CrossPerformancePowerPrediction

Published: 26 April 2021| Version 1 | DOI: 10.17632/dg2rt3vfty.1
Contributor:
Amit Mankodi

Description

We have collected performance and power datasets for 6 benchmark applications; mser, tracking, svm and stitch from SD-VBS benchmark and sha and dijkstra from MiBench benchmark from simulation systems built-in Gem5 simulator with emulation mode as well as from physical systems. Simulation Systems Performance and Power Dataset: We have built 475 simulation systems in the Gem5 simulator using emulation mode by collecting nine hardware features cpu clock speed, instriction-set-architecture (ISA), cores, L1 cache size, L2 cache size, L3 cache size, memory type, memory access speed and memory size from real systems available in the market today. We have executed each of the 6 benchmark applications on each of the 475 simulation systems to collect actual runtime along with hardware features. We have utilized the McPAT to collect power consumption for each application execution on Gem5 simulation systems. The hardware features, performance (Runtime) and Power is available in files /benchmark_algo/%application%/%application%_power.csv e.g. for mser it is available at benchmark_algo/mser/mser_power.csv, etc. Physical Systems Performance and Power Dataset: We have selected 4 physical systems for our cross performance power prediction experiments. We first have collected hardware feature values from each of the four systems using the dmidecode utility. We have modified each of the 6 benchmark applications' source code to integrate PAPI-API to collect power consumption. PAPI-API uses Intel's RAPL to read machine status registers (MSRs) to collect power consumption. We have executed modified versions of each benchmark application on each physical system to collect runtime and power consumption from benchmark logs. The hardware features, performance (Runtime) and Power are available in files /benchmark_algo/%application%/%application%_power_lab.csv e.g. for mser it is available at benchmark_algo/mser/mser_power_lab.csv, etc. Performance and Power Dataset from Gem5 Systems with Hardware Features of Physical Systems: For validation purposes, we have to build Gem5 systems with identical hardware feature values as the physical systems. We have collected performance power for each benchmark application by executing each of these systems. The files /benchmark_algo/%application%/Gem5LabSystemConfigs.csv under each application folder consists of performance (runtime) and power for the Gem5 systems with features of physical systems.

Files

Institutions

Dhirubhai Ambani Institute of Information and Communication Technology

Categories

Applied Sciences

Licence