/* StarPU --- Runtime system for heterogeneous multicore architectures.
 *
 * Copyright (C) 2009-2024  Université de Bordeaux, CNRS (LaBRI UMR 5800), Inria
 * Copyright (C) 2020       Federal University of Rio Grande do Sul (UFRGS)
 *
 * StarPU is free software; you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as published by
 * the Free Software Foundation; either version 2.1 of the License, or (at
 * your option) any later version.
 *
 * StarPU is distributed in the hope that it will be useful, but
 * WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
 *
 * See the GNU Lesser General Public License in COPYING.LGPL for more details.
 */

/*
 * NOTE: XXX: also update simgrid versions in 101_building.doxy !!
 */

/*! \page SimGridSupport SimGrid Support

StarPU can use SimGrid in order to simulate execution on an arbitrary
platform.

The principle is to first run the application natively on the platform that one
wants to laterlater simulate, and let StarPU record performance models. One
then recompiles StarPU and the application in simgrid mode, where everything
is executed the same, except the execution of the codelet function, and the
data transfers, which are replaced by virtual sleeps based on the performance
models. This thus allows to use the performance model for tasks and data
transfers, while executing natively all the rest (the task scheduler and the
application, notably).

This was tested with SimGrid from 3.11 to 3.16, and 3.18 to
3.35. SimGrid version 3.25 needs to be configured with -Denable_msg=ON .
Other versions may have compatibility issues. 3.17 notably does not build at
all. MPI simulation does not work with version 3.22.

If you have installed SimGrid by hand, make sure to set \c PKG_CONFIG_PATH to
the path where \c simgrid.pc was installed:

\verbatim
$ export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/where/simgrid/installed/lib/ppkgconfig/simgrid.pc
\endverbatim

\section Preparing Preparing Your Application For Simulation

There are a few technical details which need to be handled for an application to
be simulated through SimGrid.

If the application uses <c>gettimeofday()</c> to make its
performance measurements, the real time will be used, which will be bogus. To
get the simulated time, it has to use starpu_timing_now() which returns the
virtual timestamp in us. A basic example is available in <c>tests/main/empty_task.c</c>.

For some technical reason, the application's .c file which contains \c main() has
to be recompiled with \c starpu_simgrid_wrap.h, which in the SimGrid case will <c># define main()</c>
into <c>starpu_main()</c>, and it is \c libstarpu which will provide the real \c main() and
will call the application's \c main(). Including \c starpu.h will already
include \c starpu_simgrid_wrap.h, so usually you would not need to include
\c starpu_simgrid_wrap.h explicitly, but if for some reason including the whole
\c starpu.h header is not possible, you can include \c starpu_simgrid_wrap.h
explicitly.

To be able to test with crazy data sizes, one may want to only allocate
application data if the macro \c STARPU_SIMGRID is not defined.  Passing a <c>NULL</c> pointer to
\c starpu_data_register functions is fine, data will never be read/written to by
StarPU in SimGrid mode anyway.

To be able to run the application with e.g. CUDA simulation on a system which
does not have CUDA installed, one can fill the starpu_codelet::cuda_funcs with \c (void*)1, to
express that there is a CUDA implementation, even if one does not actually
provide it. StarPU will not actually run it in SimGrid mode anyway by default
(unless the ::STARPU_CODELET_SIMGRID_EXECUTE or ::STARPU_CODELET_SIMGRID_EXECUTE_AND_INJECT
flags are set in the codelet)

\snippet simgrid.c To be included. You should update doxygen if you see this text.

The full example is available in <c>examples/cholesky/cholesky_kernels.c</c>.

\section Calibration Calibration

The idea is to first compile StarPU normally, and run the application,
to automatically benchmark the bus and the codelets.

\verbatim
$ ./configure && make
$ STARPU_SCHED=dmda ./examples/matvecmult/matvecmult
[starpu][_starpu_load_history_based_model] Warning: model matvecmult
   is not calibrated, forcing calibration for this run. Use the
   STARPU_CALIBRATE environment variable to control this.
$ ...
$ STARPU_SCHED=dmda ./examples/matvecmult/matvecmult
TEST PASSED
\endverbatim

Note that we force to use the scheduler <c>dmda</c> to generate
performance models for the application. The application may need to be
run several times before the model is calibrated.

