledge.org/repo)
+See [cKnowledge.org/ai](http://cKnowledge.org/ai),
+[shared optimization statistics](http://cKnowledge.org/repo),
+[reusable AI artifact in the CK format](http://cKnowledge.org/ai-artifacts)
and [online demo of CK AI API with self-optimizing DNN](http://cKnowledge.org/ai/ck-api-demo) for more details.
+
We need to have easily customizable TensorFlow builds
via JSON API to be able to plug it to our framework
for collaborative benchmarking and optimization of realistic
@@ -43,7 +46,7 @@ You can see and use all public results in the [Collective Knowledge repository](
* [dividiti](http://dividiti.com)
# License
-* [BSD](https://github.com/dividiti/ck-caffe/blob/master/LICENSE) (3 clause)
+* [BSD](https://github.com/ctuning/ck-tensorflow/blob/master/LICENSE) (3 clause)
# Prerequisites
@@ -180,12 +183,15 @@ For example, we added similar support to install, use and evaluate [Caffe/Caffe2
```
$ ck pull repo:ck-caffe2
$ ck pull repo --url=https://github.com/dividiti/ck-caffe
+$ ck pull repo:ck-mxnet
$ ck install package:lib-caffe-bvlc-master-cpu-universal --env.CAFFE_BUILD_PYTHON=ON
$ ck install package:lib-caffe2-master-eigen-cpu-universal --env.CAFFE_BUILD_PYTHON=ON
+$ ck install package --tags=mxnet
$ ck run program:caffe --cmd_key=classify
$ ck run program:caffe2 --cmd_key=classify
+$ ck run program:mxnet --cmd_key=classify
$ ck crowdbench caffe --env.BATCH_SIZE=5
$ ck crowdbench caffe2 --env.BATCH_SIZE=5 --user=i_want_to_ack_my_contribution
