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That depends on your code. The short answer: if your code is a custom simulation or an iterative algorithm, then the answer is most likely yes.
The long answer is that LibGeoDecomp focuses on stencil codes: space- and time-discrete simulations in which the simulation space is decomposed according to a regular grid and time is split into discrete global time steps. Nevertheless, it has limited support for irregular spatial decompositions, too.
Yes, stencil codes are not a new topic. But that is the point, really. There are a lot of papers out there which follow the pattern We took stencil code FOO and did implement it with record breaking performance on architecture BAR, where FOO mostly refers to Jacobi or LBM while BAR will most likely be a GPU, or a large scale multi-core cluster. People write temporal and spatial blocking code, domain decompositions, parallel IO... they do this again and again. And why? Because there are currently few options for reusing implementations. This is why we believe that the time for a generic solution has come.
There surely are a number of packages which appear at a first glance to provide a similar functionality. Some are DSLs, some are libraries. But then again, we believe LibGeoDecomp has some key advantages. Please look here for a short review of how it relates to the competition. Here is a list of similar packages:
LibGeoDecomp makes heavy use of C++ class templates, so making it work with Fortran might not appear to be straightforward. Indeed it takes some thinking, but in the end it's not really complicated. Here is a quick example.
Common pitfall! Maybe. Maybe not. There are however two common fallacies which you might want to check first. My experience is that most codes fall victim to the one or the other. Don't worry though, they're easily fixed.
Download
Initializer, the main function
to implement is grid(GridBase *grid) . Some
folks will then go ahead and only initialize those cells
which are of interest to them (e.g. in an implementation of
Conway's Game of Life they might set only a couple of cells
which are marked as grid
are freshly initialized by their default constructor. But in
other cases it'll break: if you call run() in
your Simulator twice, it will re-initialize
it's grid with the help of the Initializer. But
if that one doesn't flush all the cells bad things will
happen. The reason why we don't re-initialize all cells by
default is simple: performance. Some codes would suffer by
this. Solution:grid has a
member boundingBox(). This will yield you
a this is
currently pointing) if you have already written those
members in the current iterations. For similar reasons to
the point above, we do not copy old values to the new grid
by default: it's slow and in fact most applications can do
without. Solution:You should rather read the
members of the last time step's cells, which can be accessed
through the neighborhood object, and only read those members
from this, which have already been written by
the current invocation of update().
The 3D Jacobi
code in our repo demonstrates that a default copy from
the last time step is in deed not required, as it will
overwrite its only data member in any case. If everything
else fails: *this = hood[Coord()]; might help.
Yes and no. While the
newer SoA
code may be considered an embedded DSL (embedded into
C++), the main part of the library is really a library with a
2-way callback. In a way it's similar to Qt. Qt handles the
event loop and will call back your code when it's appropriate.
So does LibGeoDecomp. Only that we don't do GUIs, but
simulations. Our callback works like this: you start a
simulation by calling run() on
a Simulator
object. The Simulator will then call back your model
(update() in your cell class). Your cell may then
in turn call back the library via a so-called neighborhood
object. The neighborhood object really is a proxy object by
which user code may get access to neighboring cells of the
last time step. For more details take a look at the
examples.
So much for the callback. The reasons why we don't use a full DSL with an external compiler are simple:
Quite simple, really: you call us, we call you, you call us. A bit more verbose:
Simulator object with your
simulation model as a template parameter. The model
describes the data a single grid cell holds and the
computations it performs in each time step.
Initializer to set up
initial conditions,Writers for output, and
optionally Steerers for modifying the
simulation at runtime) have been added, you
call run() on the Simulator.
Simulator will then call back your
code's update(): once for each cell and
timestep.
update() to
retrieve the state of your cell and the neighboring cells in
the last time step.
More details can be found in the examples. I highly recommend to take a look at the implementations of Jacobi and Game of Life.
Most development is done at the FAU in Erlangen, Germany. He try to keep an updated list here.
Please see our issue tracker on Bitbucket.
