Merlin

Priyanka Tembey, Ada Gavrilovska, Karsten Schwan
2014 Proceedings of the ACM Symposium on Cloud Computing - SOCC '14  
Workload consolidation, whether via use of virtualization or with lightweight, container-based methods, is critically important for current and future datacenter and cloud computing systems. Yet such consolidation challenges the ability of current systems to meet application resource needs and isolate their resource shares, particularly for high core count or 'scaleup' servers. This paper presents the 'Merlin' approach to managing the resources of multicore platforms, which satisfies an
more » ... ion's resource requirements efficiently -using low cost allocations -and improves isolation -measured as increased predictability of application execution. Merlin (i) creates a virtual platform (VP) as a system-level resource commitment to an application's resource shares, (ii) enforces its isolation, and (iii) operates with low runtime overhead. Further, Merlin's resource (re)-allocation and isolation methods operate by constructing online models that capture the resource 'sensitivities' of the currently running applications along all of their resource dimensions. Elevating isolation into a first-class management principle, these sensitivity-and cost-based allocation and sharing methods lead to efficient methods for shared resource use on scaleup server systems. Experimental evaluations on a large corecount machine demonstrate improved performance with reduced performance variation and increased system throughput and efficiency, for a wide range of popular datacenter workloads, compared with the methods used in prior work and with the state-of-art Xen hypervisor.
doi:10.1145/2670979.2670993 dblp:conf/cloud/TembeyGS14 fatcat:r7fa4sudrvdorflctgobj6iauq