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Darshan-runtime installation and usage

== Introduction

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This document describes darshan-runtime, which is the instrumentation
portion of the Darshan characterization tool.  It should be installed on the
system where you intend to collect I/O characterization information.

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Darshan instruments applications via either compile time wrappers for static
executables or dynamic library preloading for dynamic executables.  An
application that has been instrumented with Darshan will produce a single
log file each time it is executed.  This log summarizes the I/O access patterns
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used by the application.

The darshan-runtime instrumentation only instruments MPI applications (the
application must at least call `MPI_Init()` and `MPI_Finalize()`).  However,
it captures both MPI-IO and POSIX file access.  It also captures limited
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information about HDF5 and PnetCDF access. Darshan also exposes an API that
can be used to develop and add new instrumentation modules (for other I/O library
interfaces or to gather system-specific data, for instance), as detailed in
http://www.mcs.anl.gov/research/projects/darshan/docs/darshan-modularization.html[this document].
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Newly contributed modules include a module for gathering system-specific parameters
for jobs running on BG/Q systems, a module for gathering Lustre striping data for
files on Lustre file systems, and a module for instrumenting stdio (i.e., stream I/O
functions like `fopen()`, `fread()`, etc).

Starting in version 3.1.3, Darshan also allows for full tracing of application I/O
workloads using the newly developed Darshan eXtended Tracing (DxT) instrumentation
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module. This module can be selectively enabled at runtime to provide high-fidelity
traces of an application's I/O workload, as opposed to the coarse-grained I/O summary
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data that Darshan has traditionally provided. Currently, DxT only traces at the POSIX
and MPI-IO layers. Initial link:DXT-overhead.pdf[performance results] demonstrate the
low overhead of DxT tracing, offering comparable performance to Darshan's traditional
coarse-grained instrumentation methods.

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This document provides generic installation instructions, but "recipes" for
several common HPC systems are provided at the end of the document as well.

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More information about Darshan can be found at the 
http://www.mcs.anl.gov/darshan[Darshan web site].

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== Requirements

* MPI C compiler
* zlib development headers and library

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== Compilation
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.Configure and build example
tar -xvzf darshan-<version-number>.tar.gz
cd darshan-<version-number>/darshan-runtime
./configure --with-mem-align=8 --with-log-path=/darshan-logs --with-jobid-env=PBS_JOBID CC=mpicc
make install

.Explanation of configure arguments:
* `--with-mem-align=` (mandatory): This value is system-dependent and will be
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used by Darshan to determine if the buffer for a read or write operation is
aligned in memory.
* `--with-jobid-env=` (mandatory): this specifies the environment variable that
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Darshan should check to determine the jobid of a job.  Common values are
`PBS_JOBID` or `COBALT_JOBID`.  If you are not using a scheduler (or your
scheduler does not advertise the job ID) then you can specify `NONE` here.
Darshan will fall back to using the pid of the rank 0 process if the
specified environment variable is not set.
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* `--with-log-path=` (this, or `--with-log-path-by-env`, is mandatory): This
specifies the parent directory for the directory tree where darshan logs
will be placed.
* `--with-log-path-by-env=`: specifies an environment variable to use to
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determine the log path at run time.
* `--with-log-hints=`: specifies hints to use when writing the Darshan log
file.  See `./configure --help` for details.
* `--with-mod-mem=`: specifies the maximum amount of memory (in MiB) that
active Darshan instrumentation modules can collectively consume.
* `--with-zlib=`: specifies an alternate location for the zlib development
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header and library.
* `CC=`: specifies the MPI C compiler to use for compilation.
* `--enable-mmap-logs`: enables the use of Darshan's mmap log file mechanism.
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* `--disable-cuserid`: disables use of cuserid() at runtime.
* `--disable-ld-preload`: disables building of the Darshan LD_PRELOAD library
* `--disable-bgq-mod`: disables building of the BG/Q module (default checks
and only builds if BG/Q environment detected).
* `--enable-group-readable-logs`: sets darshan log file permissions to allow
group read access.
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* `--enable-HDF5-pre-1.10`: enables the Darshan HDF5 instrumentation module,
with support for HDF5 versions prior to 1.10
* `--enable-HDF5-post-1.10`: enables the Darshan HDF5 instrumentation module,
with support for HDF5 versions 1.10 or higher
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=== Cross compilation

