Battery-aware power management based on Markovian decision processes
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Single-ISA Heterogeneous Multi-Core Architectures: The Potential for Processor Power Reduction
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Xen and co.: communication-aware CPU scheduling for consolidated xen-based hosting platforms
Proceedings of the 3rd international conference on Virtual execution environments
Comparison of the three CPU schedulers in Xen
ACM SIGMETRICS Performance Evaluation Review
Scheduling I/O in virtual machine monitors
Proceedings of the fourth ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
Variation-Aware Application Scheduling and Power Management for Chip Multiprocessors
ISCA '08 Proceedings of the 35th Annual International Symposium on Computer Architecture
Guest-Aware Priority-Based Virtual Machine Scheduling for Highly Consolidated Server
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
Power-Efficient Response Time Guarantees for Virtualized Enterprise Servers
RTSS '08 Proceedings of the 2008 Real-Time Systems Symposium
HASS: a scheduler for heterogeneous multicore systems
ACM SIGOPS Operating Systems Review
Thread motion: fine-grained power management for multi-core systems
Proceedings of the 36th annual international symposium on Computer architecture
Temperature-constrained power control for chip multiprocessors with online model estimation
Proceedings of the 36th annual international symposium on Computer architecture
ACM SIGOPS Operating Systems Review
Efficient program scheduling for heterogeneous multi-core processors
Proceedings of the 46th Annual Design Automation Conference
Multiple clock and voltage domains for chip multi processors
Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture
Bias scheduling in heterogeneous multi-core architectures
Proceedings of the 5th European conference on Computer systems
A comprehensive scheduler for asymmetric multicore systems
Proceedings of the 5th European conference on Computer systems
Analyzing performance asymmetric multicore processors for latency sensitive datacenter applications
HotPower'10 Proceedings of the 2010 international conference on Power aware computing and systems
Scalable power control for many-core architectures running multi-threaded applications
Proceedings of the 38th annual international symposium on Computer architecture
PGCapping: exploiting power gating for power capping and core lifetime balancing in CMPs
Proceedings of the 21st international conference on Parallel architectures and compilation techniques
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Multi-core architectures with asymmetric core performance have recently shown great promise, because applications with different needs can benefit from either the high performance of a fast core or the high parallelism and power efficiency of a group of slow cores. This performance heterogeneity can be particularly beneficial to applications running in virtual machines (VMs) on virtualized servers, which often have different needs and exhibit different performance and power characteristics. Therefore, scheduling VMs on performance-asymmetric multi-core architectures can have a great impact on a system's overall energy efficiency. Unfortunately, existing VM managers, such as Xen, have not taken the heterogeneity into account and thus often result in low energy efficiencies. In this paper, we propose a novel VM scheduling algorithm that exploits core performance heterogeneity to optimize the overall system energy efficiency. We first introduce a metric termed energy-efficiency factor to characterize the power and performance behaviors of the applications hosted by VMs on different cores. We then present a method to dynamically estimate the VM's energy-efficiency factors and then map the VMs to heterogeneous cores, such that the energy efficiency of the entire system is maximized. We implement the proposed algorithm in Xen and evaluate it with standard benchmarks on a real testbed. The experimental results show that our solution improves the system energy efficiency (i.e., performance per watt) by 13.5% on average and up to 55% for some benchmarks, compared to the default Xen scheduler.