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Latest Release: 6.3.0

Table of Contents

Documents

The following listing gives those documents that are relevant to the latest release.

M. E. Rising, J. C. Armstrong, S. R. Bolding, F. B. Brown, J. S. Bull, T. P. Burke, A. R. Clark, D. A. Dixon, R. A. Forster III, J. F. Giron, T. S. Grieve, H. G. Hughes III, C. J. Josey, J. A. Kulesza, R. L. Martz, A. P. McCartney, G. W. McKinney, S. W. Mosher, E. J. Pearson, C. J. Solomon Jr., S. Swaminarayan, J. E. Sweezy, S. C. Wilson, A. J. Zukaitis. MCNP® Code Version 6.3.0 Release Notes. Los Alamos National Laboratory Tech. Rep. LA-UR-22-33103, Rev. 1. Los Alamos, NM, USA. January 2023.
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J. A. Kulesza, T. R. Adams, J. C. Armstrong, S. R. Bolding, F. B. Brown, J. S. Bull, T. P. Burke, A. R. Clark, R. A. Forster III, J. F. Giron, T. S. Grieve, C. J. Josey, R. L. Martz, G. W. McKinney, E. J. Pearson, M. E. Rising, C. J. Solomon Jr., S. Swaminarayan, T. J. Trahan, S. C. Wilson, A. J. Zukaitis. MCNP® Code Version 6.3.0 Theory & User Manual. Los Alamos National Laboratory Tech. Rep. LA-UR-22-30006, Rev. 1. Los Alamos, NM, USA. September 2022.
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J. S. Bull, J. A. Kulesza, C. J. Josey, M. E. Rising. MCNP® Code Version 6.3.0 Build Guide. Los Alamos National Laboratory Tech. Rep. LA-UR-22-32851, Rev. 1. Los Alamos, NM, USA. December 2022.
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C. J. Josey, A. R. Clark, J. A. Kulesza, E. J. Pearson, M. E. Rising. MCNP® Code Version 6.3.0 Verification & Validation Testing. Los Alamos National Laboratory Tech. Rep. LA-UR-22-32951, Rev. 1. Los Alamos, NM, USA. December 2022.
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J. S. Bull. MCNP6.2 and MCNP6.3 Performance Comparison. Los Alamos National Laboratory Presentation LA-UR-23-30469, Rev. 1. Los Alamos, NM, USA. September 2023.
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J. C. Armstrong. MCNP6.3 Executions in Parallel on Snow. Los Alamos National Laboratory Presentation LA-UR-23-30411, Rev. 1. Los Alamos, NM, USA. September 2023.
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M. E. Rising. MCNP6 Developments: A 2022-23 Year in Review. Los Alamos National Laboratory Presentation LA-UR-23-30362, Rev. 1. Los Alamos, NM, USA. September 2023.
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M. R. Dzur, J. C. Armstrong, C. A. D'Angelo. Oktavian Modeling with MCNP6.3. Los Alamos National Laboratory Presentation LA-UR-23-30240. Los Alamos, NM, USA. September 2023.
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J. A. Kulesza. Tutorial: Installing MCNP6.3 on Microsoft Windows. Los Alamos National Laboratory Video LA-UR-23-30187. Los Alamos, NM, USA. September 2023.
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C. J. Solomon Jr., C. R. Bates, M. J. Marcath. MCNP Intrinsic Source Constructor (MISC): A User's Guide. Los Alamos National Laboratory Tech. Rep. LA-UR-22-32893. Los Alamos, NM, USA. December 2022.
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C. J. Solomon Jr., C. R. Bates, J. A. Kulesza, M. J. Marcath. The Intrinsic Source Constructor Package: Installation and Use. Los Alamos National Laboratory Tech. Rep. LA-UR-22-31848. Los Alamos, NM, USA. November 2022. ISC Version 2.1.
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J. A. Kulesza. MCNP® Code Version 6.3.0 Unstructured-mesh HDF5-based Output Verification. Los Alamos National Laboratory Tech. Rep. LA-UR-22-30007. Los Alamos, NM, USA. September 2022.
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J. A. Kulesza. MCNP® Code Version 6.3.0 Unstructured-mesh Quality Metrics & Assessment. Los Alamos National Laboratory Tech. Rep. LA-UR-20-27150, Rev. 1. Los Alamos, NM, USA. September 2022.
