International Conference on Green Computing最新文献

{"title":"Information processing at work: On energy-aware algorithm design","authors":"A. Cisternino, P. Ferragina, Davide Morelli, M. Coppola","doi":"10.1109/GREENCOMP.2010.5598288","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598288","url":null,"abstract":"It is common experience to upgrade firmware of mobile devices and obtain longer battery life, living proof of how software affects power consumption of a device. Despite this empirical observation, there is a lack for models and methodologies correlating computations with power consumption. In this paper we propose a methodology for conducting measures which result independent of the underlying system running the algorithm/software to be tested. Early experimental results are presented and discussed, showing that this methodology is robust and can be used in many settings. We thus adopt it to study the impact of computation and pattern of memory accesses onto the energy-profile of an algorithm when executed on different processors and architectures, thus achieving some surprising insights on green algorithm design.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133306144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A light-weight approach to reducing energy management delays in disks","authors":"Guanying Wang, A. Butt, C. Gniady, Puranjoy Bhattacharjee","doi":"10.1109/GREENCOMP.2010.5598307","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598307","url":null,"abstract":"Today's enterprise computing systems routinely employ a large number of computers for tasks ranging from supporting daily business operations to mission-critical back-end applications. These computers consume a lot of energy whose monetary cost accounts for a significant portion of an enterprise's operating budget. Consequently, enterprises employ energy saving techniques such as turning machines off overnight and dynamic energy management during the business hours. Unfortunately, dynamic energy management, especially that for disks, introduces delays when an accessed disk is in a low power state and needs to be brought into an active state. Existing techniques mainly focus on reducing energy consumption and do not take advantage of enterprise-wide resources to mitigate the associated delays. Thus, systems designers are faced with a critical trade-off: saving energy reduces operating costs but may increase the delays exposed to the users, conversely, reducing access latencies and making the system more responsive may preclude energy management techniques. In this paper, we propose System-wide Alternative Retrieval of Data (SARD) that exploits the large number of machines in an enterprise environment to transparently retrieve binaries from other nodes, thus avoiding access delays when the local disk is in a low power mode. SARD uses a software-based approach to reduce spin-up delays while eliminating the need for major operating system changes, custom buffering, or shared memory infrastructure. The main goal of SARD is not to increase energy savings, rather reduce delays associated with energy management techniques, which will encourage users to utilize energy management techniques more frequently and realize the energy savings. Our evaluation of SARD using trace-driven simulations as well as an actual implementation in a real system shows over 71% average reduction in delays associated with energy management. Moreover, SARD achieves an additional 5.1% average reduction in energy consumption for typical desktop applications compared to the widely-used timeout-based disk energy management.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126650006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CPU gradients: Performance-aware energy conservation in multitier systems","authors":"Shuyi Chen, Kaustubh R. Joshi, M. Hiltunen, R. Schlichting, W. Sanders","doi":"10.1109/GREENCOMP.2010.5598296","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598296","url":null,"abstract":"Dynamic voltage and frequency scaling (DVFS) and virtual machine (VM) based server consolidation are well-known CPU scaling techniques for energy conservation that can have an adverse impact on system performance. For the responsiveness-sensitive multitier applications running in today's data centers, queuing models should ideally be used to predict the impact of CPU scaling on response time, to allow appropriate runtime trade-offs between performance and energy use. In practice, however, such models are difficult to construct and thus are often abandoned for ad-hoc solutions. In this paper, an alternative measurement-based approach that predicts the impact without requiring detailed application knowledge is presented. The approach proposes a new predictive model, the CPU gradient, that can be automatically measured on a running system using lightweight and nonintrusive CPU perturbations. The practical feasibility of the approach is demonstrated using extensive experiments on multiple multitier applications, and it is shown that simple energy controllers can use gradient predictions to derive as much as 50% energy savings while still meeting response time constraints.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"329 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124642284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The power of data centers: Opportunities and challenges","authors":"P. Kundu","doi":"10.1109/GREENCOMP.2010.5598265","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598265","url":null,"abstract":"While cloud computing holds great promise for reducing capital expenses (capex) and operating expenses (opex) much needs to come together in a diverse ecosystem of the typical data center, in order to truly realize it's full potential vis a vis power. This talk will walk through some possibilities for power reduction and the challenges for realizing these in the future.