2010 39th International Conference on Parallel Processing最新文献_第3页

Parallel Exact Inference on a CPU-GPGPU Heterogenous System CPU-GPGPU异构系统的并行精确推理

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.15

Hyeran Jeon, Yinglong Xia, V. Prasanna

引用次数: 22

System-Level, Unified In-band and Out-of-band Dynamic Thermal Control 系统级，统一带内带外动态热控制

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.22

Dong Li, Rong Ge, K. Cameron

{"title":"System-Level, Unified In-band and Out-of-band Dynamic Thermal Control","authors":"Dong Li, Rong Ge, K. Cameron","doi":"10.1109/ICPP.2010.22","DOIUrl":"https://doi.org/10.1109/ICPP.2010.22","url":null,"abstract":"High-density computer racks become increasingly commonplace in supercomputing centers and data centers. With tight integration of high-powered computing components in the racks, hot spots or pockets of elevated temperatures on the chips and system can be easily formed when room air circulation is not effective. Hot spots reduce the reliability of high-density systems and increase the chances of thermal emergencies, which further trigger system slowdowns or shutdowns. Techniques such as dynamically scaling down the voltage of the CPUs and fan control are available on today’s systems to reduce heat generation and dissipate heat. Unfortunately, these techniques work independently on their own without cooperation. As a result, to prevent thermal emergencies, systems may work at reduced capacity when full capacity is required. We propose a combined in-band and out-of-band approach to reduce the likelihood of thermal emergency slowdowns and improve the reliability of systems. Our thermal control framework unifies temperature control mechanisms in systems to balance temperature, power consumption, and performance. More precisely, we balance the use of in-band dynamic voltage and frequency scaling (DVFS) with out-of-band proactive fan control. Our results on a power-aware cluster indicate the coordinated use of fan control and DVFS is more effective than either technique in isolation at reducing average system operating temperatures with expected performance.","PeriodicalId":180554,"journal":{"name":"2010 39th International Conference on Parallel Processing","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128645178","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

Model-Driven Traffic Data Acquisition in Vehicular Sensor Networks 基于模型驱动的车辆传感器网络交通数据采集

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.50

Chih-Chieh Hung, Wen-Chih Peng

{"title":"Model-Driven Traffic Data Acquisition in Vehicular Sensor Networks","authors":"Chih-Chieh Hung, Wen-Chih Peng","doi":"10.1109/ICPP.2010.50","DOIUrl":"https://doi.org/10.1109/ICPP.2010.50","url":null,"abstract":"In recent years, the global position system (GPS) is widely used in technical products, such as navigation devices, GPS loggers, PDAs and mobile phones. Hence, traffic data collection platforms are proposed to collect GPS data points for traffic monitoring. In traffic data collection platforms, each vehicle equips with GPS modules and the wireless communication interfaces, such as 3G or WiFi networks, and the GPS data sensed (e.g., the speed and the position) are sent to the server. One challenge issue is that if a significant number of vehicles upload their GPS data points at the same time, it is possible that the wireless network cannot offer enough network resources for simultaneous network connections. This paper proposes a framework MDC (standing for Model-based Data Collection) to reduce the amount of data transmission and the number of vehicles reporting their GPS data points. The MDC framework is executed at the server and vehicle side collaboratively. In the vehicle side, given a series of GPS data points, model functions are derived to represent the raw GPS data points. Hence, each vehicle could report some coefficients that describe its movements instead of reporting all position information. Since vehicles move along with road segments that are usually a set of line segments, algorithm LR (standing for Liner Regression) is proposed to determine a set of line functions to represent movements of vehicles. By observing the spatial-temporal locality in traffic data, algorithm KR (standing for Kernel Regression) is developed to derive a set of kernel functions to model a series of speed readings sensed. Moreover, with the spatial-temporal locality feature in traffic data, an in-network aggregation mechanism are proposed to determine a set of groups and for each group, only one vehicle needs to report traffic data, thereby further reducing the number of simultaneous connections. Experimental results show that MDC can collect traffic data effectively and the efficiently.","PeriodicalId":180554,"journal":{"name":"2010 39th International Conference on Parallel Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125845235","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: 14

Optimal Overlay Construction on Heterogeneous Live Peer-to-Peer Streaming Systems 异构实时点对点流系统的最优覆盖结构