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C. R. Bates, S. R. Bolding, C. J. Josey, J. A. Kulesza, C. J. Solomon Jr., A. J. Zukaitis. The MCNPTools Package: Installation and Use. Los Alamos National Laboratory Tech. Rep. LA-UR-22-28935. Los Alamos, NM, USA. August 2022. MCNPTools Version 5.3.
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C. J. Josey, J. L. Conlin. LANL Nuclear Data Manager Format Specification v1.0. Los Alamos National Laboratory Tech. Rep. LA-UR-22-28306. Los Alamos, NM, USA. August 2022.
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J. A. Kulesza, C. J. Josey. Fission Matrix Processing Using the MCNP6.3 HDF5 Restart File. Los Alamos National Laboratory Tech. Rep. LA-UR-22-20980, Rev. 1. Los Alamos, NM, USA. May 2022.
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S. R. Bolding, J. A. Kulesza, M. J. Marcath, M. E. Rising. Particle Track Output (PTRAC) Improvements, Parallelism, and Post-Processing. Los Alamos National Laboratory Presentation LA-UR-21-26562. Los Alamos, NM, USA. July 2021.
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M. E. Rising, C. J. Josey, J. A. Kulesza. Improved Verification and Validation Testing and Tools. Los Alamos National Laboratory Presentation LA-UR-21-26448, Rev. 1. Los Alamos, NM, USA. July 2021.
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J. L. Conlin, R. A. Siggins. Nuclear Data Activities Supporting MCNP6.3. Los Alamos National Laboratory Presentation LA-UR-21-26372. Los Alamos, NM, USA. July 2021.
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J. A. Kulesza, J. C. Armstrong, C. J. Josey, S. Swaminarayan, J. L. Alwin, T. C. McClanahan, J. B. Spencer, J. T. Goorley, K. C. Kelley, P. S. Khalsa, G. A. Failla. MCNP Unstructured Mesh Visualization & Post-processing Techniques. Los Alamos National Laboratory Presentation LA-UR-21-26365. Los Alamos, NM, USA. July 2021.
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C. J. Josey, J. A. Kulesza. Improved FMESH Capabilities in the MCNP 6.3 Code. Los Alamos National Laboratory Presentation LA-UR-21-26363. Los Alamos, NM, USA. July 2021.
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J. A. Kulesza, J. C. Armstrong, T. C. McClanahan, S. Swaminarayan. MCNP Unstructured Mesh Elemental Quality Assessment. Los Alamos National Laboratory Presentation LA-UR-21-26362. Los Alamos, NM, USA. July 2021.
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C. J. Josey, S. R. Bolding. A Guide to Building the MCNP 6.3 Code from Source. Los Alamos National Laboratory Presentation LA-UR-21-26345. Los Alamos, NM, USA. July 2021.
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M. E. Rising, T. R. Adams, J. C. Armstrong, S. R. Bolding, F. B. Brown, J. S. Bull, R. A. Forster III, C. J. Josey, J. A. Kulesza, A. J. Zukaitis, J. E. Sweezy, S. Swaminarayan, L. Casswell. Upcoming MCNP6.3® Release: New Features and Improvements. Los Alamos National Laboratory Presentation LA-UR-21-26276, Rev. 1. Los Alamos, NM, USA. July 2021.
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R. B. Wilkerson, G. W. McKinney, M. E. Rising, J. A. Kulesza. MCNP Reactor Multigroup Tally Options Verification. Los Alamos National Laboratory Tech. Rep. LA-UR-20-27819. Los Alamos, NM, USA. October 2020.
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C. J. Josey. Converting the MCNP Runtape to HDF5. Los Alamos National Laboratory Tech. Rep. LA-UR-19-29393. Los Alamos, NM, USA. September 2019.
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F. B. Brown, C. J. Josey, S. Henderson, W. R. Martin. Automated Acceleration and Convergence Testing for Monte Carlo Criticality Calculations. Los Alamos National Laboratory Tech. Rep. LA-UR-19-23887. Los Alamos, NM, USA. August 2019.
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Build Guide Details

