Memory resource management in VMware ESX server
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Diagnosing performance overheads in the xen virtual machine environment
Proceedings of the 1st ACM/USENIX international conference on Virtual execution environments
Intel Virtualization Technology
Computer
Measuring CPU overhead for I/O processing in the Xen virtual machine monitor
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
Virtual hierarchies to support server consolidation
Proceedings of the 34th annual international symposium on Computer architecture
I/O processing in a virtualized platform: a simulation-driven approach
Proceedings of the 3rd international conference on Virtual execution environments
Characterization of network processing overheads in Xen
VTDC '06 Proceedings of the 2nd International Workshop on Virtualization Technology in Distributed Computing
An Evaluation of Server Consolidation Workloads for Multi-Core Designs
IISWC '07 Proceedings of the 2007 IEEE 10th International Symposium on Workload Characterization
Measuring interference between live datacenter applications
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Empirical study of performance benefits of hardware assisted virtualization
Proceedings of the 6th ACM India Computing Convention
Black box scheduling for resource intensive virtual machine workloads with interference models
Future Generation Computer Systems
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As virtualization becomes ubiquitous in data centers, it becomes imperative that the definition of future multi-core platform architectures take into account the performance behavior and requirements of consolidated servers. However, performance analysis of commercial servers has traditionally been focused on individual parallel benchmarks running in dedicated mode. In this paper, we present an approach to developing a performance model for virtualized CMP servers potentially running heterogeneous workloads simultaneously. We show that a consolidation performance model can be developed by decomposing the problem into three constituent parts: (a) core interference due to consolidation, (b) cache interference due to consolidation and (c) virtualization overheads. Having laid out the consolidation framework, we then perform an initial case study with a new consolidation benchmark (vConsolidate). We present vConsolidate measurement characteristics on a Core 2 Duo-based server platform and then apply the performance model in order to predict the performance slowdown of each workload due to consolidation. We show that the model constructed is capable of achieving sufficient accuracy and discuss how to improve the accuracy in the future. Last but not least, we describe the extensions required to develop a complete generalized consolidation performance model.