A high-performance, on-device neural network inference framework
## Goal
+
This project _nnfw_ aims at providing a high-performance, on-device neural network (NN) inference
framework that performs inference of a given NN model on processors, such as CPU, GPU, or NPU, in
-the target platform, such as Tizen and Smart Machine Platform (SMP).
+the target platform, such as the Linux kernel based OS including Tizen.
## Project Documents
+
- [Roadmap](docs/roadmap.md)
- [SW Requirement Specification](docs/project/2018_requirement_specification.md)
- [SW High Level Design](docs/project/2018_high_level_design.md)
## Getting started
+
- For the contribution, please refer to our [contribution guide](docs/HowToContribute.md).
- You can also find how-to documents [HERE](docs/howto.md).
- For features not listed, [create a new issue](https://github.sec.samsung.net/STAR/nnfw/issues/new).
Sooner or later, the maintainer will tag the `FEATURE_REQUEST` label and appear on the list.
-We expect most current feature requests to be focused on operator kernel implementations.
+We expect one of the most frequent feature requests would be the operator kernel implementation.
It is good to make a request, but it is better if you contribute by yourself. See the following guide,
[How to Implement Operator Kernel](docs/HowToImplementOperatorKernel.md), for help.
We are looking forward to your participation.
Thank you in advance!
+
+----
+
+## Notice
+
+We are currently working on [_nncc_](https://github.sec.samsung.net/STAR/nncc) as a sibling project.
+In our plan, the two projects will soon be integrated into one, and focusing on their roles as
+front-end(_nncc_) and back-end(_nnfw_), respectively. It will accompany the physical combination of
+the github repo. You can find the latest roadmap of the integrated project
+[here](https://github.sec.samsung.net/orgs/STAR/projects/1).