\section Simulation Simulation

Then, recompile StarPU, passing \ref enable-simgrid "--enable-simgrid"
to <c>configure</c>. Make sure to keep all the other <c>configure</c> options
the same, and notably options such as <c>--enable-maxcudadev</c>.

\verbatim
$ ./configure --enable-simgrid
\endverbatim

To specify the location of SimGrid, you can either set the environment
variables \c SIMGRID_CFLAGS and \c SIMGRID_LIBS, or use the \c configure
options \ref with-simgrid-dir "--with-simgrid-dir",
\ref with-simgrid-include-dir "--with-simgrid-include-dir" and
\ref with-simgrid-lib-dir "--with-simgrid-lib-dir", for example

\verbatim
$ ./configure --with-simgrid-dir=/opt/local/simgrid
\endverbatim

You can then re-run the application.

\verbatim
$ make
$ STARPU_SCHED=dmda ./examples/matvecmult/matvecmult
TEST FAILED !!!
\endverbatim

It is normal that the test fails: since the computation is not actually done
(that is the whole point of SimGrid), the result is wrong, of course.

If the performance model is not calibrated enough, the following error
message will be displayed

\verbatim
$ STARPU_SCHED=dmda ./examples/matvecmult/matvecmult
[starpu][_starpu_load_history_based_model] Warning: model matvecmult
    is not calibrated, forcing calibration for this run. Use the
    STARPU_CALIBRATE environment variable to control this.
[starpu][_starpu_simgrid_execute_job][assert failure] Codelet
    matvecmult does not have a perfmodel, or is not calibrated enough
\endverbatim

The number of devices can be chosen as usual with \ref STARPU_NCPU,
\ref STARPU_NCUDA, and \ref STARPU_NOPENCL, and the amount of GPU memory
with \ref STARPU_LIMIT_CUDA_MEM, \ref STARPU_LIMIT_CUDA_devid_MEM,
\ref STARPU_LIMIT_OPENCL_MEM, and \ref STARPU_LIMIT_OPENCL_devid_MEM.

\section SimulationOnAnotherMachine Simulation On Another Machine

The SimGrid support even permits to perform simulations on another machine, your
desktop, typically. To achieve this, one still needs to perform the Calibration
step on the actual machine to be simulated, then copy them to your desktop
machine (the <c>$STARPU_HOME/.starpu</c> directory). One can then perform the
Simulation step on the desktop machine, by setting the environment
variable \ref STARPU_HOSTNAME to the name of the actual machine, to
make StarPU use the performance models of the simulated machine even
on the desktop machine. To use multiple performance models in different ranks,
in case of smpi executions in a heterogeneous platform, it is possible to use the
option <c>-hostfile-platform</c> in <c>starpu_smpirun</c>, that will define
\ref STARPU_MPI_HOSTNAMES with the hostnames of your hostfile.

If the desktop machine does not have CUDA or OpenCL, StarPU is still able to
use SimGrid to simulate execution with CUDA/OpenCL devices, but the application
source code will probably disable the CUDA and OpenCL codelets in that
case. Since during SimGrid execution, the functions of the codelet are actually
not called by default, one can use dummy functions such as the following to
still permit CUDA or OpenCL execution.

\section SimulationExamples Simulation Examples

StarPU ships a few performance models for a couple of systems: \c attila,
\c mirage, \c idgraf, and \c sirocco. See Section \ref SimulatedBenchmarks for the details.

\section FakeSimulations Simulations On Fake Machines

It is possible to build fake machines which do not exist, by modifying the
platform file in <c>$STARPU_HOME/.starpu/sampling/bus/machine.platform.xml</c>
by hand: one can add more CPUs, add GPUs (but the performance model file has to
be extended as well), change the available GPU memory size, PCI memory bandwidth, etc.

\section TweakingSimulation Tweaking Simulation

The simulation can be tweaked, to be able to tune it between a very accurate
simulation and a very simple simulation (which is thus close to scheduling
theory results), see the \ref STARPU_SIMGRID_TRANSFER_COST, \ref STARPU_SIMGRID_CUDA_MALLOC_COST,
\ref STARPU_SIMGRID_CUDA_QUEUE_COST, \ref STARPU_SIMGRID_TASK_SUBMIT_COST, \ref STARPU_SIMGRID_TASK_PUSH_COST,
\ref STARPU_SIMGRID_FETCHING_INPUT_COST and \ref STARPU_SIMGRID_SCHED_COST environment variables.

