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INSTALL
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INSTALL
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Installation guide
******************
Introduction to building GROMACS
================================
These instructions pertain to building GROMACS 2018.7. You might also
want to check the up-to-date installation instructions.
Quick and dirty installation
----------------------------
1. Get the latest version of your C and C++ compilers.
2. Check that you have CMake version 3.4.3 or later.
3. Get and unpack the latest version of the GROMACS tarball.
4. Make a separate build directory and change to it.
5. Run "cmake" with the path to the source as an argument
6. Run "make", "make check", and "make install"
7. Source "GMXRC" to get access to GROMACS
Or, as a sequence of commands to execute:
tar xfz gromacs-2018.7.tar.gz
cd gromacs-2018.7
mkdir build
cd build
cmake .. -DGMX_BUILD_OWN_FFTW=ON -DREGRESSIONTEST_DOWNLOAD=ON
make
make check
sudo make install
source /usr/local/gromacs/bin/GMXRC
This will download and build first the prerequisite FFT library
followed by GROMACS. If you already have FFTW installed, you can
remove that argument to "cmake". Overall, this build of GROMACS will
be correct and reasonably fast on the machine upon which "cmake" ran.
On another machine, it may not run, or may not run fast. If you want
to get the maximum value for your hardware with GROMACS, you will have
to read further. Sadly, the interactions of hardware, libraries, and
compilers are only going to continue to get more complex.
Quick and dirty cluster installation
------------------------------------
On a cluster where users are expected to be running across multiple
nodes using MPI, make one installation similar to the above, and
another using an MPI wrapper compiler and which is building only
mdrun, because that is the only component of GROMACS that uses MPI.
The latter will install a single simulation engine binary, i.e.
"mdrun_mpi" when the default suffix is used. Hence it is safe and
common practice to install this into the same location where the non-
MPI build is installed.
Typical installation
--------------------
As above, and with further details below, but you should consider
using the following CMake options with the appropriate value instead
of "xxx" :
* "-DCMAKE_C_COMPILER=xxx" equal to the name of the C99 Compiler you
wish to use (or the environment variable "CC")
* "-DCMAKE_CXX_COMPILER=xxx" equal to the name of the C++98 compiler
you wish to use (or the environment variable "CXX")
* "-DGMX_MPI=on" to build using MPI support (generally good to
combine with building only mdrun)
* "-DGMX_GPU=on" to build using nvcc to run using NVIDIA CUDA GPU
acceleration or an OpenCL GPU
* "-DGMX_USE_OPENCL=on" to build with OpenCL support enabled.
"GMX_GPU" must also be set.
* "-DGMX_SIMD=xxx" to specify the level of SIMD support of the node
on which GROMACS will run
* "-DGMX_BUILD_MDRUN_ONLY=on" for building only mdrun, e.g. for
compute cluster back-end nodes
* "-DGMX_DOUBLE=on" to build GROMACS in double precision (slower,
and not normally useful)
* "-DCMAKE_PREFIX_PATH=xxx" to add a non-standard location for CMake
to search for libraries, headers or programs
* "-DCMAKE_INSTALL_PREFIX=xxx" to install GROMACS to a non-standard
location (default "/usr/local/gromacs")
* "-DBUILD_SHARED_LIBS=off" to turn off the building of shared
libraries to help with static linking
* "-DGMX_FFT_LIBRARY=xxx" to select whether to use "fftw", "mkl" or
"fftpack" libraries for FFT support
* "-DCMAKE_BUILD_TYPE=Debug" to build GROMACS in debug mode
Building older versions
-----------------------
Installation instructions for old GROMACS versions can be found at the
GROMACS documentation page.
Prerequisites
=============
Platform
--------
GROMACS can be compiled for many operating systems and architectures.
These include any distribution of Linux, Mac OS X or Windows, and
architectures including x86, AMD64/x86-64, several PowerPC including
POWER8, ARM v7, ARM v8, and SPARC VIII.
Compiler
--------
GROMACS can be compiled on any platform with ANSI C99 and C++11
compilers, and their respective standard C/C++ libraries. Good
performance on an OS and architecture requires choosing a good
compiler. We recommend gcc, because it is free, widely available and
frequently provides the best performance.
You should strive to use the most recent version of your compiler.
Since we require full C++11 support the minimum supported compiler
versions are
* GNU (gcc) 4.8.1
* Intel (icc) 15.0
* LLVM (clang) 3.3
* Microsoft (MSVC) 2015
Other compilers may work (Cray, Pathscale, older clang) but do not
offer competitive performance. We recommend against PGI because the
performance with C++ is very bad.
The xlc compiler is not supported and has not been tested on POWER
architectures for GROMACS-2018.7. We recommend to use the gcc compiler
instead, as it is being extensively tested.
You may also need the most recent version of other compiler toolchain
components beside the compiler itself (e.g. assembler or linker);
these are often shipped by your OS distribution’s binutils package.
