Abstract
With the increasing complexity of upcoming HPC systems, so-called “co-design” efforts to develop the hardware and applications in concert for these systems also become more challenging. It is currently difficult to gather information about the usage of programming model features, libraries, and data structure considerations in a quantitative way across a variety of applications, and this information is needed to prioritize development efforts in systems software and hardware optimizations. In this paper we propose CAASCADE, a system that can harvest this information in an automatic way in production HPC environments, and we show some early results from a prototype of the system based on GNU compilers and a MySQL database.
Original language | English |
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Title of host publication | Programming and Performance Visualization Tools - International Workshops, ESPT 2017 and VPA 2017, Revised Selected Papers |
Editors | Abhinav Bhatele, David Boehme, Joshua A. Levine, Allen D. Malony, Martin Schulz |
Publisher | Springer Verlag |
Pages | 90-104 |
Number of pages | 15 |
ISBN (Print) | 9783030178710 |
DOIs | |
State | Published - 2019 |
Event | 6th Workshop on Extreme-Scale Programming Tools, ESPT 2017 and 4th International Workshop on Visual Performance Analysis, VPA 2017 and Workshop on Extreme-Scale Programming Tools, ESPT 2018 and 5th International Workshop on Visual Performance Analysis, VPA 2018 - Dallas, United States Duration: Nov 11 2018 → Nov 16 2018 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11027 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 6th Workshop on Extreme-Scale Programming Tools, ESPT 2017 and 4th International Workshop on Visual Performance Analysis, VPA 2017 and Workshop on Extreme-Scale Programming Tools, ESPT 2018 and 5th International Workshop on Visual Performance Analysis, VPA 2018 |
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Country/Territory | United States |
City | Dallas |
Period | 11/11/18 → 11/16/18 |
Funding
Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U. S. Department of Energy. The project was sponsored via the LDRD project 8277: “Understanding HPC Applications for Evidence-based Co-design”. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Acknowledgements. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, under contract number DE-AC05-00OR22725.