Permalink
Browse files

Update README.md

  • Loading branch information...
harsha-simhadri committed Dec 2, 2017
1 parent 0ec67ab commit 734c7bed9ef770196d3440178525d8e76ddf5178
Showing with 5 additions and 5 deletions.
  1. +5 −5 README.md
View
@@ -15,16 +15,16 @@ We welcome contributions, comments and criticism. For questions, please [email H
[People](http://harsha-simhadri.org/EdgeML/People/) who have contributed to this [project](https://www.microsoft.com/en-us/research/project/resource-efficient-ml-for-the-edge-and-endpoint-iot-devices/).
### Requirements
* Linux.
* Linux:
* gcc version 5.4. Other gcc versions above 5.0 could also work.
* We developed the code on Ubuntu 16.04LTS. Other linux versions could also work.
* You can either use the Makefile in the root, or cmake via the build directory (see below).
* For Windows 10
* Visual Studio 2015. For this, use cmake (see below)
* Windows 10:
* Visual Studio 2015. Use cmake (see below).
* For Anniversary Update or later, one can use the Windows Subsystem for Linux, and the instructions for Linux build.
* On both Linux and Windows, you need an implementation of BLAS, sparseBLAS and vector math calls.
* On both Linux and Windows 10, you need an implementation of BLAS, sparseBLAS and vector math calls.
We link with the implementation provided by the [Intel(R) Math Kernel Library](https://software.intel.com/en-us/mkl).
Please download later versions (2017v3+) of MKL as far as possible.
The code can be made to work with other math libraries with a few modifications.
@@ -65,7 +65,7 @@ cmake -G "Visual Studio 14 2015 Win64" -DCMAKE_BUILD_TYPE=Release ..
```
Finally, open `EdgeML.sln` in VS2015, build and run.
Both Linux and Windows10, cmake builds will generate four executables _BonsaiTrain_, _BonsaiPredict_, _ProtoNNTrain_ and _ProtoNNPredict_ in <EDGEML_ROOT>.
For both Linux and Windows10, cmake builds will generate four executables _BonsaiTrain_, _BonsaiPredict_, _ProtoNNTrain_ and _ProtoNNPredict_ in <EDGEML_ROOT>.
### Download a sample dataset
Follow the bash commands given below to download a sample dataset, USPS10 to the repository. Bonsai and ProtoNN come with sample scripts to run on the usps10 dataset. EDGEML_ROOT is defined in the previous section.

0 comments on commit 734c7be

Please sign in to comment.