Darshan-runtime installation and usage

Table of Contents

1. Introduction
2. Requirements
3. Conventional installation
3.1. Compilation
3.2. Environment preparation
4. Spack installation
5. Instrumenting applications
5.1. Option 1: Instrumenting MPI applications at compile time
5.2. Option 2: Instrumenting MPI applications at runtime
5.3. Option 3: Instrumenting non-MPI applications at runtime
5.4. Using other profiling tools at the same time as Darshan
6. Using the Darshan eXtended Tracing (DXT) module
7. Using AutoPerf instrumentation modules
8. Configuring Darshan library at runtime
8.1. Darshan library config settings
8.2. Example Darshan configuration
9. Darshan installation recipes
9.1. Cray platforms (XE, XC, or similar)
9.2. Linux clusters using MPICH
9.3. Linux clusters using Intel MPI
9.4. Linux clusters using Open MPI
10. Debugging
10.1. No log file

1. Introduction

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.

Darshan instruments applications via either compile time wrappers or dynamic library preloading. 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 used by the application.

The darshan-runtime instrumentation has traditionally only supported MPI applications (specifically, those that call MPI_Init() and MPI_Finalize()), but, as of version 3.2.0, Darshan also supports instrumentation of non-MPI applications. Regardless of whether MPI is used, Darshan provides detailed statistics about POSIX level file accesses made by the application. In the case of MPI applications, Darshan additionally captures details on MPI-IO and HDF5 level access, as well as limited information about PnetCDF access. Note that instrumentation of non-MPI applications is currently only supported in Darshan’s shared library, which applications must LD_PRELOAD.

Starting in version 3.0.0, 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 this document. 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 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 data that Darshan has traditionally provided. Currently, DxT only traces at the POSIX and MPI-IO layers. Initial performance results demonstrate the low overhead of DxT tracing, offering comparable performance to Darshan’s traditional coarse-grained instrumentation methods.

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

More information about Darshan can be found at the Darshan web site.

2. Requirements

  • C compiler (preferably GCC-compatible)
  • zlib development headers and library

3. Conventional installation

3.1. Compilation

Configure and build example (with MPI support). 

tar -xvzf darshan-<version-number>.tar.gz
cd darshan-<version-number>/
cd darshan-runtime/
./configure --with-log-path=/darshan-logs --with-jobid-env=PBS_JOBID CC=mpicc
make install

Configure and build example (without MPI support). 

tar -xvzf darshan-<version-number>.tar.gz
cd darshan-<version-number>/
cd darshan-runtime/
./configure --with-log-path=/darshan-logs --with-jobid-env=PBS_JOBID --without-mpi CC=gcc
make install

Explanation of configure arguments:

  • --with-mem-align=NUM: This value is system-dependent and will be used by Darshan to determine if the buffer for a read or write operation is aligned in memory (default is 8).
  • --with-jobid-env=NAME (mandatory): this specifies the environment variable that 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.
  • --with-username-env=NAME: this specifies the environment variable that Darshan should check to determine the username for a job. If not specified, Darshan will use internal mechanisms to try to determine the username.

    • NOTE: Darshan relies on the LOGNAME environment variable to determine a username, but this method isn’t always reliable (e.g., on Slurm systems, LOGNAME can be wiped when specifying additional environment variables using the --export option to srun). This configure option allows specification of an additional environment variable to extract a username from (e.g., SLURM_JOB_USER).
  • --with-log-path=DIR (this, or --with-log-path-by-env, is mandatory): This specifies the parent directory for the directory tree where Darshan logs will be placed.

    • NOTE: after installation, any user can display the configured path with the darshan-config --log-path command
  • --with-log-path-by-env=NAME1,NAME2,...: specifies a comma separated list of environment variables to check at runtime for log path location before the one set by --with-log-path=DIR at configure time.
  • --with-log-hints=hint1=x;hint2=y,...: specifies hints to use when writing the Darshan log file. See ./configure --help for details.
  • --with-mod-mem=NUM: specifies the maximum amount of memory (in MiB) that active Darshan instrumentation modules can collectively consume.
  • --with-zlib=DIR: specifies an alternate location for the zlib development header and library.
  • --without-mpi: disables MPI support when building Darshan - MPI support is assumed if not specified.
  • --enable-mmap-logs: enables the use of Darshan’s mmap log file mechanism.
  • --enable-cuserid: enables use of cuserid() at runtime.
  • --disable-ld-preload: disables building of the Darshan LD_PRELOAD library
  • --enable-group-readable-logs: sets Darshan log file permissions to allow group read access.
  • CC=: specifies the C compiler to use for compilation.