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On some systems (notably the IBM Blue Gene series), the login nodes do not
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have the same architecture or runtime environment as the compute nodes.  In
this case, you must configure darshan-runtime to be built using a cross
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compiler.  The following configure arguments show an example for the BG/P system:
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--host=powerpc-bgp-linux CC=/bgsys/drivers/ppcfloor/comm/default/bin/mpicc 

== Environment preparation

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Once darshan-runtime has been installed, you must prepare a location
in which to store the Darshan log files and configure an instrumentation method.
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=== Log directory

This step can be safely skipped if you configured darshan-runtime using the
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`--with-log-path-by-env` option.  A more typical configuration uses a static
directory hierarchy for Darshan log
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The `darshan-mk-log-dirs.pl` utility will configure the path specified at
configure time to include
subdirectories organized by year, month, and day in which log files will be
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placed. The deepest subdirectories will have sticky permissions to enable
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multiple users to write to the same directory.  If the log directory is
shared system-wide across many users then the following script should be run
as root.

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.A note about log directory permissions
All log files written by darshan have permissions set to only allow
read access by the owner of the file.  You can modify this behavior,
however, by specifying the --enable-group-readable-logs option at
configure time.  One notable deployment scenario would be to configure
Darshan and the log directories to allow all logs to be readable by both the
end user and a Darshan administrators group.   This can be done with the
following steps:

* set the --enable-group-readable-logs option at configure time
* create the log directories with darshan-mk-log-dirs.pl
* recursively set the group ownership of the log directories to the Darshan
administrators group
* recursively set the setgid bit on the log directories

=== Instrumentation method

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The instrumentation method to use depends on whether the executables
produced by your MPI compiler are statically or dynamically linked.  If you
are unsure, you can check by running `ldd <executable_name>` on an example
executable.  Dynamically-linked executables will produce a list of shared
libraries when this command is executed.

Most MPI compilers allow you to toggle dynamic or static linking via options
such as `-dynamic` or `-static`.  Please check your MPI compiler man page
for details if you intend to force one mode or the other.
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== Instrumenting statically-linked applications

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Statically linked executables must be instrumented at compile time.
The simplest methods to do this are to either generate a customized
MPI compiler script (e.g. `mpicc`) that includes the link options and
libraries needed by Darshan, or to use existing profiling configuration
hooks for existing MPI compiler scripts.  Once this is done, Darshan
instrumentation is transparent; you simply compile applications using
the darshan-enabled MPI compiler scripts.

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=== Using a profile configuration 

The MPICH MPI implementation supports the specification of a profiling library
configuration that can be used to insert Darshan instrumentation without
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modifying the existing MPI compiler script.  Example profiling configuration
files are installed with Darshan 2.3.1 and later.  You can enable a profiling
configuration using environment variables or command line arguments to the
compiler scripts:

Example for MPICH 3.1.1 or newer:
export MPICC_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-cc
export MPICXX_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-cxx
export MPIFORT_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-f

Example for MPICH 3.1 or earlier:
export MPICC_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-cc
export MPICXX_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-cxx
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export MPIF77_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-f
export MPIF90_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-f
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Examples for command line use:
mpicc -profile=$DARSHAN_PREFIX/share/mpi-profile/darshan-c <args>
mpicxx -profile=$DARSHAN_PREFIX/share/mpi-profile/darshan-cxx <args>
mpif77 -profile=$DARSHAN_PREFIX/share/mpi-profile/darshan-f <args>
mpif90 -profile=$DARSHAN_PREFIX/share/mpi-profile/darshan-f <args>

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=== Using customized compiler wrapper scripts

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For MPICH-based MPI libraries, such as MPICH1, MPICH2, or MVAPICH,
custom wrapper scripts can be generated to automatically include Darshan
instrumentation.  The following example illustrates how to produce
wrappers for C, C++, and Fortran compilers:

darshan-gen-cc.pl `which mpicc` --output mpicc.darshan
darshan-gen-cxx.pl `which mpicxx` --output mpicxx.darshan
darshan-gen-fortran.pl `which mpif77` --output mpif77.darshan
darshan-gen-fortran.pl `which mpif90` --output mpif90.darshan

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=== Other configurations

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Please see the Cray recipe in this document for instructions on
instrumenting statically-linked applications on that platform.

