Whare-Map: Heterogeneity in “Homogeneous” Warehouse-Scale Computers
Venue
Proceedings of the 2013 ACM/IEEE International Symposium on Computer Architecture (ISCA), IEEE (to appear)
Publication Year
2013
Authors
Jason Mars, Lingjia Tang, Robert Hundt
BibTeX
Abstract
Modern “warehouse scale computers” (WSCs) continue to be embraced as homogeneous
computing platforms. However, due to frequent machine replacements and upgrades,
modern WSCs are in fact composed of diverse commodity microarchitectures and
machine configurations. Yet, current WSCs are architected with the assumption of
homogeneity, leaving a potentially significant performance opportunity unexplored.
In this paper, we expose and quantify the performance impact of the “homogeneity
assumption” for modern production WSCs using industry-strength large-scale
web-service workloads. In addition, we argue for, and evaluate the benefits of, a
heterogeneity-aware WSC using commercial web-service production workloads including
Google’s websearch. We also identify key factors impacting the available
performance opportunity when exploiting heterogeneity and introduce a new metric,
opportunity factor, to quantify an application’s sensitivity to the heterogeneity
in a given WSC. To exploit heterogeneity in “homogeneous” WSCs, we propose
“Whare-Map,” the WSC Heterogeneity Aware Mapper that leverages already in-place
continuous profiling subsystems found in production environments. When employing
“Whare-Map”, we observe a cluster-wide performance improvement of 15% on average
over heterogeneity–oblivious job placement and up to an 80% improvement
forweb-service applications that are particularly sensitive to heterogeneity