\section SimulationMPIApplications MPI Applications

StarPU-MPI applications can also be run in SimGrid mode. smpi currently requires
that StarPU be build statically only, so <c>--disable-shared</c> needs to be
passed to <c>./configure</c>.

The application needs to be compiled with \c smpicc, and run using the
<c>starpu_smpirun</c> script, for instance:

\verbatim
$ STARPU_SCHED=dmda starpu_smpirun -platform cluster.xml -hostfile hostfile ./mpi/tests/pingpong
\endverbatim

Where \c cluster.xml is a SimGrid-MPI platform description, and \c hostfile the
list of MPI nodes to be used. Examples of such files are available in \c tools/perfmodels. In homogeneous MPI clusters: for each MPI node, it
will just replicate the architecture referred by
\ref STARPU_HOSTNAME. To use multiple performance models in different ranks,
in case of a heterogeneous platform, it is possible to use the
option <c>-hostfile-platform</c> in <c>starpu_smpirun</c>, that will define
\ref STARPU_MPI_HOSTNAMES with the hostnames of your hostfile.

To use FxT traces, libfxt itself also needs to be built statically, <b>and</b>
with dynamic linking flags, i.e. with

\verbatim
CFLAGS=-fPIC ./configure --enable-static
\endverbatim

\section SimulationDebuggingApplications Debugging Applications

By default, SimGrid uses its own implementation of threads, which prevents \c gdb
from being able to inspect stacks of all threads.  To be able to fully debug an
application running with SimGrid, pass the <c>--cfg=contexts/factory:thread</c>
option to the application, to make SimGrid use system threads, which \c gdb will be
able to manipulate as usual.

It is also worth noting SimGrid 3.21's new parameter
<c>--cfg=simix/breakpoint</c> which allows putting a breakpoint at a precise
(deterministic!) timing of the execution. If for instance in an execution
trace we see that something odd is happening at time 19000ms, we can use
<c>--cfg=simix/breakpoint:19.000</c> and \c SIGTRAP will be raised at that point,
which will thus interrupt execution within \c gdb, allowing to inspect e.g.
scheduler state, etc.

\section SimulationMemoryUsage Memory Usage

Since kernels are not actually run and data transfers are not actually
performed, the data memory does not actually need to be allocated.  This allows
for instance to simulate the execution of applications processing very big data
on a small laptop.

The application can for instance pass <c>1</c> (or whatever bogus pointer)
to StarPU data registration functions, instead of allocating data. This will
however require the application to take care of not trying to access the data,
and will not work in MPI mode, which performs transfers.

Another way is to pass the \ref STARPU_MALLOC_SIMULATION_FOLDED flag to the
starpu_malloc_flags() function.
An example is available in <c>examples/mult/xgemm.c </c>
This will make it allocate a memory area which
one can read/write, but optimized so that this does not actually consume
memory. Of course, the values read from such area will be bogus, but this allows
the application to keep e.g. data load, store, initialization as it is, and also
work in MPI mode. A more aggressive alternative is to pass also the
\ref STARPU_MALLOC_SIMULATION_UNIQUE flag (alongside with
\ref STARPU_MALLOC_SIMULATION_FOLDED) to the starpu_malloc_flags() function.
An example is available in <c>examples/cholesky/cholesky_tag.c </c>.
This will make StarPU reuse the pointers for allocations of the same size
without calling the folded allocation again, thus decreasing some pressure on
memory management.

Note however that notably Linux kernels refuse obvious memory overcommitting by
default, so a single allocation can typically not be bigger than the amount of
physical memory, see https://www.kernel.org/doc/Documentation/vm/overcommit-accounting
This prevents for instance from allocating a single huge matrix. Allocating a
huge matrix in several tiles is not a problem, however. <c>sysctl
vm.overcommit_memory=1</c> can also be used to allow such overcommit.

Note however that this folding is done by remapping the same file several times,
and Linux kernels will also refuse to create too many memory areas. <c>sysctl
vm.max_map_count</c> can be used to check and change the default (65535). By
default, StarPU uses a 1MiB file, so it hopefully fits in the CPU cache. However,
this limits the amount of such folded memory to a bit below 64GiB. The
\ref STARPU_MALLOC_SIMULATION_FOLD environment variable can be used to increase the
size of the file.

*/
