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I hope everyone is doing well. It is my pleasure to share two great news with you today.
First, with the kind support from many of you, the MCX grant has been successfully renewed recently by the NIH. Over the past 5 years, the MCX project has grown tremendously. We have more than quadrupled the total number of registered users (500 to 2400)
and the number of citations (250 to 1100). Many of the new methods and features have been developed,
published, and added to our open-source toolkit; mcx/mmc are now available in
Fedora and Winget, and will soon become available in Debian/Ubuntu. Our software has found use in a wide range of applications and was increasingly tested and trusted by many. We feel truly honored to contribute our small part to many of your endeavors,
and would be very much eager to share our new development with you down the path. In the next chapter of the MCX project, we have planed many exciting new milestones, many of which are already under heavy development. Stay tuned, more will come!
Secondly, I am glad to announce the arrival of MCX/MMC/MCXCL v2020 - one of the most significant updates since MCX/MMC 1.0. As a registered user, you can directly access this new release from the below URL:
All 4 major components of our MCX suite have received significant updates. the full changelog (see
http://mcx.space/wiki/?Get) is too long to include in this message. Here I am only highlight a few:
* support built-in benchmarks (--bench)
* migrate to JSON/JData encoded input/output files with compression (--dumpjson,--json, --zip, -F jnii/bnii)
* automated code building, testing and continuous integration [see announcement]
* restore progress bar support on Windows
* fixed a critical bug (affecting diffuse reflectance output when using a single pattern source)
* standalone mcx speed benchmark script [see announcement]
* finally catch up with mcx in features - added support for replay, --savedetflag, trajectory, dcs, boundary condition, photon sharing, 2d domains ...
* parallel simulation using multiple NVIDIA GPUs (previously in the nvidiaomp branch)
* support all new features in mcx, such as --bench, --dumpjson, --json, --zip, -F jnii, ...
* support pocl - open-source OpenCL library
* first official release to include GPU MMC support via OpenCL [Fang2019]
* can use multiple NVIDIA GPUs in parallel
* support photon sharing for multiple patterns [Yan2020]
* GPU MMC (-G 1) now supports most CPU/SSE MMC (-G -1) features (replay/saving seeds/dref/DMMC/..)
* new all-in-one windows installer to install everything [see announcement & attachment]
* polished 3D volume renderer with axis labels [see announcement]
* Windows winget based installation [see announcement]
I would like to particularly highlight the newly added JSON/JData output options - you can use
-F jnii or -F bnii to output JSON encoded volume/detected photon data files instead of the .mc2 and .mch output formats. Storing data to
JSON/JData format allows one to easily share and integrate mcx/mmc with other data analysis pipelines. A detailed section about these new file formats, and their
MATLAB/Python parsers have been added to the README:
I hope you enjoy our new MCX/MMC/MCXCL packages, and we are exited to kick off a new chapter of the project and continue serving this community with our latest and coolest software tools!
thank you again for your support!