Compiling for niceness

Abstract

As the class of datacenters recently coined as warehouse scale computers (WSCs) continues to leverage commodity multicore processors with increasing core counts, there is a growing need to consolidate various workloads on these machines to fully utilize their computation power. However, it is well known that when multiple applications are co-located on a multicore machine, contention for shared memory resources can cause severe cross-core performance interference. To ensure that the quality of service (QoS) of user-facing applications does not suffer from performance interference, WSC operators resort to disallowing co-location of latencysensitive applications with other applications. This policy translates to low machine utilization and millions of dollars wasted in WSCs.This paper presents QoS-Compile, the first compilation approach that statically manipulates application contentiousness to enable the co-location of applications with varying QoS requirements, and as a result, can greatly improve machine utilization. Our technique first pinpoints an application's code regions that tend to cause contention and performance interference. QoS-Compile then transforms those regions to reduce their contentious nature. In essence, to co-locate applications of different QoS priorities, our compilation technique uses pessimizing transformations to throttle down the memory access rate of the contentious regions in low priority applications to reduce their interference to high priority applications. Our evaluation using synthetic benchmarks, SPEC benchmarks and large-scale Google applications show that QoS-Compile can greatly reduce contention, improve QoS of applications, and improve machine utilization. Our experiments show that our technique improves applications' QoS performance by 21% and machine utilization by 36% on average.

PowerChief

“…Quasar [16] and Paragon [15] manages datacenter resources from multiple dimensions and use collaborative filtering to allocate the right type and amount of resources satisfying the QoS target. Compilation techniques [31,55,56] are proposed to guarantee the latency target by transforming code segments that cause severe performance interference. However, all techniques in this research category cannot be directly applied in power constrained scenario where our research proposal resides.…”

“…Several studies show that slightly increased response latency leads to significant revenue drop for cloud service providers [8,13,49]. Although tremendous research efforts have been devoted to addressing this problem from various aspects such as heterogeneity [30,36,37] and interference [15,16,31,38,55,56,61,62], it is still largely an unsolved problem as more impacting factors are continuing to be discovered.…”

PowerChief

“…Several studies show that slightly increased response latency leads to significant revenue drop for cloud service providers [8,13,49]. Although tremendous research efforts have been devoted to addressing this problem from various aspects such as heterogeneity [30,36,37] and interference [15,16,31,38,55,56,61,62], it is still largely an unsolved problem as more impacting factors are continuing to be discovered.…”