Simulation Interfaces

The invocation of a simulation code is performed using either system calls or forks or via direct linkage. In the system call and fork cases, a separate process is created for the simulation and communication between Dakota and the simulation occurs through parameter and response files. For system call and fork interfaces, the interface section must specify the details of this data transfer. In the direct case, a separate process is not created and communication occurs in memory through a prescribed API.

The following sub-sections provide information on the simulation interfacing approaches:

Fork Simulation Interface

The fork simulation interface is the most common method for interfacing Dakota with an external simulation model.

The fork simulation interface uses the fork, exec, and wait families of functions to manage simulation codes or simulation drivers. Calls to fork or vfork create a copy of the Dakota process, execvp replaces this copy with the simulation code or driver process, and then Dakota uses the wait or waitpid functions to wait for completion of the new process.


In a native Windows version of Dakota, similar Win32 functions, such as _spawnvp(), are used instead.


Transfer of variables and response data between Dakota and the simulator code or driver occurs through the file system in exactly the same manner as for the system call interface.

An example of a fork interface specification follows:

        input_filter    = 'test_3pc_if'
        output_filter   = 'test_3pc_of'
        analysis_driver = 'test_3pc_ac'
        parameters_file = ''
        results_file    = 'tb.out'

Further Reading

Direct Simulation Interface

The direct interface may be used to invoke simulations that are linked into the Dakota executable. This interface eliminates overhead from process creation and file I/O and can simplify operations on massively parallel computers. These advantages are balanced with the practicality of converting an existing simulation code into a library with a subroutine interface. Sandia codes for structural dynamics (Salinas), computational fluid dynamics (Sage), and circuit simulation (Xyce) and external codes such as Phoenix Integration’s ModelCenter framework and The Mathworks’ Matlab have been linked in this way, and a direct interface to Sandia’s SIERRA multiphysics framework is under development. In the latter case, the additional effort is particularly justified since SIERRA unifies an entire suite of physics codes.


The “sandwich implementation” of combining a direct interface plug-in with Dakota’s library mode is discussed here.

In addition to direct linking with simulation codes, the direct interface also provides access to internal polynomial test functions that are used for algorithm performance and regression testing. The following test functions are available: cantilever, cyl_head, log_ratio, rosenbrock, short_column, and text_book (including text_book1, text_book2, text_book3, and text_book_ouu).

While these functions are also available as external programs in the dakota/share/dakota/test directory, maintaining internally linked versions allows more rapid testing. See the Additional Examples page for additional information on several of these test problems.

An example input specification for a direct interface follows:

        analysis_driver = 'rosenbrock'

Further Reading

System Call Simulation Interface


Users are strongly encouraged to use the fork simulation interface if possible, though the system interface is still supported for portability and backward compatibility.

The system call approach invokes a simulation code or simulation driver by using the system function from the standard C library [KR88].

In this approach, the system call creates a new process that communicates with Dakota through parameter and response files. The system call approach allows the simulation to be initiated via its standard invocation procedure (as a “black box”) and then coordinated with a variety of tools for pre- and post-processing. This approach has been widely used in previous studies [Eld98, EHB+96, EOB+96]. The system call approach involves more process creation and file I/O overhead than the direct function approach, but this extra overhead is usually insignificant compared with the cost of a simulation. An example of a system call interface specification follows:

        analysis_driver = 'text_book'
        parameters_file = ''
        results_file    = 'text_book.out'

Information on asynchronous usage of the system interface is provided in the :ref`section on system call synchronization <parallel:SLP:local:system>`.

Syntax for Filter and Driver Strings

Dakota’s default behavior is to construct input filter, analysis driver, and output filter commands by appending the names of the parameters file and results file for the evaluation/analysis to the user-provided input_filter, output_filter, and analysis_drivers strings. After adding its working directory to the PATH, Dakota executes these commands in its working directory or, if the work_directory keyword group is present, in a work directory.

Filter and driver strings may contain absolute or relative path information and whitespace; Dakota will pass them through without modification.

Quotes are also permitted with the restriction that if double-quotes (“) are used to enclose the driver or filter string as a whole, then only single quotes (’) are allowed within it, and vice versa. The input filter string ’dprepro –var "foo=1"’ works, as does "dprepro –var ’foo=1’", but not "dprepro –var "foo=1"".

In some situations, users may not wish Dakota to append the names of the parameters or results files to filter and driver strings. The verbatim keyword prevents this behavior, and causes Dakota to execute filter and driver strings “as is”.

Beginning with version 6.10, Dakota will substitute the tokens {PARAMETERS} and {RESULTS} in driver and filter strings with the names of the parameters and results files for that analysis/evaluation just prior to execution.

For example, if an interface block in the input file included:

input_filter 'preprocess {PARAMETERS}'
analysis_drivers ''
output_filter 'postprocess {RESULTS}'

Then, the input filter preprocess would be run with only the parameters file as a command line argument, the analysis driver would receive no command line arguments, and the output filter postprocess would receive only the results file name.

The combination of verbatim and substitution provide users with considerable flexibility in specifying the form of filter and driver commands.

Fork or System Call: Which to Use?

The primary operational difference between the fork and system call simulation interfaces is that, in the fork interface, the fork/exec functions return a process identifier that the wait/waitpid functions can use to detect the completion of a simulation for either synchronous or asynchronous operations. The system call simulation interface, on the other hand, must use a response file detection scheme for this purpose in the asynchronous case. Thus, an important advantage of the fork interface over the system call interface is that it avoids the potential of a file race condition when employing asynchronous local parallelism (refer to Asynchronous Local Parallelism). This condition can occur when the responses file has been created but the writing of the response data set to this file has not been completed (see System Call Synchronization). While significant care has been taken to manage this file race condition in the system call case, the fork interface still has the potential to be more robust when performing function evaluations asynchronously.

Another advantage of the fork interface is that it has additional asynchronous capabilities when a function evaluation involves multiple analyses. As shown in Table 17, the fork interface supports asynchronous local and hybrid parallelism modes for managing concurrent analyses within function evaluations, whereas the system call interface does not. These additional capabilities again stem from the ability to track child processes by their process identifiers.

The only disadvantage to the fork interface compared with the system interface is that the fork/exec/wait functions are not part of the standard C library, whereas the system function is. As a result, support for implementations of the fork/exec/wait functions can vary from platform to platform. At one time, these commands were not available on some of Sandia’s massively parallel computers. However, in the more mainstream UNIX environments, availability of fork/exec/wait should not be an issue.

In summary, the system call interface has been a workhorse for many years and is well tested and proven, but the fork interface supports additional capabilities and is recommended when managing asynchronous simulation code executions. Having both interfaces available has proven to be useful on a number of occasions and they will both continue to be supported for the foreseeable future.