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For other MPI Libraries you must manually modify the MPI compiler scripts to
add the necessary link options and libraries.  Please see the
`darshan-gen-*` scripts for examples or contact the Darshan users mailing
list for help.
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== Instrumenting dynamically-linked applications

For dynamically-linked executables, darshan relies on the `LD_PRELOAD`
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environment variable to insert instrumentation at run time.  The executables
should be compiled using the normal, unmodified MPI compiler.
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To use this mechanism, set the `LD_PRELOAD` environment variable to the full
path to the Darshan shared library. The preferred method of inserting Darshan
instrumentation in this case is to set the `LD_PRELOAD` variable specifically
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for the application of interest. Typically this is possible using
command line arguments offered by the `mpirun` or `mpiexec` scripts or by
the job scheduler:
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mpiexec -n 4 -env LD_PRELOAD /home/carns/darshan-install/lib/libdarshan.so mpi-io-test

srun -n 4 --export=LD_PRELOAD=/home/carns/darshan-install/lib/libdarshan.so mpi-io-test

For sequential programs, the following will set LD_PRELOAD for process duration only:

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env LD_PRELOAD=/home/carns/darshan-install/lib/libdarshan.so mpi-io-test

Other environments may have other specific options for controlling this behavior.
Please check your local site documentation for details.

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It is also possible to just export LD_PRELOAD as follows, but it is recommended
against doing that to prevent Darshan and MPI symbols from being pulled into
unrelated binaries:

export LD_PRELOAD=/home/carns/darshan-install/lib/libdarshan.so

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For SGI systems running the MPT environment, it may be necessary to set the `MPI_SHEPHERD`
environment variable equal to `true` to avoid deadlock when preloading the Darshan shared

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=== Instrumenting dynamically-linked Fortran applications

Please follow the general steps outlined in the previous section.  For
Fortran applications compiled with MPICH you may have to take the additional
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step of adding
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`libfmpich.so` to your `LD_PRELOAD` environment variable. For example:

export LD_PRELOAD=/path/to/mpi/used/by/executable/lib/libfmpich.so:/home/carns/darshan-install/lib/libdarshan.so

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The full path to the libfmpich.so library can be omitted if the rpath
variable points to the correct path.  Be careful to check the rpath of the
darshan library and the executable before using this configuration, however.
They may provide conflicting paths.  Ideally the rpath to the  MPI library
would *not* be set by the darshan library, but would instead be specified
exclusively by the executable itself.  You can check the rpath of the
darshan library by running `objdump -x
/home/carns/darshan-install/lib/libdarshan.so |grep RPATH`.

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== Darshan installation recipes

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The following recipes provide examples for prominent HPC systems.
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These are intended to be used as a starting point.  You will most likely have to adjust paths and options to
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reflect the specifics of your system.

=== IBM Blue Gene (BG/P or BG/Q)

IBM Blue Gene systems produces static executables by default, uses a
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different architecture for login and compute nodes, and uses an MPI
environment based on MPICH.

The following example shows how to configure Darshan on a BG/P system:

./configure --with-mem-align=16 \
 --with-log-path=/home/carns/working/darshan/releases/logs \
 --prefix=/home/carns/working/darshan/install --with-jobid-env=COBALT_JOBID \
 --with-zlib=/soft/apps/zlib-1.2.3/ \
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 --host=powerpc-bgp-linux CC=/bgsys/drivers/ppcfloor/comm/default/bin/mpicc 

The memory alignment is set to 16 not because that is the proper alignment
for the BG/P CPU architecture, but because that is the optimal alignment for
the network transport used between compute nodes and I/O nodes in the
system.  The jobid environment variable is set to `COBALT_JOBID` in this
case for use with the Cobalt scheduler, but other BG/P systems may use
different schedulers.  The `--with-zlib` argument is used to point to a
version of zlib that has been compiled for use on the compute nodes rather
than the login node.  The `--host` argument is used to force cross-compilation
of Darshan.  The `CC` variable is set to point to a stock MPI compiler.