Configure arguments for controlling which Darshan modules to use:

  • --disable-posix-mod: disables compilation and use of Darshan’s POSIX module (default=enabled)
  • --disable-mpiio-mod: disables compilation and usee of Darshan’s MPI-IO module (default=enabled)
  • --disable-stdio-mod: disables compilation and use of Darshan’s STDIO module (default=enabled)
  • --disable-dxt-mod: disables compilation and use of Darshan’s DXT module (default=enabled)
  • --enable-hdf5-mod: enables compilation and use of Darshan’s HDF5 module (default=disabled)
  • --with-hdf5=DIR: installation directory for HDF5

    • NOTE: Users must call --enable-hdf5-mod to enable HDF5 modules, --with-hdf5 is only used to additionally provide an HDF5 install prefix.
    • NOTE: HDF5 instrumentation only works on HDF5 library versions >=1.8, and further requires that the HDF5 library used to build Darshan and the HDF5 library being linked in either both be version >=1.10 or both be version <1.10
    • NOTE: This option does not work with the profile configuration instrumentation method described in the "Instrumenting applications" section (Using a profile configuration)
  • --enable-pnetcdf-mod: enables compilation and use of Darshan’s PnetCDF module (default=disabled)
  • --with-pnetcdf=DIR: installation directory for PnetCDF

    • NOTE: Users must call --enable-pnetcdf-mod to enable PnetCDF modules, --with-pnetcdf is only used to additionally provide a PnetCDF install prefix.
    • NOTE: PnetCDF instrumentation only works on PnetCDF library versions >=1.8
  • --disable-lustre-mod: disables compilation and use of Darshan’s Lustre module (default=enabled)
  • --enable-mdhim-mod: enables compilation and use of Darshan’s MDHIM module (default=disabled)

3.2. Environment preparation

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

This step can be safely skipped if you configured darshan-runtime using the --with-log-path-by-env option. A more typical configuration uses a static directory hierarchy for Darshan log files.

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 placed. The deepest subdirectories will have sticky permissions to enable 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.


A note about finding log paths after installation

Regardless of whether a Darshan installation is using the --with-log-path or --with-log-path-by-env option, end users can display the path (and/or environment variables) at any time by running darshan-config --log-path on the command line.

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

4. Spack installation

You can also install Darshan via Spack as an alternative to manual download, compilation, and installation. This may be especially convenient for single-user installs. Darshan is divided into two separate packages for the command line utilities and runtime instrumentation. You can install either or both as follows:

spack install darshan-util
spack install darshan-runtime


Darshan will generally compile and install fine using a variety of compilers, but we advise using a gcc compiler in Spack to compile Darshan (regardless of what compiler you will use for your applications) to ensure maximum runtime compatibility.

You can use the spack info darshan-runtime query to view the full list of variants available for the darshan-runtime Spack package. For example, adding a +slurm to the command line (spack install darshan-runtime+slurm) will cause Darshan to be compiled with support for gathering job ID information from the Slurm scheduler.

The following commands will load the Darshan packages once they have been installed:

spack load -r darshan-util
spack load -r darshan-runtime

Note that the spack install of darshan-runtime will use an environment variable named $DARSHAN_LOG_DIR_PATH to indicate where it should store log files. This variable is set to the user’s home directory by default when the package is loaded, but it may be overridden.

On Cray systems, you can also perform an additional step to load a Cray-specific module file. This will make a module called darshan available as described later in this document in the Cray platform recipe. It enables automatic instrumentation when using the standard Cray compiler wrappers.

module use `spack location -i darshan-runtime`/share/craype-2.x/modulefiles

5. Instrumenting applications


More specific installation "recipes" are provided later in this document for some platforms. This section of the documentation covers general techniques.

Once Darshan has been installed and a log path has been prepared, the next step is to actually instrument applications. The preferred method is to instrument applications at compile time.

5.1. Option 1: Instrumenting MPI applications at compile time

This method is applicable to C, Fortran, and C++ MPI applications (regardless of whether they are static or dynamically linked) and is the most straightforward method to apply transparently system-wide. It works by injecting additional libraries and options into the linker command line to intercept relevant I/O calls.

