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How to get MMC

1. Download the Latest Stable Release
2. Download Development Snapshot from Git (not fully tested)
2.1. Get the latest source code
2.2. Contribute to MCX
3. References

1. Download the Latest Stable Release

MMC 2017.3 (v1.0-RC1, codename Haw Flakes), released on Apr. 02, 2017

Please read the Release notes before downloading the software.

Please download MMC 2017.3 (aka v1.0-RC2, Cotton Candy) at our registration/download page. We are greatly appreciated if you can tell us a little bit about you and your related research by registering your copy of mmc. Binary executable (for 64bit machines) and source code packages are both provided. The non-SSE versions are labeled as "multicore" in the package name. All SSE4-tagged binaries are considered to have better speed, but requires your CPU to support SSE4 (or it will cause crash).

 

To compile from the source code, please follow the instructions in this section.

2. Download Development Snapshot from Git (not fully tested)

2.1. Get the latest source code

The latest code can be downloaded from the project's Github repository. This can be done using the following git command.

 git clone https://github.com/fangq/mcx.git mcx

After downloading the source code, please follow the instructions to compile and run the software.

In order to use the above git command, make sure you have installed git client on your system. If you are using a Debian-based GNU/Linux system (such as Ubuntu, Knoppix etc), you can install git by

 sudo apt-get install git-core
if you are using a Redhat-based GNU/Linux system (such as Fedora, CentOS etc), you can do this by
 su -c 'yum install git-core'
If your operating system is Windows, we recommend you installing TortoiseGit.

2.2. Contribute to MCX

If you are interested in contributing codes, testing data and documentation to MCX, please fork this project on github. Once your feature is fully developed in your forked branch, please send a pull request in order for MCX's developer to review your changes.

3. References

The author of this software would like you to acknowledge the use of this software in your related publications by citing the following paper:

You can also find more algorithm and implementation details about MMC in this paper.

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