C++11 support requires adequate support in both the compiler and the
C++ library. The gcc and MSVC compilers include their own standard
libraries and require no further configuration. For configuration of
other compilers, read on.
On Linux, both the Intel and clang compiler use the libstdc++ which
comes with gcc as the default C++ library. For GROMACS, we require the
compiler to support libstc++ version 4.8.1 or higher. To select a
particular libstdc++ library, use:
* For Intel: "-DGMX_STDLIB_CXX_FLAGS=-gcc-name=/path/to/gcc/binary"
or make sure that the correct gcc version is first in path (e.g. by
loading the gcc module). It can also be useful to add
"-DCMAKE_CXX_LINK_FLAGS="-Wl,-rpath,/path/to/gcc/lib64
-L/path/to/gcc/lib64"" to ensure linking works correctly.
* For clang: "-DCMAKE_CXX_FLAGS=--gcc-
toolchain=/path/to/gcc/folder". This folder should contain
"include/c++".
On Windows with the Intel compiler, the MSVC standard library is used,
and at least MSVC 2015 is required. Load the enviroment variables with
vcvarsall.bat.
To build with any compiler and clang’s libcxx standard library, use
"-DGMX_STDLIB_CXX_FLAGS=-stdlib=libc++
-DGMX_STDLIB_LIBRARIES='-lc++abi -lc++'".
If you are running on Mac OS X, the best option is the Intel compiler.
Both clang and gcc will work, but they produce lower performance and
each have some shortcomings. clang 3.8 now offers support for OpenMP,
and so may provide decent performance.
For all non-x86 platforms, your best option is typically to use gcc or
the vendor’s default or recommended compiler, and check for
specialized information below.
For updated versions of gcc to add to your Linux OS, see
* Ubuntu: Ubuntu toolchain ppa page
* RHEL/CentOS: EPEL page or the RedHat Developer Toolset
Compiling with parallelization options
--------------------------------------
For maximum performance you will need to examine how you will use
GROMACS and what hardware you plan to run on. Often OpenMP parallelism
is an advantage for GROMACS, but support for this is generally built
into your compiler and detected automatically.
GPU support
~~~~~~~~~~~
GROMACS has excellent support for NVIDIA GPUs supported via CUDA. On
Linux, NVIDIA CUDA toolkit with minimum version 6.5 is required, and
the latest version is strongly encouraged. Using Intel or Microsoft
MSVC compilers requires version 7.0 and 8.0, respectively. NVIDIA GPUs
with at least NVIDIA compute capability 2.0 are required. You are
strongly recommended to get the latest CUDA version and driver that
supports your hardware, but beware of possible performance regressions
in newer CUDA versions on older hardware. Note that compute capability
2.0 (Fermi) devices are no longer supported from CUDA 9.0 and later.
While some CUDA compilers (nvcc) might not officially support recent
versions of gcc as the back-end compiler, we still recommend that you
at least use a gcc version recent enough to get the best SIMD support
for your CPU, since GROMACS always runs some code on the CPU. It is
most reliable to use the same C++ compiler version for GROMACS code as
used as the host compiler for nvcc.
To make it possible to use other accelerators, GROMACS also includes
OpenCL support. The minimum OpenCL version required is 1.1. The
current OpenCL implementation is recommended for use with GCN-based
AMD GPUs, on Linux we recommend the ROCm runtime. It is also supported
with NVIDIA GPUs, but using the latest NVIDIA driver (which includes
the NVIDIA OpenCL runtime) is recommended. Also note that there are
performance limitations (inherent to the NVIDIA OpenCL runtime). It is
not possible to configure both CUDA and OpenCL support in the same
version of GROMACS.
MPI support
~~~~~~~~~~~
GROMACS can run in parallel on multiple cores of a single workstation
using its built-in thread-MPI. No user action is required in order to
enable this.
If you wish to run in parallel on multiple machines across a network,
you will need to have
* an MPI library installed that supports the MPI 1.3 standard, and
* wrapper compilers that will compile code using that library.
The GROMACS team recommends OpenMPI version 1.6 (or higher), MPICH
version 1.4.1 (or higher), or your hardware vendor’s MPI installation.
The most recent version of either of these is likely to be the best.
More specialized networks might depend on accelerations only available
in the vendor’s library. LAM-MPI might work, but since it has been
deprecated for years, it is not supported.
CMake
-----
GROMACS builds with the CMake build system, requiring at least version
3.4.3. You can check whether CMake is installed, and what version it
is, with "cmake --version". If you need to install CMake, then first
check whether your platform’s package management system provides a
suitable version, or visit the CMake installation page for pre-
compiled binaries, source code and installation instructions. The
GROMACS team recommends you install the most recent version of CMake
you can.
Fast Fourier Transform library
------------------------------
Many simulations in GROMACS make extensive use of fast Fourier
transforms, and a software library to perform these is always
required. We recommend FFTW (version 3 or higher only) or Intel MKL.