On Cray platforms you can enable the compile time instrumentation by simply loading the Darshan module. It can then be enabled for all users by placing that module in the default environment. As of Darshan 3.2.0 this will instrument both static and dynamic executables, while in previous versions of Darshan this was only sufficient for static executables. See the Cray installation recipe for more details.

For other general MPICH-based MPI implementations, you can generate Darshan-enabled variants of the standard mpicc/mpicxx/mpif90/mpif77 wrappers using the following commands:

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

The resulting *.darshan wrappers will transparently inject Darshan instrumentation into the link step without any explicit user intervention. They can be renamed and placed in an appropriate PATH to enable automatic instrumentation. This method also works correctly for both static and dynamic executables as of Darshan 3.2.0.

For other systems you can enable compile-time instrumentation by either manually adding the appropriate link options to your command line or modifying your default MPI compiler script. The darshan-config command line tool can be used to display the options that you should use:

# Linker options to use for dynamic linking (default on most platforms)
#   These arguments should go *before* the MPI libraries in the underlying
#   linker command line to ensure that Darshan can be activated.  It should
#   also ideally go before other libraries that may issue I/O function calls.
darshan-config --dyn-ld-flags

# linker options to use for static linking
#   The first set of arguments should go early in the link command line
#   (before MPI, while the second set should go at the end of the link command
#   line
darshan-config --pre-ld-flags
darshan-config --post-ld-flags

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 modifying the existing MPI compiler script. 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

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>

Note that unlike the previously described methods in this section, this method will not automatically adapt to static and dynamic linking options. The example profile configurations show above only support dynamic linking.

Example profile configurations are also provided with a "-static" suffix if you need examples for static linking.

5.2. Option 2: Instrumenting MPI applications at runtime

This method is applicable to pre-compiled dynamically linked executables as well as interpreted languages such as Python. You do not need to change your compile options in any way. This method works by injecting instrumentation at runtime. It will not work for statically linked executables.

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 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:

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 invocations of MPI programs, the following will set LD_PRELOAD for process duration only:

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.

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


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 library.

5.3. Option 3: Instrumenting non-MPI applications at runtime

Similar to the process described in the previous section, Darshan relies on the LD_PRELOAD mechanism for instrumenting dynamically-linked non-MPI applications. This allows Darshan to instrument dynamically-linked binaries produced by non-MPI compilers (e.g., gcc or clang), extending Darshan instrumentation to new contexts (like instrumentation of arbitrary Python programs or instrumenting serial file transfer utilities like cp and scp).

The only additional step required of Darshan non-MPI users is to also set the DARSHAN_ENABLE_NONMPI environment variable to signal to Darshan that non-MPI instrumentation is requested:


As described in the previous section, it may be desirable to users to limit the scope of Darshan’s instrumentation by only enabling LD_PRELOAD on the target executable:

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


Recall that Darshan instrumentation of non-MPI applications is only possible with dynamically-linked applications.

5.4. Using other profiling tools at the same time as Darshan

As of Darshan version 3.2.0, Darshan does not necessarily interfere with other profiling tools (particularly those using the PMPI profiling interface). Darshan itself does not use the PMPI interface, and instead uses dynamic linker symbol interception or --wrap function interception for static executables.

As a rule of thumb most profiling tools should appear in the linker command line before -ldarshan if possible.

6. Using the Darshan eXtended Tracing (DXT) module

Darshan’s DXT module provides full tracing of MPI-IO and POSIX read/write APIs. While the DXT module is able to capture finer-grained details compared to traditional Darshan instrumentation, it may exhibit higher runtime and memory overheads. For this reason, DXT support is disabled by default in Darshan, but users can opt-in to DXT instrumentation at runtime by setting their environment as follows:


DXT will trace each I/O operation to files instrumented by Darshan’s MPI-IO and POSIX modules, using a default memory limit of 2 MiB for each module (DXT_POSIX and DXT_MPIIO). Memory usage and a number of other aspects of DXT tracing can be configured as described in section Configuring Darshan library at runtime.

7. Using AutoPerf instrumentation modules

AutoPerf offers two additional Darshan instrumentation modules that may be enabled for MPI applications.

  • APMPI: Instrumentation of over 70 MPI-3 communication routines, providing operation counts, datatype sizes, and timing information for each application MPI rank.
  • APXC: Instrumentation of Cray XC environments to provide network and compute counters of interest, via PAPI.

