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NASA NTRS · 20150005751

Coarrars for Parallel Processing

Snyder, W. Van
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Abstract

The design of the Coarray feature of Fortran 2008 was guided by answering the question "What is the smallest change required to convert Fortran to a robust and efficient parallel language." Two fundamental issues that any parallel programming model must address are work distribution and data distribution. In order to coordinate work distribution and data distribution, methods for communication and synchronization must be provided. Although originally designed for Fortran, the Coarray paradigm has stimulated development in other languages. X10, Chapel, UPC, Titanium, and class libraries being developed for C++ have the same conceptual framework.

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Snyder, W. Van. 2011-07-04. Coarrars for Parallel Processing. https://ntrs.nasa.gov/citations/20150005751

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NASA NTRS2017

Position Paper - pFLogger: The Parallel Fortran Logging framework for HPC Applications

In the context of high performance computing (HPC), software investments in support of text-based diagnostics, which monitor a running application, are typically limited compared to those for other types of IO. Examples of such diagnostics include reiteration of configuration parameters, progress indicators, simple metrics (e.g., mass conservation, convergence of solvers, etc.), and timers. To some degree, this difference in priority is justifiable as other forms of output are the primary products of a scientific model and, due to their large data volume, much more likely to be a significant performance concern. In contrast, text-based diagnostic content is generally not shared beyond the individual or group running an application and is most often used to troubleshoot when something goes wrong. We suggest that a more systematic approach enabled by a logging facility (or logger) similar to those routinely used by many communities would provide significant value to complex scientific applications. In the context of high-performance computing, an appropriate logger would provide specialized support for distributed and shared-memory parallelism and have low performance overhead. In this paper, we present our prototype implementation of pFlogger a parallel Fortran-based logging framework, and assess its suitability for use in a complex scientific application.

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