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129650621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy-efficient application-aware online provisioning for virtualized clouds and data centers","authors":"I. Rodero, Juan Jaramillo, Andres Quiroz, M. Parashar, F. Guim, S. Poole","doi":"10.1109/GREENCOMP.2010.5598283","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598283","url":null,"abstract":"As energy efficiency and associated costs become key concerns, consolidated and virtualized data centers and clouds are attractive computing platforms for data- and compute- intensive applications. These platforms provide an abstraction of nearly-unlimited computing resources through the elastic use of pools of consolidated resources, and provide opportunities for higher utilization and energy savings. Recently, these platforms are also being considered for more traditional high-performance computing (HPC) applications that have typically targeted Grids and similar conventional HPC platforms. However, maximizing energy efficiency, cost-effectiveness, and utilization for these applications while ensuring performance and other Quality of Service (QoS) guarantees, requires leveraging important and extremely challenging tradeoffs. These include, for example, the tradeoff between the need to efficiently create and provision Virtual Machines (VMs) on data center resources and the need to accommodate the heterogeneous resource demands and runtimes of these applications. In this paper we present an energy-aware online provisioning approach for HPC applications on consolidated and virtualized computing platforms. Energy efficiency is achieved using a workload-aware, just-right dynamic provisioning mechanism and the ability to power down subsystems of a host system that are not required by the VMs mapped to it. We evaluate the presented approach using real HPC workload traces from widely distributed production systems. The results presented demonstrated that compared to typical reactive or predefined provisioning, our approach achieves significant improvements in energy efficiency with an acceptable QoS penalty.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125384459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling the performance and energy of storage arrays","authors":"Sankaran Sivathanu, Ling Liu, C. Ungureanu","doi":"10.1109/GREENCOMP.2010.5598308","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598308","url":null,"abstract":"We propose a novel framework for evaluating techniques for power optimization in storage. Given an arbitrary trace of disk requests, we split it into short time intervals, extract a set of simple statistics for each interval, and apply an analytical model to those statistics to obtain accurate information regarding the performance and energy characteristics of the system for that workload. The key abstraction used in our analytical model is the run-length - a single sequential run of requests at the disk level. Using this abstraction, the model is able to account for arbitrary interactions of random and sequential I/Os in the context of a RAID array, and obtain accurate results with less effort than a detailed individual request-level simulation. Various layout and migration policies aimed at power conservation can be easily expressed as transformations on this set of statistics for each time interval. We demonstrate the efficacy of our framework by using it to evaluate PARAID, a recently proposed technique for power optimization in storage arrays. We show that the performance and power predicted by the model under the migration and layout policies of PARAID accurately match the results of a detailed simulation of the system. The analytic model allows us to identify key parameters that affect PARAID performance, and propose an enhancement to the layout of data in PARAID which we show to perform superior to the original technique. We use both the analytic model and detailed simulations to illustrate the benefit of our new layout. This also demonstrates the significant simplicity of evaluating a new technique by applying a high-level model to the extracted trace statistics, compared to the current alternative of either implementing the new technique or simulating it at the level of individual requests","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114416771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Localized QoS-aware media access control in high-fidelity data center sensing networks","authors":"Renjie Huang, Wenzhan Song, Mingsen Xu, B. Shirazi","doi":"10.1109/GREENCOMP.2010.5598287","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598287","url":null,"abstract":"Low-cost non-intrusive wireless sensor network is ideal for high-fidelity data center monitoring and helping improve energy efficiency. However, the stringent quality of service (QoS) requirements such as real-time data delivery together with the dynamic nature of low-power wireless communication render traditional MAC protocols inapplicable to high-fidelity data center sensing networks. In this paper, we present RoMac, a localized QoS-aware TDMA MAC protocol for high-fidelity data center sensing networks. The key contributions of RoMac include: (1) it provides collision-free communication and persistent QoS guarantee such as constant packet jitter and bounded latency; (2) it is resilient to topology dynamics and truly traffic adaptive in dynamic environments. To our best knowledge, this is the first TDMA MAC protocol that can achieve the resilience to dynamic topologies; (3) its localized design eases the need of scheduling message exchange beyond the initialization phase. We present an implementation of the protocol using the TinyOS operating system running on the iMote2 sensor mote platform. Our experiment result shows that RoMac can achieve the adaptability to dynamic changes in data collection sensor networks and provide persistent QoS support in terms of timeliness, packet jitter and fairness. 