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Release Notes for Mesh-based Monte Carlo 1.0-RC3 (2017.7)

code name: Haw Flakes, released on July 7, 2017

Click this link to download MMC/MMCLAB v2017.7

Acknowledgement: This software release is made possible with the funding support from NIH/NIGMS under the grant number R01-GM114365.

1. Introduction
2. About this release
3. What's new compared to previous release
3.1. new features
3.2. other improvement
4. System requirements
5. Known issues
6. Reference

1. Introduction

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) parallelism on modern CPUs, allowing MMC to take further advantage in parallel computing.

MMCLAB is the MATLAB mex version of the MMC software. It can be directly called inside MATLAB.

This is the 4th release of our new time-based release strategy. We plan to announce 4 releases each year - one release per 3 months.

The download link to this release can be accessed from here.

2. About this release

MMC/MMCLAB 1.0-RC3 is the 3rd release candidate (RC) to the upcoming milestone, version 1.0, of MMC. It contains a number of bug fixes and four new forms of source types. The Makefile of the source code was also improved to support automatic nightly-build.

3. What's new compared to previous release

The v2017.7 release was improved upon the previous version, v2017.3 by fixing a list of bugs. They are:

3.1. new features

  1. !!key!! add flag --atomic to select use or not use atomic operations
  2. !!key!! add musmap for nodal based Jacobian (validated for homo media)
  3. !!key!! support rotation angle in expanded src domain
  4. support older version of MATLAB
  5. fix rootpath handling, move MeshID and InitElem to Domain section
  6. fix basisorder verbose flag,fix terminal width initial value
  7. add --debugphoton flag to print debug info for selected photon ID
  8. avoid static TLS error in matlab by linking with libiomp5 instead of libgomp

3.2. other improvement

  1. avoid launching 0-energy photons, improved upon c4a87df
  2. update replay testing statement
  3. support mcx detpt and old mmc output format

Pre-compiled MMC binaries are provided for Windows, Linux and Mac OS. In all cases, a binary compiled with SSE4-accelerated ray-tracing algorithms is provided for each platform.

The best simulation speed can be typically achieved by using

  mmc -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 detailed change logs can be found in the ChangeLog and Git commit history pages.

4. System requirements

Although MMC/MMCLAB can be executed independently once all input data (including mesh data) are provided, most pre- and post-processing scripts in both packages require the installation of Iso2Mesh Toolbox - a MATLAB based 3D mesh generator. Please browse http://iso2mesh.sf.net for download and installation information.

The default "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 recompile MMC using "make omp" command.

5. Known issues

  • One must use savemmcmesh.m to generate all mesh input files for MMC; otherwise, the element orientation is not guaranteed.
  • Currently, this code only supports element-based optical properties; nodal-based optical properties (for continuously varying media) will be added in a future release
  • The maximum photon number per MMC session is 2^32-1=4,294,967,295, if you need to run a large number of photons, we suggest you splitting the job into smaller jobs with each one running a smaller chunk of photons (for example 1E8). Each job should initialized with a different seed (-E).

6. Reference

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