The choice of library can be set with "cmake
-DGMX_FFT_LIBRARY=<name>", where "<name>" is one of "fftw", "mkl", or
"fftpack". FFTPACK is bundled with GROMACS as a fallback, and is
acceptable if simulation performance is not a priority. When choosing
MKL, GROMACS will also use MKL for BLAS and LAPACK (see linear algebra
libraries). Generally, there is no advantage in using MKL with
GROMACS, and FFTW is often faster. With PME GPU offload support using
CUDA, a GPU-based FFT library is required. The CUDA-based GPU FFT
library cuFFT is part of the CUDA toolkit (required for all CUDA
builds) and therefore no additional software component is needed when
building with CUDA GPU acceleration.
Using FFTW
~~~~~~~~~~
FFTW is likely to be available for your platform via its package
management system, but there can be compatibility and significant
performance issues associated with these packages. In particular,
GROMACS simulations are normally run in “mixed” floating-point
precision, which is suited for the use of single precision in FFTW.
The default FFTW package is normally in double precision, and good
compiler options to use for FFTW when linked to GROMACS may not have
been used. Accordingly, the GROMACS team recommends either
* that you permit the GROMACS installation to download and build
FFTW from source automatically for you (use "cmake
-DGMX_BUILD_OWN_FFTW=ON"), or
* that you build FFTW from the source code.
If you build FFTW from source yourself, get the most recent version
and follow the FFTW installation guide. Choose the precision for FFTW
(i.e. single/float vs. double) to match whether you will later use
mixed or double precision for GROMACS. There is no need to compile
FFTW with threading or MPI support, but it does no harm. On x86
hardware, compile with *both* "--enable-sse2" and "--enable-avx" for
FFTW-3.3.4 and earlier. From FFTW-3.3.5, you should also add "--
enable-avx2" also. On Intel processors supporting 512-wide AVX,
including KNL, add "--enable-avx512" also. FFTW will create a fat
library with codelets for all different instruction sets, and pick the
fastest supported one at runtime. On ARM architectures with NEON SIMD
support and IBM Power8 and later, you definitely want version 3.3.5 or
later, and to compile it with "--enable-neon" and "--enable-vsx",
respectively, for SIMD support. If you are using a Cray, there is a
special modified (commercial) version of FFTs using the FFTW interface
which can be slightly faster.
Using MKL
~~~~~~~~~
Use MKL bundled with Intel compilers by setting up the compiler
environment, e.g., through "source /path/to/compilervars.sh intel64"
or similar before running CMake including setting
"-DGMX_FFT_LIBRARY=mkl".
If you need to customize this further, use
cmake -DGMX_FFT_LIBRARY=mkl \
-DMKL_LIBRARIES="/full/path/to/libone.so;/full/path/to/libtwo.so" \
-DMKL_INCLUDE_DIR="/full/path/to/mkl/include"
The full list and order(!) of libraries you require are found in
Intel’s MKL documentation for your system.
Other optional build components
-------------------------------
* Run-time detection of hardware capabilities can be improved by
linking with hwloc, which is automatically enabled if detected.
* Hardware-optimized BLAS and LAPACK libraries are useful for a few
of the GROMACS utilities focused on normal modes and matrix
manipulation, but they do not provide any benefits for normal
simulations. Configuring these is discussed at linear algebra
libraries.
* The built-in GROMACS trajectory viewer "gmx view" requires X11 and
Motif/Lesstif libraries and header files. You may prefer to use
third-party software for visualization, such as VMD or PyMol.
* An external TNG library for trajectory-file handling can be used
by setting "-DGMX_EXTERNAL_TNG=yes", but TNG 1.7.10 is bundled in
the GROMACS source already.
* An external lmfit library for Levenberg-Marquardt curve fitting
can be used by setting "-DGMX_EXTERNAL_LMFIT=yes", but lmfit 6.1 is
bundled in the GROMACS source already.
* zlib is used by TNG for compressing some kinds of trajectory data
* Building the GROMACS documentation is optional, and requires
ImageMagick, pdflatex, bibtex, doxygen, python 2.7, sphinx 1.4.1,
and pygments.
* The GROMACS utility programs often write data files in formats
suitable for the Grace plotting tool, but it is straightforward to
use these files in other plotting programs, too.
Doing a build of GROMACS
========================
This section will cover a general build of GROMACS with CMake, but it
is not an exhaustive discussion of how to use CMake. There are many
resources available on the web, which we suggest you search for when
you encounter problems not covered here. The material below applies
specifically to builds on Unix-like systems, including Linux, and Mac
OS X. For other platforms, see the specialist instructions below.
Configuring with CMake
----------------------
CMake will run many tests on your system and do its best to work out
how to build GROMACS for you. If your build machine is the same as
your target machine, then you can be sure that the defaults and
detection will be pretty good. However, if you want to control aspects
of the build, or you are compiling on a cluster head node for back-end
nodes with a different architecture, there are a few things you should
consider specifying.
