Energy and Performance-Can a Wimpy-Node Cluster Challenge a Brawny Server?

TL;DR

This paper compares small, energy-efficient node clusters to powerful servers, demonstrating that clusters can save energy with minimal performance loss under variable workloads.

Contribution

It provides an empirical evaluation of energy and performance trade-offs between wimpy-node clusters and brawny servers for database workloads.

Findings

Clusters can save energy without significant performance loss.

Workload-dependent energy savings are achievable.

Clusters respond dynamically to workload changes.

Abstract

Traditional DBMS servers are usually over-provisioned for most of their daily workloads and, because they do not show good energy proportionality, waste a lot of energy while underutilized. A cluster of small (wimpy) servers, where the number of nodes can dynamically adjust to the current workload, might offer better energy characteristics for these workloads. Yet, clusters suffer from "friction losses" and may not be able to quickly adapt to the workload, whereas a single, brawny server delivers performance instantaneously. In this paper, we compare a small cluster of lightweight nodes to a single server in terms of performance and energy efficiency. We run several benchmarks, consisting of OLTP and OLAP queries at variable utilization to test the system's ability to adjust to the workloads. To quantify possible energy saving and its conceivable drawback on query runtime, we evaluate our implementation on a cluster as well as on a single, brawny server and compare the results w.r.t. performance and energy consumption. Our findings confirm that - based on the workload - energy can be saved without sacrificing too much performance.