To assist with building the MCNP code, this section describes operating system-specific details that will evolve over time (e.g., links to external websites). If details are found out of date, links found broken, etc., please contact the MCNP Team to notify them of the issue so that this webpage can be kept up to date.

The MCNP Development Team recommends using the Intel compilers which are available with the no-cost Intel® oneAPI development tools. These tools have several useful components, but only the C/C++ and Fortran compilers are needed to build MCNP:

Both of these compilers are included in the Intel® oneAPI HPC Toolkit. They can also be installed as individual packages.

Linux

The Intel® oneAPI Toolkits Installation Guide for Linux OS provides detailed instructions on how to get and install the Intel® oneAPI packages using different installer modes and package managers. After installation, review the Intel configuration guide for instructions on how to install the required GNU development tools.

Dependencies

chrpath The chrpath (binary runpath modification) utility is used during the packaging stage to help bundle the libraries used by the MCNP executables. It can be installed using the distribution's package manager.
CMake CMake can be obtained from the distribution's package manager or directly from the CMake website.
Git The Git Linux download web page has instructions on how to install Git for several distributions.
HDF5 HDF5's development package may be available from the distribution's package manager. The full name of the package varies, but it usually contains the phrase "hdf5-devel". Installation packages can also be downloaded from the Unix HDF5 v 1.12.1 website .
Make Install Make using the distribution's package manager.
MPI Install OpenMPI using the distribution's package manager. For parallel (MPI-enabled) HDF5, also install the HDF5 OpenMPI development package, if available, from the package manager. If a parallel version is not available, it must be built from the HDF5 source code.
Python The distribution's package manager can be used to install Python and individual Python modules. Note that installing the h5py package will install both Python and the numpy package as dependencies.
X11 The X11 development package is usually available from the distribution's package manager and can be found with a search for "libx11-dev" or "libx11-devel".

Building HDF5

Download the CMake-hdf5-1.12.1.tar.gz file from the HDF5 downloads page, CMake-based HDF5 source code, from the HDF Group website. In a terminal, enter the commands: 

gunzip CMake-hdf5-1.12.1.tar.gz
tar -xf CMake-hdf5-1.12.1.tar
cd CMake-hdf5=1.12.1
ctest -S HDF5config.cmake,BUILD_GENERATOR=Unix -C Release -VV -O hdf5.log

For parallel HDF5 1.12.1, replace the ctest command line with:

ctest -S HDF5config.cmake,BUILD_GENERATOR=Unix,HPC=ON -C Release -VV -O hdf5-mpi.log

To install HDF5, copy the HDF5-1.12.1-Linux.tar.gz file to the installation directory and enter these commands:

tar -xf HDF5-1.12.1-Linux.tar.gz
export HDF5_DIR="$(pwd)/HDF5-1.12.1-Linux/HDF_Group/HDF5/1.12.1/share/cmake"

macOS

The Intel® oneAPI Toolkits Installation Guide for macOS provides detailed instructions on how to get and install the Intel® oneAPI packages using different installer modes and package managers.

Dependencies

There are a variety of package managers available for macOS. The MCNP Development Team typically uses HomeBrew and/or Spack software package manager to provide such capability. As such, when a package manager is referred to in this section, it will refer to such software that provides this type of capability.

CMake CMake can be obtained from a third-party package manager or directly from the CMake website.
Git Git is included with the Xcode Command Line Tools. Other macOS download options can be found on the Git macOS downloads web page.
HDF5 HDF5 can be obtained from a third-party package manager. The HDF Group does not provide macOS installers.
Make Make is included with the Xcode Command Line Tools. Make can also be obtained from a third-party package manager.
MPI Install OpenMPI from a third-party package manager. A parallel (MPI-enabled) version of HDF5 may also be available from such package managers, and can be used if that is the case. A parallel version can also be built from the HDF5 source code.
Python Python can be obtained from a third-party package manager or from the Python macOS page. Once installed, the pip command can be used to install the h5py package, which will also install the numpy package.
X11 X11 capability on macOS is provided by the XQuartz package, which includes the X11 development files that are required to build the code.

Building HDF5

On macOS, the CMake-based version of HDF5 will only build with AppleClang, which causes problems for parallel HDF5. So, download the hdf5-1.12.1.tar.gz file from the HDF5 downloads page, Autoconf-based HDF5 source code, from the HDF5 website. Then enter: 

export HDF5_ROOT=<install path>
gunzip hdf5-1.12.1.tar.gz
tar -xf hdf5-1.12.1.tar
cd hdf5-1.12.1
./configure --prefix=$HDF5_ROOT
make -j && make test && make install

For parallel HDF5, replace the configure line with:

CC=mpicc ./configure --enable-parallel --prefix=$HDF5_ROOT

Windows

The Intel® oneAPI Toolkits Installation Guide for Windows provides detailed instructions on how to get and install the Intel® oneAPI packages using different installer modes and package managers. Note that the Intel compilers rely on the Microsoft C/C++ compiler, which are included with the no-cost Build Tools for Visual Studio package as well as Visual Studio.

 Caution

As of Visual Studio 2022, version 17.4.0, the Intel C++ Compiler Classic (icl) versions older than 2021.8 will not compile the MCNP code. For these versions of Visual Studio, icl version 2021.8 or higher must be installed. These versions of icl are distributed with the Intel® oneAPI HPC Toolkit version 2023.0 and higher.

Dependencies

CMake CMake and the required Ninja build tool are included in Visual Studio and in the freely available Build Tools for Visual Studio package. It can also be downloaded from the CMake website.
Git Git for Windows is available here.
HDF5 Version 1.12.1 of HDF5 for Windows built with Visual Studio 2019 is available in the hdf5-1.12.1-Std-win10_64-vs16.zip file on the HDF5 downloads page here. This package also works with Visual Studio 2022.
MPI The MCNP installation package includes an option to install Microsoft MPI. It is also available directly from Microsoft at Microsoft MPI. No pre-built parallel (MPI-enabled) HDF5 libraries are available for Windows; such libraries must be built from the HDF5 source code.
Python Python can be installed from the Microsoft Store or from the Python Windows page. Once installed, the pip command can be used to install the h5py package, which will also install the numpy package.
X11 The X11 development libraries required by Windows are included with the MCNP code distribution.