The best way to use CMake to configure GROMACS is to do an “out-of-
source” build, by making another directory from which you will run
CMake. This can be outside the source directory, or a subdirectory of
it. It also means you can never corrupt your source code by trying to
build it! So, the only required argument on the CMake command line is
the name of the directory containing the "CMakeLists.txt" file of the
code you want to build. For example, download the source tarball and
use
tar xfz gromacs-2018.7.tgz
cd gromacs-2018.7
mkdir build-gromacs
cd build-gromacs
cmake ..
You will see "cmake" report a sequence of results of tests and
detections done by the GROMACS build system. These are written to the
"cmake" cache, kept in "CMakeCache.txt". You can edit this file by
hand, but this is not recommended because you could make a mistake.
You should not attempt to move or copy this file to do another build,
because file paths are hard-coded within it. If you mess things up,
just delete this file and start again with "cmake".
If there is a serious problem detected at this stage, then you will
see a fatal error and some suggestions for how to overcome it. If you
are not sure how to deal with that, please start by searching on the
web (most computer problems already have known solutions!) and then
consult the gmx-users mailing list. There are also informational
warnings that you might like to take on board or not. Piping the
output of "cmake" through "less" or "tee" can be useful, too.
Once "cmake" returns, you can see all the settings that were chosen
and information about them by using e.g. the curses interface
ccmake ..
You can actually use "ccmake" (available on most Unix platforms)
directly in the first step, but then most of the status messages will
merely blink in the lower part of the terminal rather than be written
to standard output. Most platforms including Linux, Windows, and Mac
OS X even have native graphical user interfaces for "cmake", and it
can create project files for almost any build environment you want
(including Visual Studio or Xcode). Check out running CMake for
general advice on what you are seeing and how to navigate and change
things. The settings you might normally want to change are already
presented. You may make changes, then re-configure (using "c"), so
that it gets a chance to make changes that depend on yours and perform
more checking. It may take several configuration passes to reach the
desired configuration, in particular if you need to resolve errors.
When you have reached the desired configuration with "ccmake", the
build system can be generated by pressing "g". This requires that the
previous configuration pass did not reveal any additional settings (if
it did, you need to configure once more with "c"). With "cmake", the
build system is generated after each pass that does not produce
errors.
You cannot attempt to change compilers after the initial run of
"cmake". If you need to change, clean up, and start again.
Where to install GROMACS
~~~~~~~~~~~~~~~~~~~~~~~~
GROMACS is installed in the directory to which "CMAKE_INSTALL_PREFIX"
points. It may not be the source directory or the build directory.
You require write permissions to this directory. Thus, without super-
user privileges, "CMAKE_INSTALL_PREFIX" will have to be within your
home directory. Even if you do have super-user privileges, you should
use them only for the installation phase, and never for configuring,
building, or running GROMACS!
Using CMake command-line options
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Once you become comfortable with setting and changing options, you may
know in advance how you will configure GROMACS. If so, you can speed
things up by invoking "cmake" and passing the various options at once
on the command line. This can be done by setting cache variable at the
cmake invocation using "-DOPTION=VALUE". Note that some environment
variables are also taken into account, in particular variables like
"CC" and "CXX".
For example, the following command line
cmake .. -DGMX_GPU=ON -DGMX_MPI=ON -DCMAKE_INSTALL_PREFIX=/home/marydoe/programs
can be used to build with CUDA GPUs, MPI and install in a custom
location. You can even save that in a shell script to make it even
easier next time. You can also do this kind of thing with "ccmake",
but you should avoid this, because the options set with "-D" will not
be able to be changed interactively in that run of "ccmake".
SIMD support
~~~~~~~~~~~~
GROMACS has extensive support for detecting and using the SIMD
capabilities of many modern HPC CPU architectures. If you are building
GROMACS on the same hardware you will run it on, then you don’t need
to read more about this, unless you are getting configuration warnings
you do not understand. By default, the GROMACS build system will
detect the SIMD instruction set supported by the CPU architecture (on
which the configuring is done), and thus pick the best available SIMD
parallelization supported by GROMACS. The build system will also check
that the compiler and linker used also support the selected SIMD
instruction set and issue a fatal error if they do not.
Valid values are listed below, and the applicable value with the
largest number in the list is generally the one you should choose. In
most cases, choosing an inappropriate higher number will lead to
compiling a binary that will not run. However, on a number of
processor architectures choosing the highest supported value can lead
to performance loss, e.g. on Intel Skylake-X/SP and AMD Zen.
1. "None" For use only on an architecture either lacking SIMD, or
to which GROMACS has not yet been ported and none of the options
below are applicable.
2. "SSE2" This SIMD instruction set was introduced in Intel
processors in 2001, and AMD in 2003. Essentially all x86 machines
in existence have this, so it might be a good choice if you need to
support dinosaur x86 computers too.