Users can request Darshan to build the APMPI and APXC modules by passing --enable-apmpi-mod and --enable-apxc-mod options to configure, respectively. Note that these options can be requested independently (i.e., you can build Darshan with APMPI support but not APXC support, and vice versa).

The only prerequsisite for the APMPI module is that Darsan be configured with a MPI-3 compliant compiler. For APXC, the user must obviously be using a Cray XC system and must make the PAPI interface available to Darshan (i.e., by running module load papi, before building Darshan).

If using the APMPI module, users can additionally specify the --enable-apmpi-coll-sync configure option to force Darshan to synchronize before calling underlying MPI routines and to capture additional timing information on how synchronized processes are. Users should note this option will impose additional overheads, but can be useful to help diagnose whether applications are spending a lot of time synchronizing as part of collective communication calls. For this reason, we do not recommend users setting this particular option for production Darshan deployments.


The AutoPerf instrumentation modules are provided as Git submodules to Darshan’s main repository, so if building Darshan source that has been cloned from Git, it is necessary to first retrieve the AutoPerf submodules by running the following command:

git submodule update --init

8. Configuring Darshan library at runtime

To fine tune Darshan library settings (e.g., internal memory usage, instrumentation scope, etc.), Darshan provides a couple of mechanisms:

  • user environment variable overrides
  • a configuration file, which users must specify the path to using the DARSHAN_CONFIG_PATH environment variable

For settings that are specified via a config file and via an environment variable, the environment settings will take precedence.


Users of facility-provided Darshan installs should be mindful that these installs could define their own default Darshan config file. In this case, users should double check that DARSHAN_CONFIG_PATH environment variable is not already set, and if it is, users should consider copying the default config file as a starting point before applying their own settings.

8.1. Darshan library config settings

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

Table 1. Darshan library config settings

environment variable setting config file setting description
 Disables Darshan instrumentation.
 Enables Darshan's non-MPI mode, required for applications that do
 not call MPI_Init and MPI_Finalize.
 Specifies the path to a Darshan config file to load settings from.
 Prints the Darshan configuration to stderr at runtime.
 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.
 Enables internal instrumentation that will print the time required
to startup and shutdown Darshan to stderr at runtime.
 MODMEM <val>
 Specifies the amount of memory (in MiB) Darshan instrumentation
 modules can collectively consume (if not specified, a default 4 MiB
 quota is used). Overrides any `--with-mod-mem` configure argument.
 NAMEMEM <val>
 Specifies the amount of memory (in MiB) Darshan can consume for
 storing record names (if not specified, a default 1 MiB quota is
 used). Overrides any `--with-name-mem` configure argument.
 Specifies a value for system memory alignment. Overrides any
 `--with-mem-align` configure argument (default is 8 bytes).
 JOBID <string>
 Specifies the name of the environment variable to use for the job
 identifier, such as PBS_JOBID. Overrides `--with-jobid-env` configure
 LOGHINTS <string>
 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. Overrides any
 `--with-log-hints` configure argument.
 LOGPATH <path>
 Specifies the path to write Darshan log files to. Note that this
 directory needs to be formatted using the darshan-mk-log-dirs script.
 Overrides any `--with-log-path` configure argument.
 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`).
 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.
 MOD_DISABLE <mod_csv>
 Specifies a list of comma-separated Darshan module names to
 disable at runtime.
 MOD_ENABLE <mod_csv>
 Specifies a list of comma-separated Darshan module names to
 enable at runtime.
 APP_EXCLUDE <regex_csv>
 Specifies a list of comma-separated regexes that match
 application names that should not be instrumented. This is useful
 if Darshan is LD_PRELOADed, in which case logs may be generated
 for many unintended applications.
 APP_INCLUDE <regex_csv>
 Specifies a list of comma-separated regexes that match
 application names that should be instrumented. This setting is
 used to override any APP_INCLUDE rules.
 RANK_EXCLUDE <rank_csv>
 Specifies a list of comma-separated ranks (or rank ranges) that
 should not be instrumented. Rank ranges are formatted like
 "start:end" (if start or end are not specified, the first or last
 rank is assumed, respectively). Note that the Darshan library will
 still run on all processes of an application, this setting just
 controls whether specific ranks are capturing instrumentation data.
 RANK_INCLUDE <rank_csv>
 Specifies a list of comma-separated ranks (or rank ranges) that
 should be instrumented. This setting is used to override any
 Specifies a floating point percentage (i.e., ".8" would be 80%)
 indicating a threshold of small I/O operation accesses (defined
 as accesses smaller than 10 KiB), with DXT trace data being
 discarded for files that exhibit  a percentage of small I/O
 operations less than this threshold.
 Specifies a floating point percentage (i.e., ".8" would be 80%)
 indicating a threshold of unaligned I/O operation accesses (defined
 as accesses not aligned to the file alignment value determined
 by Darshan), with DXT trace data being discarded for files that
 exhibit a percentage of unaligned I/O operations less than this
 MAX_RECORDS <val> <mod_csv>
 Specifies the number of records to pre-allocate for each
 instrumentation module given in a comma-separated list.
 Most modules default to tracing 1024 file records per-process.
 NAME_EXCLUDE <regex_csv> <mod_csv>
 Specifies a list of comma-separated regexes that match
 record names that should not be instrumented for
 instrumentation modules given in a comma-separated module list.
 NAME_INCLUDE <regex_csv> <mod_csv>
 Specifies a list of comma-separated regexes that match
 record names that should be instrumented for instrumentation
 modules given in a comma-separated module list. This setting is
 used to override any NAME_EXCLUDE rules.
 (DEPRECATED) Setting this environment variable enables the DXT
 (Darshan eXtended Tracing) modules at runtime for all files
 instrumented by Darshan. Replaced by MODULE_ENABLE setting.
 (DEPRECATED) Specifies a list of comma-separated paths that
 Darshan will not instrument at runtime (in addition to Darshan's
 default exclusion list). Replaced by NAME_EXCLUDE setting.


