#OCTAVE PARALLEL INSTALL#
#OCTAVE PARALLEL SERIAL#
#OCTAVE PARALLEL LICENSE#

That fun is able to operate on vectors rather than just scalars, and returnsĪ vector.

This option must be given together with 'ChunksPerProc' and it indicates If cells occur as arguments, they are treatedĪrrayfun supports one extra option compared to parcellfun: 'Vectorized'. (Quebec, QC, Canada).Function File: = pararrayfun ( nproc, fun, a1, a2, …) Function File: pararrayfun (nproc, fun, …, 'UniformOutput', val) Function File: pararrayfun (nproc, fun, …, 'ErrorHandler', errfunc)Įvaluates a function for corresponding elements of an array.Īrgument and options handling is analogical to parcellfun, except thatĪrguments are arrays rather than cells. “A neuroimaging analysis kit for Matlab and Octave,” in Proceedings of the 17th International Conference on Functional Mapping of the Human Brain. M., Perlbarg V., Lepage C., Lyttelton O., Fonov V., Janke A., Tohka J., Evans A. (New York, NY: ACM).īellec P., Carbonell F. Technical Report,” in Proceedings of the 1977 symposium on Artificial intelligence and programming languages archive. “The Incremental Garbage Collection of Processes. Master's thesis, The University of Chicago.Īshburner J. Integrating Task Parallelism into the Python Programming Language. “The CIVET image-processing environment: a fully automated comprehensive pipeline for anatomical neuroimaging research,” in Proceedings of the 12th Annual Meeting of the Human Brain Mapping Organization. D., Lepage C., Lerch J., Fombonne E., Evans A. Finally, the parallelization efficiency (i.e., the ratio between the empirical speed-up and the ideal speed-up) is presented in panel (H).Īd-Dab'bagh Y., Einarson D., Lyttelton O., Muehlboeck J.

#OCTAVE PARALLEL SERIAL#

The speed-up factor, i.e., serial time divided by parallel time, is presented in panel (G), along with the ideal speed-up, equal to the user-specified maximal number of concurrent jobs. The parallel execution time, i.e., the time elapsed between the beginning and the end of the pipeline processing, is shown in panel (F). The serial execution time of the pipeline, i.e., the sum of execution times for all jobs, is shown in panel (E). The user-specified maximum number of concurrent jobs is indicated by a straight line. The number of jobs running at any given time across the whole execution of the pipeline (averaged on 5 min time windows) is shown in panels (B–D) for servers peuplier, magma and guillimin, respectively. The distribution of execution time for all jobs on one server ( peuplier) is shown in panel (A). Matlab Octave high-performance computing neuroimaging open-source parallel computing pipeline workflow.īenchmark experiments with the NIAK fMRI preprocessing pipeline. The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources. We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI).

#OCTAVE PARALLEL INSTALL#

The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac).

#OCTAVE PARALLEL LICENSE#

PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files.

PSOM does not introduce new language constructs to specify the steps and structure of the workflow. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline.

Octave parallel