3. "SSE4.1" Present in all Intel core processors since 2007, but
notably not in AMD Magny-Cours. Still, almost all recent processors
support this, so this can also be considered a good baseline if you
are content with slow simulations and prefer portability between
reasonably modern processors.
4. "AVX_128_FMA" AMD Bulldozer, Piledriver (and later Family 15h)
processors have this.
5. "AVX_256" Intel processors since Sandy Bridge (2011). While this
code will work on the AMD Bulldozer and Piledriver processors, it
is significantly less efficient than the "AVX_128_FMA" choice above
- do not be fooled to assume that 256 is better than 128 in this
case.
6. "AVX2_128" AMD Zen microarchitecture processors (2017); it will
enable AVX2 with 3-way fused multiply-add instructions. While the
Zen microarchitecture does support 256-bit AVX2 instructions, hence
"AVX2_256" is also supported, 128-bit will generally be faster, in
particular when the non-bonded tasks run on the CPU – hence the
default "AVX2_128". With GPU offload however "AVX2_256" can be
faster on Zen processors.
7. "AVX2_256" Present on Intel Haswell (and later) processors
(2013), and it will also enable Intel 3-way fused multiply-add
instructions.
8. "AVX_512" Skylake-X desktop and Skylake-SP Xeon processors
(2017); it will generally be fastest on the higher-end desktop and
server processors with two 512-bit fused multiply-add units (e.g.
Core i9 and Xeon Gold). However, certain desktop and server models
(e.g. Xeon Bronze and Silver) come with only one AVX512 FMA unit
and therefore on these processors "AVX2_256" is faster (compile-
and runtime checks try to inform about such cases). Additionally,
with GPU accelerated runs "AVX2_256" can also be faster on high-end
Skylake CPUs with both 512-bit FMA units enabled.
9. "AVX_512_KNL" Knights Landing Xeon Phi processors
10. "IBM_QPX" BlueGene/Q A2 cores have this.
11. "Sparc64_HPC_ACE" Fujitsu machines like the K computer have
this.
12. "IBM_VMX" Power6 and similar Altivec processors have this.
13. "IBM_VSX" Power7, Power8 and later have this.
14. "ARM_NEON" 32-bit ARMv7 with NEON support.
15. "ARM_NEON_ASIMD" 64-bit ARMv8 and later.
The CMake configure system will check that the compiler you have
chosen can target the architecture you have chosen. mdrun will check
further at runtime, so if in doubt, choose the lowest number you think
might work, and see what mdrun says. The configure system also works
around many known issues in many versions of common HPC compilers.
A further "GMX_SIMD=Reference" option exists, which is a special SIMD-
like implementation written in plain C that developers can use when
developing support in GROMACS for new SIMD architectures. It is not
designed for use in production simulations, but if you are using an
architecture with SIMD support to which GROMACS has not yet been
ported, you may wish to try this option instead of the default
"GMX_SIMD=None", as it can often out-perform this when the auto-
vectorization in your compiler does a good job. And post on the
GROMACS mailing lists, because GROMACS can probably be ported for new
SIMD architectures in a few days.
CMake advanced options
~~~~~~~~~~~~~~~~~~~~~~
The options that are displayed in the default view of "ccmake" are
ones that we think a reasonable number of users might want to consider
changing. There are a lot more options available, which you can see by
toggling the advanced mode in "ccmake" on and off with "t". Even
there, most of the variables that you might want to change have a
"CMAKE_" or "GMX_" prefix. There are also some options that will be
visible or not according to whether their preconditions are satisfied.
Helping CMake find the right libraries, headers, or programs
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
If libraries are installed in non-default locations their location can
be specified using the following variables:
* "CMAKE_INCLUDE_PATH" for header files
* "CMAKE_LIBRARY_PATH" for libraries
* "CMAKE_PREFIX_PATH" for header, libraries and binaries (e.g.
"/usr/local").
The respective "include", "lib", or "bin" is appended to the path. For
each of these variables, a list of paths can be specified (on Unix,
separated with “:”). These can be set as enviroment variables like:
CMAKE_PREFIX_PATH=/opt/fftw:/opt/cuda cmake ..
(assuming "bash" shell). Alternatively, these variables are also
"cmake" options, so they can be set like
"-DCMAKE_PREFIX_PATH=/opt/fftw:/opt/cuda".
The "CC" and "CXX" environment variables are also useful for
indicating to "cmake" which compilers to use. Similarly,
"CFLAGS"/"CXXFLAGS" can be used to pass compiler options, but note
that these will be appended to those set by GROMACS for your build
platform and build type. You can customize some of this with advanced
CMake options such as "CMAKE_C_FLAGS" and its relatives.
See also the page on CMake environment variables.
CUDA GPU acceleration
~~~~~~~~~~~~~~~~~~~~~
If you have the CUDA Toolkit installed, you can use "cmake" with:
cmake .. -DGMX_GPU=ON -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda
(or whichever path has your installation). In some cases, you might
need to specify manually which of your C++ compilers should be used,
e.g. with the advanced option "CUDA_HOST_COMPILER".
