# Design Doc: Remote Parameter Updater for Cluster Train

For an overview of distribute training, please refer to distributed training design doc. In this design doc, we will discuss the parameter updater that will use parameter server cclient The Client Library of Parameter Server Design Doc to manage and update parameters.

## Parameter Updater

Parameter Updater is used by trainer to manage and update parameter, there are mainly two kind of parameter updater: local and remote, since this design is for cluster train, we will only discuss remote parameter updater here.

### Remote Parameter Updater

Remote Parameter Updater manage parameters through remote parameter server with the client that communicate with pserver(The Client Library of Parameter Server Design Doc)

In PaddlePaddle Python V2 API, trainer is implemented in python, and the trainer will hold a instance of parameter updater and call it’s functions directly. In this design, we will also expose the api of RemoteParameterUpdater to python with swig.

#### Sparse Remote Parameter Updater

Since we will only implement dense parameter management new, the mechanism for sparse parameter will be discussed in next stage.

### Interface Design

TBD