Pynamic: the Python Dynamic Benchmark

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Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, we ... continued below

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Lee, G L; Ahn, D H; de Supinksi, B R; Gyllenhaal, J C & Miller, P J July 10, 2007.

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Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, we present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.

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PDF-file: 8 pages; size: 0.1 Mbytes

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  • Presented at: 2007 IEEE International Symposium on Workload Characterization, Boston, MA, United States, Sep 27 - Sep 29, 2007

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  • Report No.: UCRL-CONF-232621
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 923611
  • Archival Resource Key: ark:/67531/metadc902901

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • July 10, 2007

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  • Sept. 27, 2016, 1:39 a.m.

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  • Dec. 6, 2016, 4:55 p.m.

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Lee, G L; Ahn, D H; de Supinksi, B R; Gyllenhaal, J C & Miller, P J. Pynamic: the Python Dynamic Benchmark, article, July 10, 2007; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc902901/: accessed December 13, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.