Whare-map

Jason Mars, Lingjia Tang
2013 Proceedings of the 40th Annual International Symposium on Computer Architecture - ISCA '13  
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
more » ... 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 heterogeneityoblivious job placement and up to an 80% improvement for web-service applications that are particularly sensitive to heterogeneity.
doi:10.1145/2485922.2485975 dblp:conf/isca/MarsT13 fatcat:6uwkaqpedfhundlyslj3yuwvba