This depends on which of the libraries features you wish to use, but for a basic build you'll only need:
Additionally you may wish to provide:
If you don't just want to use the library, but also to modify it, then the build system may want to auto-regenerate LibGeoDecomp's internal MPI datatypes. This requires:
Some of the examples come with a Qt GUI and may a camera for input. For those you will need:
LibGeoDecomp is written in standard C++ so it should work out of the box with all C++ compilers. But because the world is big and bad (and so is the C++ standard) things are not that easy. We test LibGeoDecomp regularly with the following compilers:
Theoretically LibGeoDecomp shouldn't be picky regarding the version of a given package. However, here is a list of versions that we regularly test for compatibility:
| Package | Minimum Version | Tested Versions |
|---|---|---|
| CMake | 2.6.4 | 2.6.4, 2.8.2, 2.8.5, 2.8.8, 2.8.9, 2.8.11 |
| Open MPI | 1.4.2, 1.5.3, 1.5.5, 1.6.0, 1.6.5 | |
| Intel MPI | 4.0.1, 4.0.3 | |
| Boost | 1.37, y1.44, 1.47, 1.48, 1.49, 1.53 | |
| Qt | 4.0 | 4.8.1, 4.8.2, 4.8.5 |
| OpenCV | 2.3.1a, 2.4.5 |
With CMake you can select the C++ compiler
via CMAKE_CXX_COMPILER. Additionally I'd suggest
you to set some compiler flags to tone down the warnings
caused by some Boost libraries:
cmake -D CMAKE_CXX_COMPILER=icpc -D ADDITIONAL_COMPILE_FLAGS="-Wall -Wno-sign-compare -wd383 -wd981 -wd1418 ../../src"
JUQUEEN is the IBM Blue Gene/Q at Forschungszentrum Jülich. At
the point of this writing, it is
the fastest
European system. Building on JUQUEEN is slightly tricky,
as you'll want to use xlc++, IBM's C++ compiler,
which still has troubles with templates. And pretty much
everything in LibGeoDecomp is a template. Also, no interactive
jobs are available on this machine, which means you can't run
the unit tests on your build machine.
module load boost module load cmake cmake -D UNITEXEC=echo -D MPIEXEC=echo -D CMAKE_C_COMPILER=xlc -D CMAKE_CXX_COMPILER=mpixlcxx -D ADDITIONAL_COMPILE_FLAGS="-I/bgsys/local/boost/1.47.0" -D Boost_NO_BOOST_CMAKE=true -D BOOST_INCLUDEDIR="/bgsys/local/boost/1.47.0" -D LIB_LINKAGE_TYPE=STATIC ../../src/
You can't pull external HG repositories on SuperMUC and there
is no build of Boost for the PGI and Intel compilers. You'll
thus have to scp your checkout of LibGeoDecomp to
one of the login nodes. And I suggest using GCC for
compilation. In essence, the default build flags are
absolutely fine for this machine:
module load cmake module load boost/1.47_gcc cd libgeodecomp/ BUILD_DIR=build/`uname -ms | sed s/\ /-/g` mkdir -p $BUILD_DIR cd $BUILD_DIR cmake ../../src/ make -j10
If you've installed Boost in a non-standard location (e.g.
your home), then you can always set BOOST_ROOT. This is how we build on Tsubame 2.0:
cmake -D BOOST_ROOT=/home/usr5/A2401222/boost_1_50_0/ -D CMAKE_CXX_COMPILER=icpc -D ADDITIONAL_COMPILE_FLAGS="-Wall -Wno-sign-compare -wd383 -wd981 -wd1418" ../../src/
Easy: send us your CMake
output and make output! Which system (hardware vendor,
operating system) are you trying to build on?
CMake should do the right thing to discover
your environment. But given the variety of target platforms, I
wouldn't wonder if it fails on some systems. We'll be happy to
fix that! Below is a script which captures the relevant output
in the files cmake.log and make.log.
Run it from your build directory.
cmake ../../src 2>&1 | tee cmake.log make 2>&1 | tee make.log
Under certain conditions the value of a build variable and
CMake's argument parsing may interfere. In this case you
should add :STRING to the definition. Here you
see how to set a certain machine architecture, handy if you're
building on a 64-bit capable machine whose toolchain defaults
to building 32-bit code.
cmake -D ADDITIONAL_COMPILE_FLAGS:STRING="-march=core2 -m64" ../../src/
