Results of 2013 Survey of Parallel Computing Needs Focusing on NSF-funded Researchers

Abstract

The field of supercomputing is experiencing a rapid change in system structure, programming models, and software environments in response to advances in application requirements and in underlying enabling technologies. Traditional parallel programming approaches have relied on static resource allocation and task scheduling through programming interfaces such as MPI and OpenMP. These methods are reaching their efficiency and scalability limits on the new emerging classes of systems, spurring the creation of innovative dynamic strategies and software tools, including advanced runtime system software and programming interfaces that use them. To accelerate adoption of these next-generation methods, Indiana University is investigating the creation of a single supported Reconfigurable Execution Framework Testbed (REFT) to be used by parallel application algorithm developers as well as researchers in advanced tools for parallel computing. These investigations are funded by the National Science Foundation Award Number 1205518 to Indiana University with Thomas Sterling as Principal Investigator, and Maciej Brodowicz, Matthew R. Link, Andrew Lumsdaine, and Craig Stewart as Co-Principal Investigators. As a starting point in this research we proposed to assess needs in parallel computing in general and needs for software tools and testbeds in particular within the NSF-funded research community. As one set of data toward understanding these needs, we conducted a survey of researchers funded by the National Science Foundation. Because of the strong possibility of distinct needs of researchers funded by what is now the Division of Advanced Cyberinfrastructure, researchers funded by the other divisions of the Computer and Information Sciences and Engineering Directorate, and researchers funded by the remainder of the NSF, we surveyed these populations separately. The report states the methods and summarize survey results. The data sets and copies of SPSS descriptive statistics describing the data are available online at http://hdl.handle.net/2022/19924.