2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)最新文献_第5页

Self-Aware Workload Forecasting in Data Center Power Prediction 数据中心功率预测中的自感知工作负荷预测

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00047

Ying-Feng Hsu, Kazuhiro Matsuda, Morito Matsuoka

{"title":"Self-Aware Workload Forecasting in Data Center Power Prediction","authors":"Ying-Feng Hsu, Kazuhiro Matsuda, Morito Matsuoka","doi":"10.1109/CCGRID.2018.00047","DOIUrl":"https://doi.org/10.1109/CCGRID.2018.00047","url":null,"abstract":"The number and scale of data centers are rapidly increasing, due to the growing demand for cloud computing services. Cloud computing infrastructure relies on a massive amount of information and communication technology (ICT) equipment, which consume an enormous amount of power. Power saving and energy optimization have therefore become essential goals for data centers. An enhanced data center energy management system (DEMS) provides a solution for data center power consumption based on its coordinative control of ICT equipment. An efficient power prediction model is essential for such a DEMS because it facilitates the proactive control of ICT equipment and reduces the total power consumption. In this paper, we propose a novel self-aware workload forecasting (SAWF) framework for total power consumption prediction in data centers. It includes three major components. First, there is a feature selection module, which evaluates the importance of variables from all ICT equipment in a data center and dynamically selects the most relevant variables for data input. Second, we propose an accurate and efficient neural network model to forecast future total power consumption. Third, we provide an online error monitoring and model updating module that continuously monitors prediction errors and updates the model when necessary.","PeriodicalId":321027,"journal":{"name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132320659","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}

引用次数: 19

IoT Edge Device Based Key Frame Extraction for Face in Video Recognition 基于IoT边缘设备的视频识别人脸关键帧提取

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00087

Xuan Qi, Chen Liu, S. Schuckers

引用次数: 9

Multi-Level Load Balancing with an Integrated Runtime Approach 集成运行时方法的多级负载平衡

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00018

Seonmyeong Bak, Harshitha Menon, Sam White, M. Diener, L. Kalé

{"title":"Multi-Level Load Balancing with an Integrated Runtime Approach","authors":"Seonmyeong Bak, Harshitha Menon, Sam White, M. Diener, L. Kalé","doi":"10.1109/CCGRID.2018.00018","DOIUrl":"https://doi.org/10.1109/CCGRID.2018.00018","url":null,"abstract":"The recent trend of increasing numbers of cores per chip has resulted in vast amounts of on-node parallelism. These high core counts result in hardware variability that introduces imbalance. Applications are also becoming more complex, re-sulting in dynamic load imbalance. Load imbalance of any kind can result in loss of performance and system utilization. We address the challenge of handling both transient and persistent load imbalances while maintaining locality with low overhead. In this paper, we propose an integrated runtime system that combines the Charm++ distributed programming model with concurrent tasks to mitigate load imbalances within and across shared memory address spaces. It utilizes a periodic assignment of work to cores based on load measurement, in combination with user created tasks to handle load imbalance. We integrate OpenMP with Charm++ to enable creation of potential tasks via OpenMP's parallel loop construct. This is also available to MPI applications through the Adaptive MPI implementation. We demonstrate the benefits of our work on three applications. We show improvements of Lassen by 29.6% on Cori and 46.5% on Theta. We also demonstrate the benefits on a Charm++ application, ChaNGa by 25.7% on Theta, as well as an MPI proxy application, Kripke, using Adaptive MPI.","PeriodicalId":321027,"journal":{"name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124014066","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}

引用次数: 17

A Conceptual Framework for the Use of Graph Representation Within High Energy Physics Analysis 在高能物理分析中使用图表示的概念框架

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00063

Danielle Turvill, L. Barnby, A. Anjum

引用次数: 1

A Scalable Cloud-Edge Computing Framework for Supporting Device-Adaptive Big Media Provisioning 支持设备自适应大媒体供应的可扩展云边缘计算框架

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00099

A. Galletta, A. Cuzzocrea, A. Celesti, M. Fazio, M. Villari

引用次数: 4

An Elasticity Study of Distributed Graph Processing 分布式图处理的弹性研究

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00062

Sietse Au, Alexandru Uta, A. Ilyushkin, A. Iosup

{"title":"An Elasticity Study of Distributed Graph Processing","authors":"Sietse Au, Alexandru Uta, A. Ilyushkin, A. Iosup","doi":"10.1109/CCGRID.2018.00062","DOIUrl":"https://doi.org/10.1109/CCGRID.2018.00062","url":null,"abstract":"Graphs are a natural fit for modeling concepts used in solving diverse problems in science, commerce, engineering, and governance. Responding to the variety of graph data and algorithms, many parallel and distributed graph processing systems exist. However, until now these platforms use a static model of deployment: they only run on a pre-defined set of machines. This raises many conceptual and pragmatic issues, including misfit with the highly dynamic nature of graph processing, and could lead to resource waste and high operational costs. In contrast, in this work we explore a dynamic model of deployment. We first characterize workload dynamicity, beyond mere active-vertex variability. Then, to conduct an in-depth elasticity study of distributed graph processing, we build a prototype, JoyGraph, which is the first such system that implements complex, policy-based, and fine-grained elasticity. Using the state-of-the-art LDBC Graphalytics benchmark and the SPEC Cloud Group's elasticity metrics, we show the benefits of elasticity in graph processing: (i) improved resource utilization, (ii) reduced operational costs, and (iii) aligned operation-workload dynamicity. Furthermore, we explore the cost of elasticity in graph processing. We identify a key drawback: although elasticity does not degrade application throughput, graph-processing workloads are sensitive to data movement while leasing or releasing resources.","PeriodicalId":321027,"journal":{"name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116046635","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}