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.77

Min Yang, Yuanyuan Yang

{"title":"Optimal Overlay Construction on Heterogeneous Live Peer-to-Peer Streaming Systems","authors":"Min Yang, Yuanyuan Yang","doi":"10.1109/ICPP.2010.77","DOIUrl":"https://doi.org/10.1109/ICPP.2010.77","url":null,"abstract":"Media streaming is an important Internet application and has received more and more attention in recent years. Traditional media streaming systems are deployed in a server-client mode which scales poorly with the increasing population of the clients. Peer-to-peer media streaming can greatly enhance the scalability of the system by employing the clients to help forward the media content. In this paper, we consider optimizing the overlay construction for peer-to-peer streaming systems with heterogeneous access link bandwidths. Our goal is to maximize the total downloading rate and satisfy the heterogeneous downloading requirements when the uplink bandwidth is limited. We first formalize it into a problem of finding maximum number of edge disjoint trees in a graph which models the peers and their access link bandwidths. Then we give a centralized heuristic algorithm to solve the problem. Based on the centralized algorithm, we further propose a distributed algorithm which constructs an adaptive overlay topology that can adapt itself to the changing peers such that the end-to-end delay and link stress are minimized. We compare our scheme with another recently proposed scheme called MDM through simulations. Our simulation results show that the proposed scheme outperforms MDM by about 30% with respect to the average peer satisfaction. In addition, the proposed scheme achieves less link stress than MDM.","PeriodicalId":180554,"journal":{"name":"2010 39th International Conference on Parallel Processing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130726922","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: 4

Extending the Monte Carlo Processor Modeling Technique: Statistical Performance Models of the Niagara 2 Processor 扩展蒙特卡罗处理器建模技术:Niagara 2处理器的统计性能模型

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.44

Waleed Alkohlani, Jeanine E. Cook, R. Srinivasan

引用次数: 4

A Machine Learning Approach for Optimizing Parallel Logic Simulation 优化并行逻辑仿真的机器学习方法

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.62

S. Meraji, C. Tropper

引用次数: 6

Efficient Work Stealing for Fine Grained Parallelism 细粒度并行的高效工作窃取

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.39

Karl-Filip Faxén

引用次数: 48

Energy Modeling of Wireless Sensor Nodes Based on Petri Nets 基于Petri网的无线传感器节点能量建模

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.19

Ali Shareef, Yifeng Zhu

引用次数: 33

Distributing a Metric-Space Search Index onto Processors 在处理器上分配度量空间搜索索引

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.51

Mauricio Marín, Flavio Ferrarotti, V. Gil-Costa

引用次数: 16

Designing Power-Aware Collective Communication Algorithms for InfiniBand Clusters InfiniBand集群的功耗感知集体通信算法设计

2010 39th International Conference on Parallel Processing Pub Date : 2010-09-13 DOI: 10.1109/ICPP.2010.78

K. Kandalla, E. Mancini, S. Sur, D. Panda

{"title":"Designing Power-Aware Collective Communication Algorithms for InfiniBand Clusters","authors":"K. Kandalla, E. Mancini, S. Sur, D. Panda","doi":"10.1109/ICPP.2010.78","DOIUrl":"https://doi.org/10.1109/ICPP.2010.78","url":null,"abstract":"Modern supercomputing systems have witnessed a phenomenal growth in the recent history owing to the advent of multi-core architectures and high speed networks. However, the operational and maintenance costs of these systems have also grown rapidly. Several concepts such as Dynamic Voltage and Frequency Scaling (DVFS) and CPU Throttling have been proposed to conserve the power consumed by the compute nodes during idle periods. However, it is necessary to design software stacks in a power-aware manner to minimize the amount of power drawn by the system during the execution of applications. It is also critical to minimize the performance overheads associated with power-aware algorithms, as the benefits of saving power could be lost if the application runs for a longer time. Modern multi-core architectures such as the Intel “Nehalem” allow for DVFS and CPU throttling operations to be performed with little overheads. In this paper, we explore how these features can be leveraged to design algorithms to deliver fine-grained power savings during the communication phases of parallel applications. We also propose a theoretical model to analyze the power consumption characteristics of communication operations. We use microbenchmarks and application benchmarks such as NAS and CPMD to measure the performance of our proposed algorithms and to demonstrate the potential for saving power with 32 and 64 processes. We observe about 8% improvement in the overall energy consumed by these applications with little performance overheads.","PeriodicalId":180554,"journal":{"name":"2010 39th International Conference on Parallel Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115244616","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: 42