Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556)最新文献

Linear algebra algorithms in a heterogeneous cluster of personal computers 个人计算机异构集群中的线性代数算法

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843740

Jorge G. Barbosa, J. Tavares, A. J. Padilha

引用次数: 47

MoBiDiCK: a tool for distributed computing on the Internet MoBiDiCK:一个在互联网上进行分布式计算的工具

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843755

M. Dharsee, C. Hogue

引用次数: 5

A cost/benefit model for dynamic resource sharing 动态资源共享的成本/收益模型

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843753

D. Katramatos, D. Saxena, Nehal Mehta, S. Chapin

引用次数: 5

Agent-based resource discovery 基于代理的资源发现

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843731

K. Jun, Ladislau Bölöni, K. Palacz, D. Marinescu

引用次数: 66

Cluster performance and the implications for distributed, heterogeneous grid performance 集群性能及其对分布式异构网格性能的影响

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843749

Craig A. Lee, C. DeMatteis, J. Stepanek, John Wang

{"title":"Cluster performance and the implications for distributed, heterogeneous grid performance","authors":"Craig A. Lee, C. DeMatteis, J. Stepanek, John Wang","doi":"10.1109/HCW.2000.843749","DOIUrl":"https://doi.org/10.1109/HCW.2000.843749","url":null,"abstract":"Examines the issues surrounding efficient execution in heterogeneous grid environments. The performances of a Linux cluster and a parallel supercomputer are initially compared using both benchmarks and an application. With an understanding of how benchmark and application performance is affected by processor and interconnect speed, a comparison is made with the bandwidth and latencies available in a tested grid. Of significant concern is the fact that the available communication bandwidth and latencies have a dynamic range of 3 to 4 orders of magnitude, while processor speeds have a range of about one-half order of magnitude. Also, while both processor speed and network bandwidth are increasing very rapidly, simple propagation delay will become more significant in the network latencies seen by many grid applications. That is to say, the pipes in a grid will be getting fatter but not commensurately shorter. How are we to effectively utilize such an infrastructure? Clearly, an attractive approach is to require sufficient concurrency in the application such that a coarse-grain, data-driven model of execution can be used to hide latencies while hopefully keeping context-switching overheads low. If the \"spatial component\" of an application is understood, then runtime systems could also apply established techniques like caching, compression, estimation and speculative pre-fetching. Ideally, this low-level performance management should be encapsulated in an easy-to-use abstraction.","PeriodicalId":351836,"journal":{"name":"Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556)","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123011294","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: 7

Task execution time modeling for heterogeneous computing systems 异构计算系统的任务执行时间建模

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843743

Shoukat Ali, H. Siegel, Muthucumaru Maheswaran, D. Hensgen, Sahra Ali

{"title":"Task execution time modeling for heterogeneous computing systems","authors":"Shoukat Ali, H. Siegel, Muthucumaru Maheswaran, D. Hensgen, Sahra Ali","doi":"10.1109/HCW.2000.843743","DOIUrl":"https://doi.org/10.1109/HCW.2000.843743","url":null,"abstract":"A distributed heterogeneous computing (HC) system consists of diversely capable machines harnessed together to execute a set of tasks that vary in their computational requirements. Heuristics are needed to map (match and schedule) tasks onto machines in an HC system so as to optimize some figure of merit. This paper characterizes a simulated HC environment by using the expected execution times of the tasks that arrive in the system onto the different machines present in the system. This information is arranged in an \"expected time to compute\" (ETC) matrix as a model of the given HC system, where the entry (i, j) is the expected execution time of task i on machine j. This model is needed to simulate different HC environments to allow testing of relative performance of different mapping heuristics under different circumstances. In particular the ETC model is used to express the heterogeneity among the runtimes of the tasks to be executed, and among the machines in the HC system. An existing range-based technique to generate ETC matrices is described. A coefficient-of-variation based technique to generate ETC matrices is proposed, and compared with the range-based technique. The coefficient-of-variation-based ETC generation method provides a greater control over the spread of values (i.e., heterogeneity) in any given row or column of the ETC matrix than the range-based method.","PeriodicalId":351836,"journal":{"name":"Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132624648","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: 249

Reliable cluster computing with a new checkpointing RAID-x architecture 可靠的集群计算与一个新的检查点RAID-x架构

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843742

K. Hwang, Hai Jin, Roy S. C. Ho, Wonwoo Ro

引用次数: 13

The NRW-Metacomputer - building blocks for a worldwide computational grid nrw -元计算机-全球计算网格的构建模块

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843730

Claus Bitten, J. Gehring, U. Schwiegelshohn, R. Yahyapour

引用次数: 16

Master/slave computing on the Grid 网格上的主/从计算

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843728

Gary Shao, F. Berman, R. Wolski

引用次数: 133

Combining workstations and supercomputers to support grid applications: the parallel tomography experience 结合工作站和超级计算机来支持网格应用:并行断层扫描体验

Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556) Pub Date : 2000-05-01 DOI: 10.1109/HCW.2000.843748

Shava Smallen, W. Cirne, J. Frey, F. Berman, R. Wolski, Mei-Hui Su, C. Kesselman, S. Young, Mark Ellisman

{"title":"Combining workstations and supercomputers to support grid applications: the parallel tomography experience","authors":"Shava Smallen, W. Cirne, J. Frey, F. Berman, R. Wolski, Mei-Hui Su, C. Kesselman, S. Young, Mark Ellisman","doi":"10.1109/HCW.2000.843748","DOIUrl":"https://doi.org/10.1109/HCW.2000.843748","url":null,"abstract":"Computational grids are becoming an increasingly important and powerful platform for the execution of large-scale, resource-intensive applications. However, it remains a challenge for applications to tap into the potential of grid resources in order to achieve performance. In this paper, we illustrate how work queue applications can leverage grids to achieve performance through coallocation. We describe our experiences in developing a scheduling strategy for a production tomography application targeted at grids that contain both workstations and parallel supercomputers. Our strategy uses dynamic information exported by a supercomputer's batch scheduler to simultaneously schedule tasks on workstations and immediately-available supercomputer nodes. This strategy is of great practical interest because it combines resources that are available in a typical research laboratory: time-shared workstations and CPU time in remote space-shared supercomputers. We show that this strategy improves the performance of the tomography application compared to traditional scheduling strategies, which target the application to either type of resource alone.","PeriodicalId":351836,"journal":{"name":"Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129139983","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: 77