1","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125454714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cooling-aware and thermal-aware workload placement for green HPC data centers","authors":"Ayan Banerjee, T. Mukherjee, G. Varsamopoulos, S. Gupta","doi":"10.1109/GREENCOMP.2010.5598306","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598306","url":null,"abstract":"High Performance Computing (HPC) data centers are becoming increasingly dense; the associated power-density and energy consumption of their operation is increasing. Up to half of the total energy is attributed to cooling the data center; greening the data center operations to reduce both computing and cooling energy is imperative. To this effect: i) the Energy Inefficiency Ratio of SPatial job scheduling (a.k.a. job placement) algorithms, also referred as SP-EIR, is analyzed by comparing the total (computing + cooling) energy consumption incurred by the algorithms with the minimum possible energy consumption, while assuming that the job start times are already decided to meet the Service Level Agreements (SLAs); and ii) a coordinated cooling-aware job placement and cooling management algorithm, Highest Thermostat Setting (HTS), is developed. HTS is aware of dynamic behavior of the Computer Room Air Conditioner (CRAC) units and places the jobs in a way to reduce the cooling demands from the CRACs. Dynamic updates of the CRAC thermostat settings based on the cooling demands can enable a reduction in energy consumption. Simulation results based on power measurements and job traces from the ASU HPC data center show that: i) HTS reduces the SP-EIR by 15% compared to LRH, a thermal-aware spatial scheduling algorithm; and ii) in conjunction with FCFS-Backfill, HTS increases the throughput per unit energy by 6.89% and 5.56%, respectively, over LRH and MTDP (an energy-effcient spatial scheduling algorithm with server consolidation).","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"7 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129339150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing job performance under a given power constraint in HPC centers","authors":"M. Etinski, J. Corbalán, J. Labarta, M. Valero","doi":"10.1109/GREENCOMP.2010.5598303","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598303","url":null,"abstract":"Never-ending striving for performance has resulted in a tremendous increase in power consumption of HPC centers. Power budgeting has become very important from several reasons such as reliability, operating costs and limited power draw due to the existing infrastructure. In this paper we propose a power budget guided job scheduling policy that maximize overall job performance for a given power budget. We have shown that using DVFS under a power constraint performance can be significantly improved as it allows more jobs to run simultaneously leading to shorter wait times. Aggressiveness of frequency scaling applied to a job depends on instantaneous power consumption and on the job's predicted performance. Our policy has been evaluated for four workload traces from systems in production use with up to 4 008 processors. The results show that our policy achieves up to two times better performance compared to power budgeting without DVFS. Moreover it leads to 23% lower CPU energy consumption on average. Furthermore, we have investigated how much job performance and energy efficiency can be improved under our policy and same power budget by an increase in the number of DVFS enabled processors.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"80 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115499651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coordinated power management of periodic real-time tasks on chip multiprocessors","authors":"V. Devadas, Hakan Aydin","doi":"10.1109/GREENCOMP.2010.5598261","DOIUrl":"https://doi.org/10.1109/GREENCOMP.2010.5598261","url":null,"abstract":"In this paper, we undertake the problem of minimizing system-level energy on chip-multicore processors (CMPs) executing a periodic real-time workload. Our framework has two components: i.) a static phase that selects a subset of cores upon which the workload can be executed without dissipating excessive static power and performs task-to-core allocation, ii.) a dynamic phase that involves managing the selected cores at run-time through coordinated power management framework that exploits Dynamic Voltage and Frequency Scaling (DVFS) as well as multiple idle states offered by modern CMP architectures, to reduce the dynamic power. We explicitly consider the unique traits of the currently available CMP architectures that distinguish them from multiprocessors, including the unique voltage level shared by the cores and its implications for DVFS. We identify the global energy-efficient frequency which indicates the minimum frequency level at which concurrent execution on multiple cores should take place to preserve the efficiency of DVFS. Then we propose two algorithms CVFS and CVFS* to minimize the dynamic energy consumption through concerted use of DVFS and idle states. Our experimental evaluation indicates that our framework can provide significant gains in system energy.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126875404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}