引用次数: 3

A Hard Real-time Scheduler for Spark on YARN 基于YARN的Spark硬实时调度器

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00096

Guolu Wang, Jungang Xu, Renfeng Liu, Shanshan Huang

{"title":"A Hard Real-time Scheduler for Spark on YARN","authors":"Guolu Wang, Jungang Xu, Renfeng Liu, Shanshan Huang","doi":"10.1109/CCGRID.2018.00096","DOIUrl":"https://doi.org/10.1109/CCGRID.2018.00096","url":null,"abstract":"Apache Spark is a fast and general engine for large-scale data processing using distributed memory. It provides different deploy modes to meet the needs of different users and Spark on YARN is the most popular deploy mode. Different deploy modes have different scheduling mechanisms. Spark on YARN has three different schedulers, including FIFO Scheduler, Fair Scheduler, and Capacity Scheduler. However, these three schedulers cannot fit hard real-time application scenarios. With the application of Apache Spark more widely, the needs of hard real-time scheduling will increase quickly. In this paper, we proposed a novel hard real-time scheduling algorithm called DVDA (Deadline and Value Density-Aware) in order to meet the requirements of hard real-time scheduling. Compared with traditional EDF (Earliest Deadline First) algorithm which only considers the deadline, the DVDA algorithm considers both the deadline and value density of the application. Furthermore, we implement a DVDA Scheduler for Spark on YARN based on the DVDA algorithm. Finally, the experiments are conducted to verify the effectiveness of the algorithm. Experimental results show that the proposed algorithm can increase the application completed rate by 18% and 6%, Value Income by 78% and 32% compared with default Capacity scheduler and EDF-Capacity scheduler respectively.","PeriodicalId":321027,"journal":{"name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127023801","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}

引用次数: 6

Davram: Distributed Virtual Memory in User Space Davram:用户空间中的分布式虚拟内存

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00050

Linhua Jiang, Ke Wang, Dongfang Zhao

引用次数: 4

A Provider-Agnostic Approach to Multi-cloud Orchestration Using a Constraint Language 使用约束语言实现多云编排的提供者不可知方法

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00032

Dani Baur, Daniel Seybold, F. Griesinger, Hynek Masata, Jörg Domaschka

{"title":"A Provider-Agnostic Approach to Multi-cloud Orchestration Using a Constraint Language","authors":"Dani Baur, Daniel Seybold, F. Griesinger, Hynek Masata, Jörg Domaschka","doi":"10.1109/CCGRID.2018.00032","DOIUrl":"https://doi.org/10.1109/CCGRID.2018.00032","url":null,"abstract":"Cloud computing and its computing as an utility paradigm provides on-demand resources allowing the seamless adaptation of applications to fluctuating demands. While the Cloud's ongoing commercialisation has lead to a vast provider landscape, vendor lock-in is still a major hindrance. Recent outages demonstrate that relying exclusively on one provider is not sufficient. While existing cloud orchestration tools promise to solve the problems by supporting deployments across multiple cloud providers, they typically rely on provider dependent models forcing prior knowledge of offers and obstructing flexibility in case of errors. We propose a cloud provider-agnostic application and resource description using a constraint language. It allows users to express resource requirements of an application without prior knowledge of existing offers. Additionally, we propose a discovery service automatically collecting available offers. We combine this with a matchmaking algorithm representing the discovery model and the user-given constraints in a constraint satisfaction problem (CSP) that is then solved. Finally, we manipulate this discovery model during runtime to react on errors. Our evaluation shows that using a constraint-based language is a feasible approach to the provider selection problem, and that it helps to overcome vendor lock-in.","PeriodicalId":321027,"journal":{"name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132911648","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}

引用次数: 13

Enabling Efficient Inter-Node Message Passing and Remote Memory Access Via a uGNI Based Light-Weight Network Substrate for Cray Interconnects 基于uGNI的Cray互连轻量级网络基板实现高效节点间消息传递和远程内存访问

2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) Pub Date : 2018-05-01 DOI: 10.1109/CCGRID.2018.00006

U. Wickramasinghe, A. Lumsdaine

{"title":"Enabling Efficient Inter-Node Message Passing and Remote Memory Access Via a uGNI Based Light-Weight Network Substrate for Cray Interconnects","authors":"U. Wickramasinghe, A. Lumsdaine","doi":"10.1109/CCGRID.2018.00006","DOIUrl":"https://doi.org/10.1109/CCGRID.2018.00006","url":null,"abstract":"Today's cutting-edge network hardware features extremely low latency and high bandwidth transactions for higher-level communication substrates. The Cray XC/XE family of network fabrics, also known as Cray Aries/Gemini respectively, supports such high-performance remote memory access operations (RMA) and a plethora of transaction modes to optimize communication via lower-level interfaces such as uGNI and DMAPP. However, enabling efficient one-sided communication for higher-level substrates is difficult due to barriers presented by the programming model itself, as well as miscellaneous synchronization bottlenecks at the runtime layers. We present an efficient programming model based on a distributed memory allocator for RMA and a communication substrate based on readers and writers for inter-node message passing and RMA operations. We try to maximize performance by introducing a scalable RMA event notification scheme and synchronization protocols that fully leverage Aries/Gemini fabric. Micro-benchmark results demonstrate that our library outperforms Cray MPI-3.0-based RMA one-sided operations by 1.5X and up to 6X in certain cases and is comparable or improves upon performance on others.","PeriodicalId":321027,"journal":{"name":"2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130790216","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}

引用次数: 1