  • Config file settings must be specified one per-line, with settings and their parameters separated by any whitespace.
  • Settings that take a comma-separated list of modules can use "*" as a wildcard to represent all modules.
  • Some config file settings (specifically, MOD_DISABLE/ENABLE, APP_EXCLUDE/INCLUDE, RANK_EXCLUDE/INCLUDE, NAME_EXCLUDE/INCLUDE, and MAX_RECORDS) may be repeated multiple times rather than providing comma-separated values, to ease readability.
  • Improperly formatted config settings are ignored, with Darshan falling back to its default configuration.
  • All settings that take regular expressions as input expect them to be formatted according to the POSIX regex.h interface — refer to the manpage for more details on regex syntax.

8.2. Example Darshan configuration

An example configuration file with annotations is given below (note that comments are allowed by prefixing a line with #):

# enable DXT modules, which are off by default

# allocate 4096 file records for POSIX and MPI-IO modules
# (darshan only allocates 1024 per-module by default)

# the '*' specifier can be used to apply settings for all modules
# in this case, we want all modules to ignore record names
# prefixed with "/home" (i.e., stored in our home directory),
# with a superseding inclusion for files with a ".out" suffix)
NAME_EXCLUDE    ^/home        *
NAME_INCLUDE    .out$         *

# bump up Darshan's default memory usage to 8 MiB

# avoid generating logs for git and ls binaries
APP_EXCLUDE     git,ls

# exclude instrumentation for all ranks first
# then selectively re-include ranks 0-3 and 12:15

# only retain DXT traces for files that were accessed
# using small I/O ops 20+% of the time

This configuration could be similarly set using environment variables, though note that both MAX_RECORDS and NAME_EXCLUDE/INCLUDE settings do not have environment variable counterparts:

export DARSHAN_APP_EXCLUDE="git,ls"
export DARSHAN_RANK_INCLUDE="0:3,12:15"

9. Darshan installation recipes

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

9.1. Cray platforms (XE, XC, or similar)

This section describes how to compile and install Darshan, as well as how to use a software module to enable and disable Darshan instrumentation on Cray systems.

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 compiler is 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 programming environment with a command similar to "module swap PrgEnv-intel PrgEnv-gnu". Please see your site documentation for information about how to switch programming environments.

The following example shows how to configure and build Darshan on a Cray system using the GNU programming environment. Adjust the --with-log-path and --prefix arguments to point to the desired log file path and installation path, respectively.

module swap PrgEnv-pgi PrgEnv-gnu
./configure \
 --with-log-path=/shared-file-system/darshan-logs \
 --prefix=/soft/darshan-3.3.0 \
 --with-jobid-env=SLURM_JOBID \
 --with-username-env=SLURM_JOB_USER \
make install
module swap PrgEnv-gnu PrgEnv-pgi


The job ID is set to SLURM_JOBID for use with a Slurm based scheduler. An additional environment variable for querying a job’s username (SLURM_JOB_USER) is provided as a fallback in case the default environment variable LOGNAME is not properly set (e.g., as is the case when using Slurm’s --export option to srun). The CC variable is configured to point the standard MPI compiler.

