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Title: Position Paper: Applying Machine Learning to Software Analysis to Achieve Trusted, Repeatable Scientific Computing

Producing trusted results from high-performance codes is essential for policy and has significant economic impact. We propose combining rigorous analytical methods with machine learning techniques to achieve the goal of repeatable, trustworthy scientific computing.
Authors:
 [1] ;  [1]
  1. ORNL
Publication Date:
OSTI Identifier:
1265800
DOE Contract Number:
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: ASCR Cybersecurity Workshop 2, Arlington, VA, USA, 20150602, 20150603
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English