ACM/IEEE SC 2006 Conference (SC'06)最新文献_第5页

High-Performance and Scalable MPI over InfiniBand with Reduced Memory Usage: An In-Depth performance Analysis 通过InfiniBand减少内存使用的高性能和可扩展MPI:深入的性能分析

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188565

S. Sur, Matthew J. Koop, D. Panda

{"title":"High-Performance and Scalable MPI over InfiniBand with Reduced Memory Usage: An In-Depth performance Analysis","authors":"S. Sur, Matthew J. Koop, D. Panda","doi":"10.1145/1188455.1188565","DOIUrl":"https://doi.org/10.1145/1188455.1188565","url":null,"abstract":"InfiniBand is an emerging HPC interconnect being deployed in very large scale clusters, with even larger InfiniBand-based clusters expected to be deployed in the near future. The message passing interface (MPI) is the programming model of choice for scientific applications running on these large scale clusters. Thus, it is very critical for the MPI implementation used to be based on a scalable and high-performance design. We analyze the performance and scalability aspects of MVAPICH, a popular open-source MPI implementation on InfiniBand, from an application standpoint. We analyze the performance and memory requirements of the MPI library while executing several well-known applications and benchmarks, such as NAS, SuperLU, NAMD, and HPL on a 64-node InfiniBand cluster. Our analysis reveals that latest design of MVAPICH requires an order of magnitude less internal MPI memory (average per process) and yet delivers the best possible performance. Further, we observe that for these benchmarks and applications evaluated, the internal memory requirement of MVAPICH remains nearly constant at around 5-10 MB as the number of processes increase, indicating that the MVAPICH design is highly scalable","PeriodicalId":333909,"journal":{"name":"ACM/IEEE SC 2006 Conference (SC'06)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130761396","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: 60

Blue Matter: Approaching the Limits of Concurrency for Classical Molecular Dynamics 蓝物质:接近经典分子动力学并发性的极限

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188547

B. Fitch, A. Rayshubskiy, M. Eleftheriou, T. Ward, M. Giampapa, M. Pitman, R. Germain

引用次数: 55

Evaluation of a Workflow Scheduler Using Integrated Performance Modelling and Batch Queue Wait Time Prediction 基于集成性能建模和批处理队列等待时间预测的工作流调度程序评估

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188579

Daniel Nurmi, A. Mandal, J. Brevik, C. Koelbel, R. Wolski, K. Kennedy

{"title":"Evaluation of a Workflow Scheduler Using Integrated Performance Modelling and Batch Queue Wait Time Prediction","authors":"Daniel Nurmi, A. Mandal, J. Brevik, C. Koelbel, R. Wolski, K. Kennedy","doi":"10.1145/1188455.1188579","DOIUrl":"https://doi.org/10.1145/1188455.1188579","url":null,"abstract":"Large-scale distributed systems offer computational power at unprecedented levels. In the past, HPC users typically had access to relatively few individual supercomputers and, in general, would assign a one-to-one mapping of applications to machines. Modern HPC users have simultaneous access to a large number of individual machines and are beginning to make use of all of them for single-application execution cycles. One method that application developers have devised in order to take advantage of such systems is to organize an entire application execution cycle as a workflow. The scheduling of such workflows has been the topic of a great deal of research in the past few years and, although very sophisticated algorithms have been devised, a very specific aspect of these distributed systems, namely that most supercomputing resources employ batch queue scheduling software, has therefore been omitted from consideration, presumably because it is difficult to model accurately. In this work, we augment an existing workflow scheduler through the introduction of methods which make accurate predictions of both the performance of the application on specific hardware, and the amount of time individual workflow tasks would spend waiting in batch queues. Our results show that although a workflow scheduler alone may choose correct task placement based on data locality or network connectivity, this benefit is often compromised by the fact that most jobs submitted to current systems must wait in overcommitted batch queues for a significant portion of time. However, incorporating the enhancements we describe improves workflow execution time in settings where batch queues impose significant delays on constituent workflow tasks","PeriodicalId":333909,"journal":{"name":"ACM/IEEE SC 2006 Conference (SC'06)","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122515577","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: 70

A Memory Model for Scientific Algorithms on Graphics Processors 图形处理器上科学算法的内存模型

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188549

N. Govindaraju, S. Larsen, J. Gray, Dinesh Manocha

引用次数: 211

Toward Real-Time Image Guided Neurosurgery Using Distributed and Grid Computing 利用分布式和网格计算实现实时图像引导神经外科

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188536

N. Chrisochoides, Andrey Fedorov, A. Kot, N. Archip, P. Black, O. Clatz, A. Golby, R. Kikinis, S. Warfield

{"title":"Toward Real-Time Image Guided Neurosurgery Using Distributed and Grid Computing","authors":"N. Chrisochoides, Andrey Fedorov, A. Kot, N. Archip, P. Black, O. Clatz, A. Golby, R. Kikinis, S. Warfield","doi":"10.1145/1188455.1188536","DOIUrl":"https://doi.org/10.1145/1188455.1188536","url":null,"abstract":"Neurosurgical resection is a therapeutic intervention in the treatment of brain tumors. Precision of the resection can be improved by utilizing magnetic resonance imaging (MRI) as an aid in decision making during image guided neurosurgery (IGNS). Image registration adjusts pre-operative data according to intra-operative tissue deformation. Some of the approaches increase the registration accuracy by tracking image landmarks through the whole brain volume. High computational cost used to render these techniques inappropriate for clinical applications. In this paper we present a parallel implementation of a state of the art registration method, and a number of needed incremental improvements. Overall, we reduced the response time for registration of an average dataset from about an hour and for some cases more than an hour to less than seven minutes, which is within the time constraints imposed by neurosurgeons. For the first time in clinical practice we demonstrated, that with the help of distributed computing non-rigid MRI registration based on volume tracking can be computed intra-operatively","PeriodicalId":333909,"journal":{"name":"ACM/IEEE SC 2006 Conference (SC'06)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130255700","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: 57

End-System Aware, Rate-Adaptive Protocol for Network Transport in LambdaGrid Environments 面向终端系统的低速网格网络传输速率自适应协议

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188572

P. Datta, W. Feng, Sushant Sharma

引用次数: 6

Architectures and APIs: Assessing Requirements for Delivering FPGA Performance to Applications 架构和api:评估向应用交付FPGA性能的需求

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188571

K. Underwood, K. Hemmert, C. Ulmer

引用次数: 30

Designing a Highly-Scalable Operating System: The Blue Gene/L Story 设计一个高度可扩展的操作系统:蓝色基因/L的故事

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188578

José E. Moreira, Michael Brutman, J. Castaños, Thomas Engelsiepen, M. Giampapa, Thomas Gooding, R. Haskin, T. Inglett, D. Lieber, P. McCarthy, M. Mundy, Jeff Parker, Brian P. Wallenfelt

引用次数: 66

Toward a Doctrine of Containment: Grid Hosting with Adaptive Resource Control 迈向遏制原则:网格托管与自适应资源控制

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188561

L. Ramakrishnan, David E. Irwin, Laura E. Grit, Aydan R. Yumerefendi, Adriana Iamnitchi, J. Chase

引用次数: 71

Evaluating Grid Portal Security 评估网格门户的安全性

ACM/IEEE SC 2006 Conference (SC'06) Pub Date : 2006-11-11 DOI: 10.1145/1188455.1188574

D. Vecchio, Victor Hazlewood, M. Humphrey

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引用次数: 19