If instrumentation of the HDF5 library is desired, additionally load an acceptable HDF5 module (e.g., module load cray-hdf5-parallel) prior to building and use the the --enable-hdf5-mod configure argument. We additionally recommend that you modify Darshan’s generated Cray software module to include a dependency on the HDF5 software module used — this is necessary to ensure Darshan library dependencies are satisfied at application link and run time.

prereq cray-hdf5-parallel

Note that the Darshan-enabled Cray compiler wrappers will always prefer user-supplied HDF5 libraries over the library used to build Darshan. However, due to ABI changes in the HDF5 library, the two HDF5 libraries used must be compatible. Specifically, the HDF5 library versions need to be either both greater than or equal to 1.10 or both less than 1.10. If users use an HDF5 version that is incompatible with Darshan, either link or runtime errors will occur and the user will have to switch HDF5 versions or unload the Darshan module.

Optional RDTSCP timers for Theta

Darshan’s default mechanism (clock_gettime()) for retrieving timing information may introduce more overhead than expected for statically linked executables on some platforms. The Theta system at the ALCF (as of July 2021) is a notable example. It uses static linking by default (which prevents the use of the standard vDSO optimization for clock_gettime() calls), and it’s CPU architecture exhibits relatively high system call overhead. For Theta and other similar platforms you can explicitly request that Darshan use the RDTSCP instruction in place of clock_gettime() for timing purposes. RDTSCP is a non-portable, Intel-specific instruction. It must be enabled explicitly at configure time, and the base clock frequency of the compute node CPU must be specified.

This mechanism can be activated on Theta by adding the --enable-rdtscp=1300000000 to the configure command line (the KNL CPUs on Theta have a base frequency of 1.3 GHz).

Note that timer overhead is unlikely to be a factor in overall performance unless the application has an edge case workload with frequent sequential I/O operations, such as small I/O accesses to cached data on a single process.

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.

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

Darshan will automatically install example software module files in the following locations (depending on how you specified the --prefix option in the previous section):


Select the one that is appropriate for your Cray programming environment (see the version number of the craype module in module list).

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 Darshan.

The modulefile that you select can be copied to a system location, or the install location can be added to your local module path with the following command:

module use /soft/darshan-3.3.0/share/craype-<VERSION>/modulefiles

From this point, Darshan instrumentation can be enabled for all future application compilations by running "module load darshan".

9.2. Linux clusters using MPICH

Most MPICH installations produce dynamic executables by default. To configure Darshan in this environment you can use the following example. We recommend using mpicc with GNU compilers to compile Darshan.

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

The darshan-gen-* scripts described earlier in this document can be used to create variants of the standard mpicc/mpicxx/mpif77/mpif90 scripts that are Darshan enabled. These scripts will work correctly for both dynamic and statically linked executables.

9.3. 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-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 enable Darshan instrumentation at compile time by adding darshan-config --dyn-ld-flags options to your linker command line.

Alternatively you can use LD_PRELOAD runtime instrumentation method to instrument executables that have already been compiled.

9.4. 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.

You can enable Darshan instrumentation at compile time by adding darshan-config --dyn-ld-flags options to your linker command line.

Alternatively you can use LD_PRELOAD runtime instrumentation method to instrument executables that have already been compiled.

10. Debugging

10.1. No log file

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

  • Make sure you are looking in the correct place for logs. Confirm the location with the darshan-config --log-path command.
  • 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

For dynamically linked executables:

  • Ensure that the Darshan library is present in the list of shared libraries to be used by the application, and that it appears before the MPI library:
> ldd mpi-io-test
        linux-vdso.so.1 (0x00007ffd83925000)
        libdarshan.so => /home/carns/working/install/lib/libdarshan.so (0x00007f0f4a7a6000)
        libmpi.so.12 => /home/carns/working/src/spack/opt/spack/linux-ubuntu19.10-skylake/gcc-9.2.1/mpich-3.3.2-h3dybprufq7i5kt4hcyfoyihnrnbaogk/lib/libmpi.so.12 (0x00007f0f4a44f000)
        libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f0f4a241000)


  • 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