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Title: Create full-scale predictive economic models on ROI and innovation with performance computing

Abstract

The U.S. Department of Energy (DOE), the world's largest buyer and user of supercomputers, awarded IDC Research, Inc. a grant to create two macroeconomic models capable of quantifying, respectively, financial and non-financial (innovation) returns on investments in HPC resources. Following a 2013 pilot study in which we created the models and tested them on about 200 real-world HPC cases, DOE authorized us to conduct a full-out, three-year grant study to collect and measure many more examples, a process that would also subject the methodology to further testing and validation. A secondary, "stretch" goal of the full-out study was to advance the methodology from association toward (but not all the way to) causation, by eliminating the effects of some of the other factors that might be contributing, along with HPC investments, to the returns produced in the investigated projects.

Authors:
 [1];  [1]
  1. IDC Research, Inc., Framingham, MA (United States)
Publication Date:
Research Org.:
IDC Research, Inc., Framingham, MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1405141
Report Number(s):
14SC503191
1143742
DOE Contract Number:  
SC0012576
Resource Type:
Technical Report
Resource Relation:
Related Information: http://www.hpcuserforum.com/ROI/
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; HPC; HPC Retun on Investments (ROI); HPC INNOVATATIONS

Citation Formats

Joseph, Earl C., and Conway, Steve. Create full-scale predictive economic models on ROI and innovation with performance computing. United States: N. p., 2017. Web. doi:10.2172/1405141.
Joseph, Earl C., & Conway, Steve. Create full-scale predictive economic models on ROI and innovation with performance computing. United States. doi:10.2172/1405141.
Joseph, Earl C., and Conway, Steve. Fri . "Create full-scale predictive economic models on ROI and innovation with performance computing". United States. doi:10.2172/1405141. https://www.osti.gov/servlets/purl/1405141.
@article{osti_1405141,
title = {Create full-scale predictive economic models on ROI and innovation with performance computing},
author = {Joseph, Earl C. and Conway, Steve},
abstractNote = {The U.S. Department of Energy (DOE), the world's largest buyer and user of supercomputers, awarded IDC Research, Inc. a grant to create two macroeconomic models capable of quantifying, respectively, financial and non-financial (innovation) returns on investments in HPC resources. Following a 2013 pilot study in which we created the models and tested them on about 200 real-world HPC cases, DOE authorized us to conduct a full-out, three-year grant study to collect and measure many more examples, a process that would also subject the methodology to further testing and validation. A secondary, "stretch" goal of the full-out study was to advance the methodology from association toward (but not all the way to) causation, by eliminating the effects of some of the other factors that might be contributing, along with HPC investments, to the returns produced in the investigated projects.},
doi = {10.2172/1405141},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {10}
}