Abstract
As we approach exascale systems, power is turning from an optimization goal to a critical operating constraint. With power bounds imposed by both stakeholders and the limitations of existing infrastructure, we need to develop new techniques that work with limited power to extract maximum performance. In this paper, we explore this area and provide an approach to find the theoretical upper bound of computational performance on a per-application basis in hybrid MPI + OpenMP applications. We use a linear programming (LP) formulation to optimize application schedules under various power constraints, where a schedule consists of a DVFS state and number of OpenMP threads for each section of computation between consecutive MPI calls. We also provide a more flexible mixed integer-linear (ILP) formulation and show that the resulting schedules closely match schedules from the LP formulation. Across four applications, we use our LP-derived upper bounds to show that current approaches trail optimal, power-constrained performance by up to 41.1%. This demonstrates the untapped potential of current systems, and our LP formulation provides future optimization approaches with a quantitative optimization target.
| Original language | English (US) |
|---|---|
| Title of host publication | International Conference for High Performance Computing, Networking, Storage and Analysis, SC |
| Publisher | IEEE Computer Society |
| Volume | 15-20-November-2015 |
| ISBN (Print) | 9781450337236 |
| DOIs | |
| State | Published - Nov 15 2015 |
| Event | International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2015 - Austin, United States Duration: Nov 15 2015 → Nov 20 2015 |
Other
| Other | International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2015 |
|---|---|
| Country | United States |
| City | Austin |
| Period | 11/15/15 → 11/20/15 |
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ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Software
Cite this
Finding the limits of power-constrained application performance. / Bailey, Peter E.; Marathe, Aniruddha; Lowenthal, David K; Rountree, Barry; Schulz, Martin.
International Conference for High Performance Computing, Networking, Storage and Analysis, SC. Vol. 15-20-November-2015 IEEE Computer Society, 2015. a79.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Finding the limits of power-constrained application performance
AU - Bailey, Peter E.
AU - Marathe, Aniruddha
AU - Lowenthal, David K
AU - Rountree, Barry
AU - Schulz, Martin
PY - 2015/11/15
Y1 - 2015/11/15
N2 - As we approach exascale systems, power is turning from an optimization goal to a critical operating constraint. With power bounds imposed by both stakeholders and the limitations of existing infrastructure, we need to develop new techniques that work with limited power to extract maximum performance. In this paper, we explore this area and provide an approach to find the theoretical upper bound of computational performance on a per-application basis in hybrid MPI + OpenMP applications. We use a linear programming (LP) formulation to optimize application schedules under various power constraints, where a schedule consists of a DVFS state and number of OpenMP threads for each section of computation between consecutive MPI calls. We also provide a more flexible mixed integer-linear (ILP) formulation and show that the resulting schedules closely match schedules from the LP formulation. Across four applications, we use our LP-derived upper bounds to show that current approaches trail optimal, power-constrained performance by up to 41.1%. This demonstrates the untapped potential of current systems, and our LP formulation provides future optimization approaches with a quantitative optimization target.
AB - As we approach exascale systems, power is turning from an optimization goal to a critical operating constraint. With power bounds imposed by both stakeholders and the limitations of existing infrastructure, we need to develop new techniques that work with limited power to extract maximum performance. In this paper, we explore this area and provide an approach to find the theoretical upper bound of computational performance on a per-application basis in hybrid MPI + OpenMP applications. We use a linear programming (LP) formulation to optimize application schedules under various power constraints, where a schedule consists of a DVFS state and number of OpenMP threads for each section of computation between consecutive MPI calls. We also provide a more flexible mixed integer-linear (ILP) formulation and show that the resulting schedules closely match schedules from the LP formulation. Across four applications, we use our LP-derived upper bounds to show that current approaches trail optimal, power-constrained performance by up to 41.1%. This demonstrates the untapped potential of current systems, and our LP formulation provides future optimization approaches with a quantitative optimization target.
UR - http://www.scopus.com/inward/record.url?scp=84966549024&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84966549024&partnerID=8YFLogxK
U2 - 10.1145/2807591.2807637
DO - 10.1145/2807591.2807637
M3 - Conference contribution
AN - SCOPUS:84966549024
SN - 9781450337236
VL - 15-20-November-2015
BT - International Conference for High Performance Computing, Networking, Storage and Analysis, SC
PB - IEEE Computer Society
ER -