To make it possible to get best performance from NVIDIA Tesla and
Quadro GPUs, you should install the GPU Deployment Kit and configure
GROMACS to use it by setting the CMake variable
"-DGPU_DEPLOYMENT_KIT_ROOT_DIR=/path/to/your/kit". The NVML support is
most useful if "nvidia-smi --applications-clocks-
permission=UNRESTRICTED" is run (as root). When application clocks
permissions are unrestricted, the GPU clock speed can be increased
automatically, which increases the GPU kernel performance roughly
proportional to the clock increase. When using GROMACS on suitable
GPUs under restricted permissions, clocks cannot be changed, and in
that case informative log file messages will be produced. Background
details can be found at this NVIDIA blog post. NVML support is only
available if detected, and may be disabled by turning off the
"GMX_USE_NVML" CMake advanced option.
By default, code will be generated for the most common CUDA
architectures. However, to reduce build time and binary size we do not
generate code for every single possible architecture, which in rare
cases (say, Tegra systems) can result in the default build not being
able to use some GPUs. If this happens, or if you want to remove some
architectures to reduce binary size and build time, you can alter the
target CUDA architectures. This can be done either with the
"GMX_CUDA_TARGET_SM" or "GMX_CUDA_TARGET_COMPUTE" CMake variables,
which take a semicolon delimited string with the two digit suffixes of
CUDA (virtual) architectures names, for instance “35;50;51;52;53;60”.
For details, see the “Options for steering GPU code generation”
section of the nvcc man / help or Chapter 6. of the nvcc manual.
The GPU acceleration has been tested on AMD64/x86-64 platforms with
Linux, Mac OS X and Windows operating systems, but Linux is the best-
tested and supported of these. Linux running on POWER 8, ARM v7 and v8
CPUs also works well.
Experimental support is available for compiling CUDA code, both for
host and device, using clang (version 3.9 or later). A CUDA toolkit
(>= v7.0) is still required but it is used only for GPU device code
generation and to link against the CUDA runtime library. The clang
CUDA support simplifies compilation and provides benefits for
development (e.g. allows the use code sanitizers in CUDA host-code).
Additionally, using clang for both CPU and GPU compilation can be
beneficial to avoid compatibility issues between the GNU toolchain and
the CUDA toolkit. clang for CUDA can be triggered using the
"GMX_CLANG_CUDA=ON" CMake option. Target architectures can be selected
with "GMX_CUDA_TARGET_SM", virtual architecture code is always
embedded for all requested architectures (hence
GMX_CUDA_TARGET_COMPUTE is ignored). Note that this is mainly a
developer-oriented feature and it is not recommended for production
use as the performance can be significantly lower than that of code
compiled with nvcc (and it has also received less testing). However,
note that with clang 5.0 the performance gap is significantly narrowed
(at the time of writing, about 20% slower GPU kernels), so this
version could be considered in non performance-critical use-cases.
OpenCL GPU acceleration
~~~~~~~~~~~~~~~~~~~~~~~
The primary target of the GROMACS OpenCL support is accelerating
simulations on AMD hardware, both discrete GPUs and APUs (integrated
CPU+GPU chips). The GROMACS OpenCL on NVIDIA GPUs works, but
performance and other limitations make it less practical (for details
see the user guide).
To build GROMACS with OpenCL support enabled, two components are
required: the OpenCL headers and the wrapper library that acts as a
client driver loader (so-called ICD loader). The additional, runtime-
only dependency is the vendor-specific GPU driver for the device
targeted. This also contains the OpenCL compiler. As the GPU compute
kernels are compiled on-demand at run time, this vendor-specific
compiler and driver is not needed for building GROMACS. The former,
compile-time dependencies are standard components, hence stock
versions can be obtained from most Linux distribution repositories
(e.g. "opencl-headers" and "ocl-icd-libopencl1" on Debian/Ubuntu).
Only the compatibility with the required OpenCL version 1.1 needs to
be ensured. Alternatively, the headers and library can also be
obtained from vendor SDKs (e.g. from AMD), which must be installed in
a path found in "CMAKE_PREFIX_PATH" (or via the environment variables
"AMDAPPSDKROOT" or "CUDA_PATH").
To trigger an OpenCL build the following CMake flags must be set
cmake .. -DGMX_GPU=ON -DGMX_USE_OPENCL=ON
On Mac OS, an AMD GPU can be used only with OS version 10.10.4 and
higher; earlier OS versions are known to run incorrectly.
Static linking
~~~~~~~~~~~~~~
Dynamic linking of the GROMACS executables will lead to a smaller disk
footprint when installed, and so is the default on platforms where we
believe it has been tested repeatedly and found to work. In general,
this includes Linux, Windows, Mac OS X and BSD systems. Static
binaries take more space, but on some hardware and/or under some
conditions they are necessary, most commonly when you are running a
parallel simulation using MPI libraries (e.g. BlueGene, Cray).
