Estimating the accuracy of user surveys for assessing the impact of HPC systems

AMS Citation:
Hart, D., M. Rishel, and D. Nychka, 2016: Estimating the accuracy of user surveys for assessing the impact of HPC systems. Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale, 18, doi:10.1145/2949550.2949640.
Date:2016-08-01
Resource Type:article
Title:Estimating the accuracy of user surveys for assessing the impact of HPC systems
Abstract: Each year, the Computational & Information Systems Laboratory (CISL) conducts a survey of its current and recent user community to gather a number of metrics about the scientific impact and outcomes from the use of CISL’s high-performance computing systems, particularly peer-reviewed publications. However, with a modest response rate and reliance on selfreporting by users, the accuracy of the survey is uncertain as is the degree of that uncertainty. To quantify this uncertainty, CISL undertook a project that attempted to provide statistically supported limits on the accuracy and precision of the survey approach. We discovered limitations related to the range of users' HPC usage in our modeling phase, and several methods were attempted to adjust the model to fit the usage data. The resulting statistical models leverage data about the HPC usage associated with survey invitees to quantify the degree to which the survey undercounts the relevant publications. A qualitative assessment of the collected publications aligns with the statistical models, reiterates the challenges associated with acknowledgment for use of HPC resources, and suggests ways to improve the survey results further.
Peer Review:Non-refereed
Copyright Information:Copyright 2016 Association for Computing Machinery.
OpenSky citable URL: ark:/85065/d7r2133m
Publisher's Version: 10.1145/2949550.2949640
Author(s):
  • David Hart - NCAR/UCAR
  • Melissa Rishel
  • Doug Nychka - NCAR/UCAR
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