Parameter server framework for distributed machine learning
Перейти к файлу
Fei Gao 2af610bf25 Delete second_order_gradient_updater.h 2016-04-15 18:05:34 +08:00
Test merge log from multiverso-next 2016-04-14 12:06:41 +08:00
include adjust vs project structure 2016-04-14 16:54:43 +08:00
src adjust vs project structure 2016-04-14 16:54:43 +08:00
.gitignore adjust vs project structure 2016-04-14 16:54:43 +08:00
CMakeLists.txt merge log from multiverso-next 2016-04-14 12:06:41 +08:00
LICENSE refine the CMakeList 2015-11-16 23:36:27 +08:00
Multiverso.sln adjust vs project structure 2016-04-14 16:54:43 +08:00
README.md recover README.md 2016-04-14 13:16:11 +08:00

README.md

multiverso

Multiverso is a parameter server based framework for training machine learning models on big data with numbers of machines. It is currently a standard C++ library and provides a series of friendly programming interfaces. With such easy-to-use APIs, machine learning researchers and practitioners do not need to worry about the system routine issues such as distributed model storage and operation, inter-process and inter-thread communication, multi-threading management, and so on. Instead, they are able to focus on the core machine learning logics: data, model, and training.

For more details, please view our website http://www.dmtk.io.

Build

Linux (Tested on Ubuntu 12.04)

  1. Run mkdir build
  2. Run cd build
  3. Run cmake ..
  4. Run make

Windows

For windows users, please refer to README in windows folder.

Current distributed systems based on multiverso: