Abstract
Operating chips at high energy efficiency is one of the major challenges for modern large-scale supercomputers. Low-voltage operation of transistors increases the energy efficiency but leads to frequency and power variation across cores on the same chip. Finding energy-optimal configurations for such chips is a hard problem. In this work, we study how integer linear programming techniques can be used to obtain energy-efficient configurations of chips that have heterogeneous cores. Our proposed methodologies give optimal configurations as compared with competent but sub-optimal heuristics while having negligible timing overhead. The proposed ParSearch method gives up to 13.2% and 7% savings in energy while causing only 2% increase in execution time of two HPC applications: miniMD and Jacobi, respectively. Our results show that integer linear programming can be a very powerful online method to obtain energy-optimal configurations.
Original language | English (US) |
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Pages (from-to) | 451-466 |
Number of pages | 16 |
Journal | International Journal of High Performance Computing Applications |
Volume | 31 |
Issue number | 5 |
DOIs | |
State | Published - Sep 1 2017 |
Keywords
- energy
- heterogeneity
- integer programming
- low-voltage computing
- multicore chips
- near-threshold voltage computing
- optimization
- power
- process variation
- quadratic integer programming
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Hardware and Architecture