Prometheus: Coherent Exploration of Hardware and Software Optimizations using Aspen
Abstract
With the dramatic increase in scale expected for Exascale computing, there is a dire need for tuning of hardware configurations and software optimizations such that they are in unison. However, the expected increase in tunable hardware parameters makes searching through the design space for optimal hardware-and-software configurations much more challenging. Towards this end, we propose a composable hardware-software optimization framework called Prometheus. Prometheus uses a combination of analytical and machine-learning techniques to capture application characteristics and subsequently determine the hardware-software configuration for near-optimal performance. We evaluate Prometheus for its efficacy using four widely used proxy applications: LULESH, CoMD, CG and CoEVP. We demonstrate that Prometheus identifies near-optimal hardwaresoftware configurations and verify the results via brute-force search of the design space.
- Authors:
-
- Virginia Tech, Blacksburg, VA
- ORNL
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1476412
- DOE Contract Number:
- AC05-00OR22725
- Resource Type:
- Conference
- Resource Relation:
- Conference: 26th IEEE International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems - Milwaukee, Wisconsin, United States of America - 9/25/2018 8:00:00 AM-9/28/2018 8:00:00 AM
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Umar, Mariam, Moore, Shirley V., Vetter, Jeffrey, and Cameron, Kirk W. Prometheus: Coherent Exploration of Hardware and Software Optimizations using Aspen. United States: N. p., 2018.
Web. doi:10.1109/MASCOTS.2018.00032.
Umar, Mariam, Moore, Shirley V., Vetter, Jeffrey, & Cameron, Kirk W. Prometheus: Coherent Exploration of Hardware and Software Optimizations using Aspen. United States. https://doi.org/10.1109/MASCOTS.2018.00032
Umar, Mariam, Moore, Shirley V., Vetter, Jeffrey, and Cameron, Kirk W. 2018.
"Prometheus: Coherent Exploration of Hardware and Software Optimizations using Aspen". United States. https://doi.org/10.1109/MASCOTS.2018.00032. https://www.osti.gov/servlets/purl/1476412.
@article{osti_1476412,
title = {Prometheus: Coherent Exploration of Hardware and Software Optimizations using Aspen},
author = {Umar, Mariam and Moore, Shirley V. and Vetter, Jeffrey and Cameron, Kirk W.},
abstractNote = {With the dramatic increase in scale expected for Exascale computing, there is a dire need for tuning of hardware configurations and software optimizations such that they are in unison. However, the expected increase in tunable hardware parameters makes searching through the design space for optimal hardware-and-software configurations much more challenging. Towards this end, we propose a composable hardware-software optimization framework called Prometheus. Prometheus uses a combination of analytical and machine-learning techniques to capture application characteristics and subsequently determine the hardware-software configuration for near-optimal performance. We evaluate Prometheus for its efficacy using four widely used proxy applications: LULESH, CoMD, CG and CoEVP. We demonstrate that Prometheus identifies near-optimal hardwaresoftware configurations and verify the results via brute-force search of the design space.},
doi = {10.1109/MASCOTS.2018.00032},
url = {https://www.osti.gov/biblio/1476412},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Sep 01 00:00:00 EDT 2018},
month = {Sat Sep 01 00:00:00 EDT 2018}
}