Queuing Theoretic Analysis of Power-performance Tradeoff in Power-efficient Computing

TL;DR

This paper uses queuing theory to analyze the power-performance tradeoff in power-efficient computing, identifying optimal system configurations that maximize efficiency for both single and multi-server systems.

Contribution

It provides a queuing theoretic framework to determine optimal processing speeds and system settings, revealing 'sweet spots' for power efficiency in various configurations.

Findings

Optimal processing speed and threshold values minimize power consumption.

Existence of best server farm size and speed combinations in multi-server systems.

Identification of power-efficient operating points in different system setups.

Abstract

In this paper we study the power-performance relationship of power-efficient computing from a queuing theoretic perspective. We investigate the interplay of several system operations including processing speed, system on/off decisions, and server farm size. We identify that there are oftentimes "sweet spots" in power-efficient operations: there exist optimal combinations of processing speed and system settings that maximize power efficiency. For the single server case, a widely deployed threshold mechanism is studied. We show that there exist optimal processing speed and threshold value pairs that minimize the power consumption. This holds for the threshold mechanism with job batching. For the multi-server case, it is shown that there exist best processing speed and server farm size combinations.