Creating a Visual Studio Project Solution File Using the Intel CMake Toolset

CMake can also create the MCNP project solution file, mcnp.sln for use with Visual Studio. Note that compiling the MCNP code with Visual Studio will take longer than using the Ninja build tool.

Open a command prompt and create a new the MCNP build tree folder, build_VS. Go to the new folder and enter the following CMake command, depending on which version of Visual Studio is used:

Visual Studio 2019

cmake -G "Visual Studio 16 2019" ..\ -T "Intel C++ Compiler 19.2" -DCMAKE_Fortran_FLAGS_INIT=/MP

Visual Studio 2022

cmake -G "Visual Studio 17 2022" ..\ -T "Intel C++ Compiler 19.2" -DCMAKE_Fortran_FLAGS_INIT=/MP

The -DCMAKE_Fortran_FLAGS_INIT=/MP CMake flag tells the Fortran compiler to process the source code in parallel.

To open the MCNP project in Visual Studio, enter the command: 

devenv mcnp.sln

Building HDF5

Download the CMake-hdf5-1.12.1.zip file from the HDF5 downloads page, CMake-based HDF5 source code, from the HDF Group website. Build instructions depend on the version of Visual Studio used.

Visual Studio 2019

In a command prompt, enter the commands:

chdir <path to extracted folder>
ctest -S HDF5config.cmake,BUILD_GENERATOR=VS201964 -C Release -VV -O hdf5.log

Visual Studio 2022

Unfortunately, the HDF5 CMake build system is not setup to use Visual Studio 2022. To add Visual Studio 2022 to the CMake configuration file, open the file CMake-hdf5-1.12.1/HDF5config.cmake and scroll down to line 164: 

164:    set (SITE_COMPILER_VERSION "11")
165:  else ()
166:    message (FATAL_ERROR "Invalid BUILD_GENERATOR must be - Unix, VS2019, VS201964, VS2017, or VS201764, VS2015, VS201564")

Add these lines between lines 164 and 165:

  elseif (BUILD_GENERATOR STREQUAL "VS202264")
    set (CTEST_CMAKE_GENERATOR "Visual Studio 17 2022")
    set (CMAKE_GENERATOR_ARCHITECTURE "x64")
    set (SITE_OS_BITS "64")
    set (SITE_COMPILER_NAME "vs2022")
    set (SITE_COMPILER_VERSION "17")

Next, open a command prompt and enter the commands: 

chdir <path to extracted folder>
ctest -S HDF5config.cmake,BUILD_GENERATOR=VS202264 -C Release -VV -O hdf5.log

For either version of Visual Studio, after this process is finished, extract the generated HDF5-1.12.1-win64.zip file to a location of your choice.

To build parallel HDF5, open the file HDF5options.cmake and scroll down to line 80:

79:     set (ADD_BUILD_OPTIONS "${ADD_BUILD_OPTIONS} -DHDF5_BUILD_JAVA:BOOL=OFF")
80:     set (ADD_BUILD_OPTIONS "${ADD_BUILD_OPTIONS} -DHDF5_ENABLE_THREADSAFE:BOOL=OFF")
81:  endif()

Insert this line after line 80:

    set (ADD_BUILD_OPTIONS "${ADD_BUILD_OPTIONS} -DMPI_GUESS_LIBRARY_NAME=MSMPI")

This option assures that CMake uses Microsoft MPI to build parallel HDF5

Next, replace the ctest command from above with:

ctest -S HDF5config.cmake,BUILD_GENERATOR=VS201964,MPI=ON -C Release -VV -O hdf5-mpi.log -D LOCAL_SKIP_TEST=ON

or 

ctest -S HDF5config.cmake,BUILD_GENERATOR=VS202264,MPI=ON -C Release -VV -O hdf5-mpi.log -D LOCAL_SKIP_TEST=ON

depending on the Visual Studio version.

Tests typically need to be disabled on Windows machines, as some of the parallel tests tend to lock up on hard drives formatted with NTFS. If one is using a true parallel file system, that option can be omitted.

Issues Identified After Release

The release notes that accompany this version identify known issues at the time of release. This webpage lists known issues identified by the MCNP Development Team following the release that they are tracking internally (using the issue-tracker ID given in the "ID" column). A brief description is also given and, if available, a recommended solution and/or recommended patch is provided.

ID Description Recommended Solution
None N/A N/A