* To link GROMACS binaries statically against the internal GROMACS
libraries, set "-DBUILD_SHARED_LIBS=OFF".
* To link statically against external (non-system) libraries as
well, set "-DGMX_PREFER_STATIC_LIBS=ON". Note, that in general
"cmake" picks up whatever is available, so this option only
instructs "cmake" to prefer static libraries when both static and
shared are available. If no static version of an external library is
available, even when the aforementioned option is "ON", the shared
library will be used. Also note that the resulting binaries will
still be dynamically linked against system libraries on platforms
where that is the default. To use static system libraries,
additional compiler/linker flags are necessary, e.g. "-static-libgcc
-static- libstdc++".
* To attempt to link a fully static binary set
"-DGMX_BUILD_SHARED_EXE=OFF". This will prevent CMake from
explicitly setting any dynamic linking flags. This option also sets
"-DBUILD_SHARED_LIBS=OFF" and "-DGMX_PREFER_STATIC_LIBS=ON" by
default, but the above caveats apply. For compilers which don’t
default to static linking, the required flags have to be specified.
On Linux, this is usually "CFLAGS=-static CXXFLAGS=-static".
Portability aspects
~~~~~~~~~~~~~~~~~~~
A GROMACS build will normally not be portable, not even across
hardware with the same base instruction set, like x86. Non-portable
hardware-specific optimizations are selected at configure-time, such
as the SIMD instruction set used in the compute kernels. This
selection will be done by the build system based on the capabilities
of the build host machine or otherwise specified to "cmake" during
configuration.
Often it is possible to ensure portability by choosing the least
common denominator of SIMD support, e.g. SSE2 for x86, and ensuring
the you use "cmake -DGMX_USE_RDTSCP=off" if any of the target CPU
architectures does not support the "RDTSCP" instruction. However, we
discourage attempts to use a single GROMACS installation when the
execution environment is heterogeneous, such as a mix of AVX and
earlier hardware, because this will lead to programs (especially
mdrun) that run slowly on the new hardware. Building two full
installations and locally managing how to call the correct one (e.g.
using a module system) is the recommended approach. Alternatively, as
at the moment the GROMACS tools do not make strong use of SIMD
acceleration, it can be convenient to create an installation with
tools portable across different x86 machines, but with separate mdrun
binaries for each architecture. To achieve this, one can first build a
full installation with the least-common-denominator SIMD instruction
set, e.g. "-DGMX_SIMD=SSE2", then build separate mdrun binaries for
each architecture present in the heterogeneous environment. By using
custom binary and library suffixes for the mdrun-only builds, these
can be installed to the same location as the “generic” tools
installation. Building just the mdrun binary is possible by setting
the "-DGMX_BUILD_MDRUN_ONLY=ON" option.
Linear algebra libraries
~~~~~~~~~~~~~~~~~~~~~~~~
As mentioned above, sometimes vendor BLAS and LAPACK libraries can
provide performance enhancements for GROMACS when doing normal-mode
analysis or covariance analysis. For simplicity, the text below will
refer only to BLAS, but the same options are available for LAPACK. By
default, CMake will search for BLAS, use it if it is found, and
otherwise fall back on a version of BLAS internal to GROMACS. The
"cmake" option "-DGMX_EXTERNAL_BLAS=on" will be set accordingly. The
internal versions are fine for normal use. If you need to specify a
non-standard path to search, use
"-DCMAKE_PREFIX_PATH=/path/to/search". If you need to specify a
library with a non-standard name (e.g. ESSL on AIX or BlueGene), then
set "-DGMX_BLAS_USER=/path/to/reach/lib/libwhatever.a".
If you are using Intel MKL for FFT, then the BLAS and LAPACK it
provides are used automatically. This could be over-ridden with
"GMX_BLAS_USER", etc.
On Apple platforms where the Accelerate Framework is available, these
will be automatically used for BLAS and LAPACK. This could be over-
ridden with "GMX_BLAS_USER", etc.
Changing the names of GROMACS binaries and libraries
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
It is sometimes convenient to have different versions of the same
GROMACS programs installed. The most common use cases have been single
and double precision, and with and without MPI. This mechanism can
also be used to install side-by-side multiple versions of mdrun
optimized for different CPU architectures, as mentioned previously.
By default, GROMACS will suffix programs and libraries for such builds
with "_d" for double precision and/or "_mpi" for MPI (and nothing
otherwise). This can be controlled manually with "GMX_DEFAULT_SUFFIX
(ON/OFF)", "GMX_BINARY_SUFFIX" (takes a string) and "GMX_LIBS_SUFFIX"
(also takes a string). For instance, to set a custom suffix for
programs and libraries, one might specify:
cmake .. -DGMX_DEFAULT_SUFFIX=OFF -DGMX_BINARY_SUFFIX=_mod -DGMX_LIBS_SUFFIX=_mod
Thus the names of all programs and libraries will be appended with
"_mod".
