Spinning is a synchronization mechanism commonly used in applications and operating systems. Excessive spinning, however, often indicates performance or correctness (e.g., livelock) problems. Detecting if applications and operating systems are spinning is essential for achieving high performance, especially in consolidated servers running virtual machines. Prior research has used source or binary instrumentation to detect spinning. However, these approaches place a significant burden on programmers and may even be infeasible in certain situations. In this paper, we propose efficient hardware to detect spinning in unmodified applications and operating systems. Based on this hardware, we develop 1) scheduling and power policies that adaptively manage resources for spinning threads, 2) system support that helps detect when a multithreaded program is livelocked, and 3) hardware performance counters that accurately reflect system performance. Using full-system simulation with SPEC OMP, SPLASH-2, and Wisconsin commercial workloads, we demonstrate that our mechanisms effectively improve the management of multithreaded systems.

Dynamic consolidation of virtual machines (VMs) can reduce energy consumption by switching idle hosts to sleep mode. However, to meet the quality of service of customers, it is necessary to achieve the trade-off between energy and performance. This paper first puts forward a new dynamic threshold adjustment method using the variation coefficient of historical CPU utilisation, actual CPU utilisation and million instructions per second requests by VMs in migration list. Furthermore, it devises a novel VM allocation policy based on the grey correlation degree model, and formulates a conversion model of CPU utilisation for achieving better trade-off between energy consumption and performance. Finally, some experiments are carried out on the CloudSim and the PlanetLab workloads. The experimental results show that the methods proposed in this paper have obvious advantages on the trade-off between energy and performance during the VM consolidation.