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Once Darshan has been installed, you can use one of the static
instrumentation methods described earlier in this document.  If you
use the profiling configuration file method, then please note that the
Darshan installation includes profiling configuration files that have been
adapted specifically for the Blue Gene environment.  Set the following
environment variables to enable them, and then use your normal compiler
scripts.  This method is compatible with both GNU and IBM compilers.

Blue Gene profiling configuration example:
export MPICC_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-bg-cc
export MPICXX_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-bg-cxx
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export MPIF77_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-bg-f
export MPIF90_PROFILE=$DARSHAN_PREFIX/share/mpi-profile/darshan-bg-f

=== Cray platforms (XE, XC, or similar)

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The Cray programming environment produces static executables by default,
which means that Darshan instrumentation must be inserted at compile
time.  This can be accomplished by loading a software module that sets
appropriate environment variables to modify the Cray compiler script link
behavior.  This section describes how to compile and install Darshan,
as well as how to use a software module to enable and disable Darshan
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==== Building and installing Darshan

Please set your environment to use the GNU programming environment before
configuring or compiling Darshan.  Although Darshan can be built with a
variety of compilers, the GNU compilers are recommended because it will
produce a Darshan library that is interoperable with the widest range
of compilers and linkers.  On most Cray systems you can enable the GNU
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programming environment with a command similar to "module swap PrgEnv-pgi
PrgEnv-gnu".  Please see your site documentation for information about
how to switch programming environments.
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The following example shows how to configure and build Darshan on a Cray
system using the GNU programming environment.  Adjust the 
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--with-log-path and --prefix arguments to point to the desired log file path 
and installation path, respectively.
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module swap PrgEnv-pgi PrgEnv-gnu
./configure --with-mem-align=8 \
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 --with-log-path=/shared-file-system/darshan-logs \
 --prefix=/soft/darshan-2.2.3 \
 --with-jobid-env=PBS_JOBID --disable-cuserid CC=cc
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make install
module swap PrgEnv-gnu PrgEnv-pgi
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The job ID is set to `PBS_JOBID` for use with a Torque or PBS based scheduler.
The `CC` variable is configured to point the standard MPI compiler.
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The --disable-cuserid argument is used to prevent Darshan from attempting to
use the cuserid() function to retrieve the user name associated with a job.
Darshan automatically falls back to other methods if this function fails,
but on some Cray environments (notably the Beagle XE6 system as of March 2012)
the cuserid() call triggers a segmentation fault.  With this option set,
Darshan will typically use the LOGNAME environment variable to determine a
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As in any Darshan installation, the darshan-mk-log-dirs.pl script can then be 
used to create the appropriate directory hierarchy for storing Darshan log 
files in the --with-log-path directory.
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Note that Darshan is not currently capable of detecting the stripe size
(and therefore the Darshan FILE_ALIGNMENT value) on Lustre file systems.
If a Lustre file system is detected, then Darshan assumes an optimal
file alignment of 1 MiB.

==== Enabling Darshan instrumentation 

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Darshan will automatically install example software module files in the
following locations (depending on how you specified the --prefix option in
the previous section):
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Select the one that is appropriate for your Cray programming environment
(see the version number of the craype module in `module list`).
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If you are using the Cray Programming Environment version 1.x, then you
must modify the corresponding modulefile before using it.  Please see
the comments at the end of the file and choose an environment variable
method that is appropriate for your system.  If this is not done, then
the compiler may fail to link some applications when the Darshan module
is loaded.

If you are using the Cray Programming Environment version 2.x then you can
likely use the modulefile as is.  Note that it pulls most of its
configuration from the lib/pkgconfig/darshan-runtime.pc file installed with

The modulefile that you select can be copied to a system location, or the
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install location can be added to your local module path with the following
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module use /soft/darshan-2.2.3/share/craype-<VERSION>/modulefiles
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From this point, Darshan instrumenation can be enabled for all future
application compilations by running "module load darshan".
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=== Linux clusters using Intel MPI 

Most Intel MPI installations produce dynamic executables by default.  To
configure Darshan in this environment you can use the following example:

./configure --with-mem-align=8 --with-log-path=/darshan-logs --with-jobid-env=PBS_JOBID CC=mpicc

There is nothing unusual in this configuration except that you should use
the underlying GNU compilers rather than the Intel ICC compilers to compile
Darshan itself.