Changing installation tree structure
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
By default, a few different directories under "CMAKE_INSTALL_PREFIX"
are used when when GROMACS is installed. Some of these can be changed,
which is mainly useful for packaging GROMACS for various
distributions. The directories are listed below, with additional notes
about some of them. Unless otherwise noted, the directories can be
renamed by editing the installation paths in the main CMakeLists.txt.
"bin/"
The standard location for executables and some scripts. Some of the
scripts hardcode the absolute installation prefix, which needs to
be changed if the scripts are relocated. The name of the directory
can be changed using "CMAKE_INSTALL_BINDIR" CMake variable.
"include/gromacs/"
The standard location for installed headers.
"lib/"
The standard location for libraries. The default depends on the
system, and is determined by CMake. The name of the directory can
be changed using "CMAKE_INSTALL_LIBDIR" CMake variable.
"lib/pkgconfig/"
Information about the installed "libgromacs" library for "pkg-
config" is installed here. The "lib/" part adapts to the
installation location of the libraries. The installed files
contain the installation prefix as absolute paths.
"share/cmake/"
CMake package configuration files are installed here.
"share/gromacs/"
Various data files and some documentation go here. The first part
can be changed using "CMAKE_INSTALL_DATADIR", and the second by
using "GMX_INSTALL_DATASUBDIR" Using these CMake variables is the
preferred way of changing the installation path for
"share/gromacs/top/", since the path to this directory is built
into "libgromacs" as well as some scripts, both as a relative and
as an absolute path (the latter as a fallback if everything else
fails).
"share/man/"
Installed man pages go here.
Compiling and linking
---------------------
Once you have configured with "cmake", you can build GROMACS with
"make". It is expected that this will always complete successfully,
and give few or no warnings. The CMake-time tests GROMACS makes on the
settings you choose are pretty extensive, but there are probably a few
cases we have not thought of yet. Search the web first for solutions
to problems, but if you need help, ask on gmx-users, being sure to
provide as much information as possible about what you did, the system
you are building on, and what went wrong. This may mean scrolling back
a long way through the output of "make" to find the first error
message!
If you have a multi-core or multi-CPU machine with "N" processors,
then using
make -j N
will generally speed things up by quite a bit. Other build generator
systems supported by "cmake" (e.g. "ninja") also work well.
Building only mdrun
~~~~~~~~~~~~~~~~~~~
This is now supported with the "cmake" option
"-DGMX_BUILD_MDRUN_ONLY=ON", which will build a different version of
"libgromacs" and the "mdrun" program. Naturally, now "make install"
installs only those products. By default, mdrun-only builds will
default to static linking against GROMACS libraries, because this is
generally a good idea for the targets for which an mdrun-only build is
desirable.
Installing GROMACS
------------------
Finally, "make install" will install GROMACS in the directory given in
"CMAKE_INSTALL_PREFIX". If this is a system directory, then you will
need permission to write there, and you should use super-user
privileges only for "make install" and not the whole procedure.
Getting access to GROMACS after installation
--------------------------------------------
GROMACS installs the script "GMXRC" in the "bin" subdirectory of the
installation directory (e.g. "/usr/local/gromacs/bin/GMXRC"), which
you should source from your shell:
source /your/installation/prefix/here/bin/GMXRC
It will detect what kind of shell you are running and set up your
environment for using GROMACS. You may wish to arrange for your login
scripts to do this automatically; please search the web for
instructions on how to do this for your shell.
Many of the GROMACS programs rely on data installed in the
"share/gromacs" subdirectory of the installation directory. By
default, the programs will use the environment variables set in the
"GMXRC" script, and if this is not available they will try to guess
the path based on their own location. This usually works well unless
you change the names of directories inside the install tree. If you
still need to do that, you might want to recompile with the new
install location properly set, or edit the "GMXRC" script.
Testing GROMACS for correctness
-------------------------------
Since 2011, the GROMACS development uses an automated system where
every new code change is subject to regression testing on a number of
platforms and software combinations. While this improves reliability
quite a lot, not everything is tested, and since we increasingly rely
on cutting edge compiler features there is non-negligible risk that
the default compiler on your system could have bugs. We have tried our
best to test and refuse to use known bad versions in "cmake", but we
strongly recommend that you run through the tests yourself. It only
takes a few minutes, after which you can trust your build.
The simplest way to run the checks is to build GROMACS with
"-DREGRESSIONTEST_DOWNLOAD", and run "make check". GROMACS will
automatically download and run the tests for you. Alternatively, you
can download and unpack the GROMACS regression test suite
http://gerrit.gromacs.org/download/regressiontests-2018.7.tar.gz
tarball yourself and use the advanced "cmake" option
"REGRESSIONTEST_PATH" to specify the path to the unpacked tarball,
which will then be used for testing. If the above does not work, then