Celebrate the arrivals of MCX 1.0 and MMC 1.0
August 24, 2018
After nearly 10 years of continuous development, it is our great pleasure to announce that MCX 1.0 (v2018) has finally arrived! In the meantime, MMC has also arrived at its v1.0 milestone, after its initially publication in 2010. Moreover, we also proudly announce the first stable release of MCX-OpenCL (or MCXCL) - a "clone" of MCX that can run on nearly all CPUs and GPUs across many vendors.
These releases represent an important milestone for the MCX project (http://mcx.space), and signifies that MCX/MMC has grown from unique research ideas to become mature, robust, full-featured, and general purpose Monte Carlo simulation platform that empowers thousands of researchers and students around the world to explore, to teach and to create. This also marks the start of a wonderful new journey along which many exciting new ideas, methods, features await ahead.
As of today, our combined registered MCX and MMC user number (with unique emails) has exceeded 1,500, with people coming from every corner of the world. The total download number in the past 7 years has exceeded 22,500 from our Sourceforge site alone. There are over 780 academic publications cited our works, and more than 1,200 questions/replies were received in our mailing lists, subscribed by over 250 active users. We are proud of these achievements and feel deeply honored to contribute, even in a small way, to many ongoing exciting new research, and are committed to continue dedicating our efforts in maintaining and improving our software. We will continue working with every one of you, addressing your concerns and new feature requests, bringing the latest and fastest software to you with transparency and openness.
Today, we celebrate MCX/MMC 1.0, we thank all the hard-works from the developers' team, particularly those PhD students who had made MCX a fast and better software - Fanny Nina-Paravecino, Leiming Yu, Ruoyang Yao, Yaoshen Yuan, Shijie Yan and Anh Phong Tran, as well as the continual support and guidance from collaborators, Dr. David Kaeli and Dr. Xavier Intes. We also thank all the valuable feedback received from our users, your bug reports and constructive discussions are crucial for us to improve our software. Last, but not the least, we thank NIH/NIGMS for funding (R01-GM114365) this endeavor. It is not possible for us to get where we are today without this support.
Today, we also kickoff the new development cycle for MCX 2.0! We will continue accelerating our software by taking advantage of emerging GPU architectures, new hardware resources and algorithm optimizations, in the meantime, focusing on usability and broader dissemination.
You can directly access the new packages at the below site
https://sourceforge.net/projects/mcx/files/
Several critical bugs have been fixed in the new MCX codes. I urge everyone to upgrade from an old release to the latest version to avoid getting incorrect results. The details of these bugs can be found here
http://mcx.space/wiki/index.cgi?Doc/ReleaseNotes/v2018#About_this_release
Starting from this release, we provide an all-in-one package named MCXStudio - it contains all 7 modules (MCX, MCX-CL, MMC, MCXLAB, MCXLAB-CL, MMCLAB and mcxstudio GUI) precompiled for Windows/Linux and Mac. For new users, we suggest you to try the GUI (mcxstudio) in the all-in-one package as a quick-start.
We also completely redesigned our wiki to make information easier to find
you can find the release notes and detailed video tutorials in the below links
For those of you who could not run MCX due to the lack of NVIDIA GPUs, please try our MCX-CL (and MCXLAB-CL) software - they are highly compatible with MCX (MCXLAB) and can utilize AMD/Intel CPUs/GPUs for high-throughput MC simulations. In our paper published earlier this year, the simulation speed on AMD GPUs is comparable to those from NVIDIA cards. Please see our paper for details.
https://doi.org/10.1117/1.JBO.23.1.010504
Please continue using our user forums (http://mcx.space/wiki/?Help ) to provide your feedback or suggestions.
Enjoy the new software and happy modeling!
Qianqian Fang, PhD Northeastern University, Boston