You can use the `LD_PRELOAD` method described earlier in this document to
instrument executables compiled with the Intel MPI compiler scripts.  This
method has been briefly tested using both GNU and Intel compilers.

Darshan is only known to work with C and C++ executables generated by the
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Intel MPI suite in versions prior to the 2017 version -- Darshan will not
produce instrumentation for Fortran executables in these earlier versions (pre-2017).
For more details on this issue please check this Intel forum discussion:
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=== Linux clusters using MPICH 

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Follow the generic instructions provided at the top of this document.  For MPICH versions 3.1 and
later, MPICH uses shared libraries by default, so you may need to consider the dynamic linking
instrumentation approach.  

The static linking method can be used if MPICH is configured to use static
linking by default, or if you are using a version prior to 3.1.
The only modification is to make sure that the `CC` used for compilation is
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based on a GNU compiler.  Once Darshan has been installed, it should be
capable of instrumenting executables built with GNU, Intel, and PGI

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Darshan is not capable of instrumenting Fortran applications build with MPICH versions 3.1.1, 3.1.2,
or 3.1.3 due to a library symbol name compatibility issue.  Consider using a newer version of
MPICH if you wish to instrument Fortran applications.  Please see
http://trac.mpich.org/projects/mpich/ticket/2209 for more details.

MPICH versions 3.1, 3.1.1, 3.1.2, and 3.1.3 may produce link-time errors when building static
executables (i.e. using the -static option) if MPICH is built with shared library support.
Please see http://trac.mpich.org/projects/mpich/ticket/2190 for more details.  The workaround if you
wish to use static linking is to configure MPICH with `--enable-shared=no --enable-static=yes` to
force it to use static MPI libraries with correct dependencies.

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=== Linux clusters using Open MPI

Follow the generic instructions provided at the top of this document for
compilation, and make sure that the `CC` used for compilation is based on a
GNU compiler.

Open MPI typically produces dynamically linked executables by default, which
means that you should use the `LD_PRELOAD` method to instrument executables
that have been built with Open MPI.  Darshan is only compatible with Open
MPI 1.6.4 and newer.  For more details on why Darshan is not compatible with
older versions of Open MPI, please refer to the following mailing list discussion:


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== Upgrading to Darshan 3.x from 2.x

Beginning with Darshan 3.0.0, Darshan has been rewritten to modularize its runtime environment
and log file format to simplify the addition of new I/O characterization data. The process of
compiling and installing the Darshan 3.x source code should essentially be identical to this
process on Darshan 2.x. Therefore, the installation recipes given in the previous section
should work irrespective of the Darshan version being used. Similarly, the manner in which
Darshan is used should be the same across versions -- the sections in this document regarding
Darshan link:darshan-runtime.html#_environment_preparation[environment preparation],
instrumenting link:darshan-runtime.html#_instrumenting_statically_linked_applications[statically
linked applications] and link:darshan-runtime.html#_instrumenting_dynamically_linked_applications[
dynamically linked applications], and using link:darshan-runtime.html#_runtime_environment_variables[
runtime environment variables] are equally applicable to both versions.

However, we do provide some suggestions and expectations for system administrators to keep in
mind when upgrading to Darshan 3.x:

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* Darshan 2.x and Darshan 3.x produce incompatible log file formats
    ** log files named *.darshan.gz or *.darshan.bz2: Darshan 2.x format
    ** log files named *.darshan: Darshan 3.x format
        *** a field in the log file header indicates underlying compression method in 3.x logs
    ** There is currently no tool for converting 2.x logs into the 3.x log format.
    ** The `darshan-logutils` library will provide error messages to indicate whether a given
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log file is incompatible with the correspnonding library version. 
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* We encourage administrators to use the same log file directory for version 3.x as had been
used for version 2.x.
    ** Within this directory, the determination on which set of log utilities (version 2.x
or version 3.x) to use can be based on the file extension for a given log (as explained
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== Runtime environment variables

The Darshan library honors the following environment variables to modify
behavior at runtime:

