On the power characteristics of mergesort: An empirical study

Al-Hashimi, Muhammad; Saleh, Mostafa; Abulnaja, Osama Ahmed; Aljabri, Naif

doi:10.1109/accs-peit.2017.8303038

Cited by 6 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The novelty of this work against our previous work [4] is the environment and the reliable instruments. In earlier experiments, we used Windows 7 OS.…”

Section: Experimental Setup and Methodologymentioning

confidence: 97%

“…In this paper, we resolve the limitations of our previous work [4] and present a new comprehensive energy study of mergesort focusing on power characteristics. We resolve the drawbacks in the previous work by using a modern CPU, new reliable profiler, new environment configuration, and in-depth investigation of power consumption behavior of mergesort.…”

Section: Introductionmentioning

confidence: 95%

“…So, depending on the type of economy in effort, some procedures may reasonably be expected to do better when it comes to how fast they go through their energy budget. Based on how it splits lists, it seems that mergesort could have a natural advantage there, which a preliminary investigation seems to indicate [4].…”

Section: Motivationmentioning

confidence: 99%

“…Al-Hashimi et al [4] investigated power and energy consumption of Mergesort and Quicksort on Intel Xeon E5-2640 CPU (SandyBridge). The researchers identified some power efficiency advantage for generic mergesort over a highly optimized 3-way quicksort in terms of power consumption.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Investigating power efficiency of mergesort

et al. 2019

Self Cite

View full text Add to dashboard Cite

Excessive power consumption emerged as a major obstacle to achieving exascale performance in next-generation supercomputers, creating a need to explore new ways to reduce those requirements. In this study, we present a comprehensive empirical investigation of a power advantage anticipated in the mergesort method based on identifying a feature expected to be physically power efficient. We use a highperformance quicksort as a realistic baseline to compare. Results show a generic mergosort to have a distinct advantage over an optimized quicksort lending support to our expectation. They also help develop some insights toward power efficiency gains likely meaningful in a future exascale context where trading some of the abundant performance for much needed power savings in a ubiquitous computation may prove interesting.

show abstract

“…The novelty of this work against our previous work [4] is the environment and the reliable instruments. In earlier experiments, we used Windows 7 OS.…”

Section: Experimental Setup and Methodologymentioning

confidence: 97%

Section: Introductionmentioning

confidence: 95%

Section: Motivationmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Investigating power efficiency of mergesort

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…All the above confounding factors will give a very ideal environment for the power profiling experiments, give more realistic results and reduce the experiment time. We use the proposed profiler and these environment setting to obtain the results for some algorithms power consumption estimation for two published papers [13], [14] .…”

Section: Ambient Temperaturementioning

confidence: 99%

Build Power Profiling Tool for Modern CPUs

Abulnaja¹

2019

JKAU Comp IT Sci

View full text Add to dashboard Cite

. Reduce the application power consumption is one of the main challenges for the HPC community. Code power profilers are very important for researchers to identify the performance bottlenecks and power consumption for their code. Most of the modern CPUs are equipped with a built-in sensor to allow researchers and HPC engineers to estimate the power consumption of the running applications. To estimate the power consumption for any piece of code running on CPU, you need to eliminate the confounding factors as possible and run the code many times until the average converge. The reason for that is the environment, which has the OS and other processes and services running at the same time with your code and may report incorrect power readings. In this paper, we build a power profiler tool, which saves the researcher time by running and profiling different pieces of code with different types of workloads, and keeps running until the average converge. Furthermore, we identify and eliminate the environment confounding factor which saves the researcher time and gives a realistic result for power consumption experiments.

show abstract