Mesh-based Monte Carlo, or MMC, is a Monte Carlo simulation package designed for simulating photon transport in 3D heterogeneous media. MMC can use a volumetric mesh to represent a complex domain, making it computationally and memory efficient.
MMC supports multi-threading based parallel computing. You can obtain a nearly linear speed-up when using more CPU cores in your simulation. Starting from version 0.8, MMC also supports the Single-Instruction Multiple-Data (SIMD) parallism on modern CPUs, allowing MMC to take further advantage in parallel computing.
The download link to this release can be accessed from here.
MMC 0.9.0 is an important maintenance release. It contains fixes to several high priority bugs and a number of major feature additions. Thanks to the contribution of Dr. Stefan Carp, MMC now supports photon momentum transfer simulations and becomes useful for diffuse correlation spectroscopy (DCS) studies.
The new release of v0.9.0 was highly polished upon the previous version, v0.8.0, published over 6 months ago. The key changes include:
Pre-compiled MMC binaries are provided for Windows (32/64bit), Linux (32/64bit) and Mac OS (32/64bit). In all cases, a binary compiled with a fast SFMT-19937 RNG (mmc_sfmt) is included along with the default binary (mmc) using the GLIBC RNG.
Using mmc_sfmt is generally recommended over mmc. The highest simulation speed can be typically achieved by using
mmc_sfmt -M S -C 0 ....
One can recompile all binaries using an Intel C++ Compiler. It can generate binaries up to 25% faster than the equivalent binaries compiled with GCC.
The "multicore" MMC binaries can be used on almost all computers (even those with a single-core processor).
The "SSE4" binaries require your computer to support SSE4 instructions. This can be determined by using the following command on Linux/MacOS
grep 'sse4' /proc/cpuinfo
or using a freeware "CPU-Z" on windows. If you attempt to run the SSE4 on an unsupported computer, you will get an error when executing the binary. In that case, you should switch to the "multicore" binaries.
The next release of MMC will be version 1.0. In this release, we will include wide-field illumination and MPI support to MMC, as a result of a collaboration between me and Dr. Xavier Intes and Jin Chen from RPI (this has been implemented and tested, Jin is now working on final polishing of the code). Stay tuned if you are interested.