Uni10
Welcome to Uni10, the Universal Tensor Network Library.
Introduction
Uni10 is an open-source C++ library designed for the development of tensor network algorithms. Programming tensor network algorithms is tedious and prone to errors. The task of keeping track of tensor indices while performing contraction of a complicated tensor network can be daunting. It is desirable to have a platform that provides bookkeeping capability and optimization.
This software distinguishes itself from other available software solutions by providing the following advantages:
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Fully implemented in C++.
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Aimed toward applications in tensor network algorithms.
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Provides basic tensor operations with an easy-to-use interface.
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Provides a Network class to process and store the details of the graphical representations of the networks.
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Implements a heuristic algorithm to search for an optimal pairwise contraction order based on the available computation and memory resources.
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Provides a collection of Python wrappers which interact with the compiled C++ library to take advantage of the Python language for better code readability and faster prototyping, without sacrificing the speed.
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Provides behind-the-scene optimization and acceleration.
Copyright and Changes
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See GPL and LGPL for copyright conditions.
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See ChangeLog for release notes and changes.
Installation
Download
The latest Uni10 source code can be downloaded from github.
Requirements
- cmake version > 2.8.12
- C++ compiler
- BLAS and LAPACK libraries and header files
- Cuda Toolkit for GPU support
- Doxygen (for documentation)
Build
To build Un10, follow the following steps:
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Create a build directory
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Use Cmake to generate makefile
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Build library and exmamples
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Install library and examples (May require root access)
Examples
Using system c++, blas and lapack
> mkdir build
> cd build
> cmake </path/to/uni10/>
> make
> sudo make install
The installation path defaults to /usr/local/uni10.
To override the default path, use CMAKE_INSTALL_PREFIX :
> cmake -DCMAKE_INSTALL_PREFIX=</installation_path> </path/to/uni10/>
To use MKL and Intel compiler:
> cmake -DBUILD_WITH_MKL=on -DBUILD_WITH_INTEL_COMPILER=on </path/to/uni10/>
If cmake failes to find blas and lapack, specify the libraries by
> cmake -DBLAS_LIBRARIES=</path/to/blas> -DLAPACK_LIBRARIES=</path/to/lapack> </path/to/uni10/>
Build Options
| Option | Description (Default value) |
|---|---|
| BUILD_WITH_MKL | Use Intel MKL for lapack and blas (off) |
| BUILD_WITH_INTEL_COMPILERS | Use Intel C++ compiler (off) |
| BUILD_EXAMPLES | Build C++ examples (on) |
| BUILD_DOC | Build Documentation (off) |
| CMAKE_INSTALL_PREFIX | Installation location (/usr/local/uni10) |
API Documentation
API documentation can be found here
Contributors and Maintainers
- Ying-Jer Kao (National Taiwan University)
- Pochung Chen (National Tsing-Hua University)
- Yun-Hsuan Chou (National Taiwan University)
- Kelly Wu (National Tsing-Hua University)
- Yi-Hau Jhu (National Tsing-Hua University)
- Chen-Yen Lai (Los Alamos Laboratory)
- Kai-Hsin Wu (National Taiwan University)
- Chih-Yuan Lee (National Taiwan University)
- Chung-Yo Luo (National Tsing-Hua University)
Alumni
- Yun-Da Hsieh
- Tama Ma
- Sukhbinder Singh
Help and Bug Reports
Please report bugs on Github by creating issues.
Known issues
- CMake generated Xcode project not working
To Do
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GUI for generating network files
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Full GPU support