* DARSHAN_DISABLE: disables Darshan instrumentation
* DARSHAN_INTERNAL_TIMING: enables internal instrumentation that will print the time required to startup and shutdown Darshan to stderr at run time.
* DARSHAN_LOGHINTS: specifies the MPI-IO hints to use when storing the Darshan output file.  The format is a semicolon-delimited list of key=value pairs, for example: hint1=value1;hint2=value2
* DARSHAN_MEMALIGN: specifies a value for system memory alignment
* DARSHAN_JOBID: specifies the name of the environment variable to use for the job identifier, such as PBS_JOBID
* DARSHAN_DISABLE_SHARED_REDUCTION: disables the step in Darshan aggregation in which files that were accessed by all ranks are collapsed into a single cumulative file record at rank 0.  This option retains more per-process information at the expense of creating larger log files. Note that it is up to individual instrumentation module implementations whether this environment variable is actually honored.
* DARSHAN_LOGPATH: specifies the path to write Darshan log files to. Note that this directory needs to be formatted using the darshan-mk-log-dirs script.
* DARSHAN_LOGFILE: specifies the path (directory + Darshan log file name) to write the output Darshan log to. This overrides the default Darshan behavior of automatically generating a log file name and adding it to a log file directory formatted using darshan-mk-log-dirs script.
* DARSHAN_MODMEM: specifies the maximum amount of memory (in MiB) Darshan instrumentation modules can collectively consume at runtime (if not specified, Darshan uses a default quota of 2 MiB).
* DARSHAN_MMAP_LOGPATH: if Darshan's mmap log file mechanism is enabled, this variable specifies what path the mmap log files should be stored in (if not specified, log files will be stored in `/tmp`).
* DARSHAN_EXCLUDE_DIRS: specifies a list of comma-separated paths that Darshan will not instrument at runtime (in addition to Darshan's default blacklist)
* DXT_ENABLE_IO_TRACE: setting this environment variable enables the DXT (Darshan eXtended Tracing) modules at runtime. Users can specify a numeric value for this variable to set the number of MiB to use for tracing per process; if no value is specified, Darshan will use a default value of 4 MiB.
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== Debugging

=== No log file

In cases where Darshan is not generating a log file for an application, some common things to check are:

* Check stderr to ensure Darshan isn't indicating any internal errors (e.g., invalid log file path)

For statically linked executables:

* Ensure that Darshan symbols are present in the underlying executable by running `nm` on it:
> nm test | grep darshan
0000000000772260 b darshan_core
0000000000404440 t darshan_core_cleanup
00000000004049b0 T darshan_core_initialize
000000000076b660 d darshan_core_mutex
00000000004070a0 T darshan_core_register_module

* Make sure the application executable is statically linked:
    ** In general, we encourage the use of purely statically linked executables when using the static
instrumentation method given in link:darshan-runtime.html#_instrumenting_statically_linked_applications[Section 5]
    ** If purely static executables are not an option, we encourage users to use the LD_PRELOAD method of
instrumentation given in link:darshan-runtime.html#_instrumenting_dynamically_linked_applications[Section 6]
    ** Statically linked executables are the default on Cray platforms and the IBM BG platforms; 
statically linked executables can be explicitly requested using the `-static` compile option to most compilers
    ** You can verify that an executable is purely statically linked by using the `file` command:
> file mpi-io-test
mpi-io-test: ELF 64-bit LSB  executable, x86-64, version 1 (GNU/Linux), statically linked, for GNU/Linux 2.6.24, BuildID[sha1]=9893e599e7a560159ccf547b4c4ba5671f65ba32, not stripped

* Ensure that the linker is correctly linking in Darshan's runtime libraries:
    ** A common mistake is to explicitly link in the underlying MPI libraries (e.g., `-lmpich` or `-lmpichf90`)
in the link command, which can interfere with Darshan's instrumentation
        *** These libraries are usually linked in automatically by the compiler
        *** MPICH's `mpicc` comipler's `-show` flag can be used to examine the invoked link command, for instance
    ** The linker's `-y` option can be used to verify that Darshan is properly intercepting MPI_Init
function (e.g. by setting `CFLAGS='-Wl,-yMPI_Init'`), which it uses to initialize its runtime structures
/usr/common/software/darshan/3.0.0-pre3/lib/libdarshan.a(darshan-core-init-finalize.o): definition of MPI_Init