1018288
Coupled Power and Thermal Simulation with Active Cooling
Power is rapidly becoming the primary design constraint for systems ranging from server computers to handhelds. In this paper we study microarchitecture-level coupled power and thermal simulation considering dynamic and leakage power models with temperature and voltage scaling. We develop an accurate temperature-dependent leakage power model and efficient temperature calculation, and show that leakage energy can be different by up to 10X for temperatures between 35°C and 110°C. Given the growing significance of leakage power and its sensitive dependence on temperature, no power simulation without considering dynamic temperature calculation is accurate. Furthermore, we discuss the thermal runaway induced by the interdependence between leakage power and temperature, and show that in the near future thermal runaway could be a severe problem. We also study the microarchitecture level coupled power and thermal management by novel active cooling techniques that reduce packaging thermal resistance. We show that the direct water-spray cooling technique reduces thermal resistance from 0.8°C/W for conventional packaging to 0.05°C/W, and increases system maximum clock by up to 2.44X under the same thermal constraints.
9509924
Microarchitecture-level leakage reduction with data retention
In this paper, we study microarchitecture-level leakage energy reduction by power gating. We consider the virtual power/ground rails clamp (VRC) and multithreshold CMOS (MTCMOS) techniques and apply VRC to memory-based units for data retention and MTCMOS to the other units. We propose a systematic methodology for leakage reduction at the microarchitecture level, in which profiling of idle period distribution and ideal power gating analysis are used to select a target component for realistic power gating. We show that the ideal leakage energy reduction can be up to 30% of the total energy for the modern high-performance very long instruction word processors we study and that the secondary level (L2) cache contributes most to the reduction. We further improve the existing adaptive cache decay method for leakage reduction by using VRC for data retention and name it VRC decay . Applied to L2 cache, the VRC decay, on average, increases performance by 5.6% and reduces system energy by 24.1%, compared to the adaptive cache decay without data retention.
1023314
An Investigation into the Application of Different Performance Prediction Methods to Distributed Enterprise Applications
Response time predictions for workload on new server architectures can enhance Service Level Agreement–based resource management. This paper evaluates two performance prediction methods using a distributed enterprise application benchmark. The historical method makes predictions by extrapolating from previously gathered performance data, while the layered queuing method makes predictions by solving layered queuing networks. The methods are evaluated in terms of: the systems that can be modelled; the metrics that can be predicted; the ease with which the models can be created and the level of expertise required; the overheads of recalibrating a model; and the delay when evaluating a prediction. The paper also investigates how a prediction-enhanced resource management algorithm can be tuned so as to compensate for predictive inaccuracy and balance the costs of SLA violations and server usage.
6921769
Time-compression: systems concerns, usage, and benefits
With the proliferation of online multimedia content and thepopularity of multimedia streaming systems, it is increasinglyuseful to be able to skim and browse multimedia quickly. A keytechnique that enables quick browsing of multimedia istime-compression. Prior research has described how speech can betime-compressed (shortened in duration) while preserving the pitchof the audio. However, client-server systems providing thisfunctionality have not been available.
In this paper, we first describe the key tradeoffs faced bydesigners of streaming multimedia systems deployingtime-compression. The implementation tradeoffs primarily impact thegranularity of time-compression supported (discrete vs. continuous)and the latency (wait-time) experienced by users after adjustingdegree of time-compression. We report results of user studiesshowing impact of these factors on the average- compression-rateachieved. We also present data on the usage patterns and benefitsof time compression. Overall, we show significant time-savings forusers and that considerable flexibility is available to thedesigners of client-server streaming systems with timecompression.
16360889
Optimising static workload allocation in multiclusters
Summary form only given. Workload allocation and job dispatching are two fundamental components in static job scheduling for distributed systems. We address the static workload allocation techniques for two types of job stream in multicluster systems, namely, nonreal-time job streams and soft-real-time job streams, which request different qualities of service. Two workload allocation strategies (called ORT and OMR) are developed by establishing and numerically solving two optimisation equation sets. The ORT strategy achieves the optimised mean response time for the nonreal-time job stream; while the OMR strategy can gain the optimised mean miss rate for the soft-real-time job stream over multiple clusters (these strategies can also be applied in a single cluster system). The effectiveness of both strategies is demonstrated through theoretical analysis. The proposed workload allocation schemes are combined with two job dispatching strategies (weighted random and weighted round-robin) to generate new static job scheduling algorithms for multicluster environments. These algorithms are evaluated through extensive experimental studies and the results show that compared with static approaches without the optimisation techniques, the proposed workload allocation schemes can significantly improve the performance of static job scheduling in multiclusters, in terms of both the mean response time (for the nonreal-time jobs) and the mean miss rate (for soft-real-time jobs).
5953229
Building an intelligent camera management system
Given rapid improvements in storage devices, network infrastructure and streaming-media technologies, a large number of corporations and universities are recording lectures and making them available online for anytime, anywhere access. However, producing high-quality lecture videos is still labor intensive and expensive. Fortunately, recent technology advances are making it feasible to build automated camera management systems to capture lectures. In this paper we report our design of such a system, including system configuration, audio-visual tracking techniques, software architecture, and user study. Motivated by different roles in a professional video production team, we have developed a multi-cinematographer single-director camera management system. The system performs lecturer tracking, audience tracking, and video editing all fully automatically, and offers quality close to that of human-operated systems.
2855119
Optimal Scheduling of Aperiodic Jobs on Cluster
This paper presents an algorithm to schedule aperiodic jobs on a cluster system. A cluster consists of one dispatcher and multiple schedulers. The algorithm is optimal for the response time of each aperiodic job. Aperiodic jobs are partitioned into phases and assigned deadlines by the dispatcher. With the deadline, the aperiodic jobs can be scheduled uniformly under EDF (Earliest Deadline First) together with periodic jobs. With rigorous theoretical analysis and proof, we have that even if the dispatcher has no scheduling information, the algorithm can still dispatch the aperiodic jobs onto the proper scheduler to achieve optimal response time and also guarantee the deadline requirements of periodic jobs.