Time-energy Measurements of Shared-memory Applications on Modern Multicore Systems
This repository provides the time-energy data collected and analyzed in our research paper entitled "The Time and Energy Efficiency of Modern Multicore Systems" (PARCO 2019). Please read our Data-in-Brief article for a detailed description of the data.
How to Use
To generate model data in
data/model folder, go to scripts folder and run:
$ ./run-homogeneous.sh $ ./run-heterogeneous.sh
Python 3 to run these scripts.
The model's equations are implemented in model.py.
The script model_homogeneous.py uses the equations corresponding to homogeneous multicore systems implemented in model.py. It takes as paramters the number of cores, the active power fraction of the system (APF), the idle power of the system (in Watts), application name (for display) and the measured data for the given application on the given homogeneous system.
Usage: model_homogeneous.py n apf psys app measurements_file n - total number of cores apf - APF psys - system power [W] app - application name measurements_file - time-energy measuremnets on all cores
The script model_heterogeneous.py uses the equations corresponding to heterogeneous multicore systems implemented in model.py. It takes as paramters the total number of cores, the number of little and big cores, the active power fraction (APF) of little and big cores, the idle power of the system (in Watts), application name (for display) and the measured data for the given application on little cores, big cores, all cores using static scheduling and all cores using dynamic scheduling.
Usage: model_heterogeneous.py n nl nb apf_l apf_b app file_l file_b file_static file_dynamic [-l2b] n - total number of cores nl - number of little cores nb - number of big cores apf_l - APF of little core apf_b - APF of big core p_sys - system (idle) power app - application name file_l - performance measuremnets on little cores only file_b - performance measuremnets on big cores only file_static - performance measuremnets on all cores using static OpenMP scheduling file_dynamic - performance measuremnets on all cores using dynamic OpenMP scheduling
List of Publications
 D. Loghin and Y.M. Teo, "The Energy Efficiency of Modern Multicore Systems", in Proc. of the 47th International Conference on Parallel Processing Companion https://doi.org/10.1145/3229710.3229714
 D. Loghin and Y.M. Teo, "The Time and Energy Efficiency of Modern Multicore Systems", in "PARCO" https://doi.org/10.1016/j.parco.2019.04.009
 D. Loghin and Y.M. Teo, "Time-energy Measured Data on Modern Multicore Systems Running Shared-memory Applications", in "Data in Brief" https://doi.org/10.1016/j.dib.2019.104670).
This repository is licensed under Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/)
If you are using these data in your research, please cite one of our papers.