2012 International Conference for High Performance Computing, Networking, Storage and Analysis最新文献_第4页

MCREngine: A scalable checkpointing system using data-aware aggregation and compression mcreengine:使用数据感知聚合和压缩的可伸缩检查点系统

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.3233/SPR-130371

T. Islam, K. Mohror, S. Bagchi, A. Moody, B. Supinski, R. Eigenmann

引用次数: 86

Optimizing the computation of n-point correlations on large-scale astronomical data 大规模天文数据n点关联计算的优化

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.89

William B. March, Kenneth Czechowski, Marat Dukhan, T. Benson, Dongryeol Lee, A. Connolly, R. Vuduc, Edmond Chow, Alexander G. Gray

引用次数: 11

Design and analysis of data management in scalable parallel scripting 设计和分析可扩展并行脚本中的数据管理

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.44

Zhao Zhang, D. Katz, J. Wozniak, Allan Espinosa, Ian T Foster

引用次数: 31

Scalable multi-GPU 3-D FFT for TSUBAME 2.0 Supercomputer 用于TSUBAME 2.0超级计算机的可扩展多gpu三维FFT

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.100

Akira Nukada, Kento Sato, S. Matsuoka

引用次数: 39

Portable section-level tuning of compiler parallelized applications 编译器并行化应用程序的可移植分段级调优

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.97

Dheya Ghazi Mustafa, R. Eigenmann

引用次数: 8

Classifying soft error vulnerabilities in extreme-Scale scientific applications using a binary instrumentation tool 利用二进制检测工具对极端规模科学应用中的软错误漏洞进行分类

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.5555/2388996.2389074

Dong Li, J. Vetter, Weikuan Yu

{"title":"Classifying soft error vulnerabilities in extreme-Scale scientific applications using a binary instrumentation tool","authors":"Dong Li, J. Vetter, Weikuan Yu","doi":"10.5555/2388996.2389074","DOIUrl":"https://doi.org/10.5555/2388996.2389074","url":null,"abstract":"Extreme-scale scientific applications are at a significant risk of being hit by soft errors on supercomputers as the scale of these systems and the component density continues to increase. In order to better understand the specific soft error vulnerabilities in scientific applications, we have built an empirical fault injection and consequence analysis tool - BIFIT -that allows us to evaluate how soft errors impact applications. In particular, BIFIT is designed with capability to inject faults at very specific targets: an arbitrarily-chosen execution point and any specific data structure. We apply BIFIT to three mission-critical scientific applications and investigate the applications vulnerability to soft errors by performing thousands of statistical tests. We, then, classify each applications individual data structures based on their sensitivity to these vulnerabilities, and generalize these classifications across applications. Subsequently, these classifications can be used to apply appropriate resiliency solutions to each data structure within an application. Our study reveals that these scientific applications have a wide range of sensitivities to both the time and the location of a soft error; yet, we are able to identify intrinsic relationships between application vulnerabilities and specific types of data objects. In this regard, BIFIT enables new opportunities for future resiliency research.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114511216","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: 120

A parallel two-level preconditioner for Cosmic Microwave Background map-making 宇宙微波背景图制作的平行两级预处理

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.10

L. Grigori, R. Stompor, M. Szydlarski

{"title":"A parallel two-level preconditioner for Cosmic Microwave Background map-making","authors":"L. Grigori, R. Stompor, M. Szydlarski","doi":"10.1109/SC.2012.10","DOIUrl":"https://doi.org/10.1109/SC.2012.10","url":null,"abstract":"Generalized least square problems with nondiagonal weights arise frequently in an estimation of two dimensional images from data of cosmological as well as astro- or geo- physical observations. As the observational data sets keep growing at Moore's rate, with their volumes exceeding tens and hundreds billions of samples, the need for fast and efficiently parallelizable iterative solvers is generally recognized. In this work we propose a new iterative algorithm for solving generalized least square systems with weights given by a blockdiagonal matrix with Toeplitz blocks. Such cases are physically well motivated and correspond to measurement noise being piece-wise stationary - a common occurrence in many actual observations. Our iterative algorithm is based on the conjugate gradient method and includes a parallel two-level preconditioner (2lvl-PCG) constructed from a limited number of sparse vectors estimated from the coefficients of the initial linear system. Our prototypical application is the map-making problem in the Cosmic Microwave Background data analysis. We show experimentally that our parallel implementation of 2lvl-PCG outperforms by a factor of up to 6 the standard one-level PCG in terms of both the convergence rate and the time to solution on up to 12, 228 cores of NERSC's Cray XE6 (Hopper) system displaying nearly perfect strong and weak scaling behavior in this regime.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116182828","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

Fault prediction under the microscope: A closer look into HPC systems 显微镜下的故障预测:对高性能计算系统的深入研究

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.57

Ana Gainaru, F. Cappello, M. Snir, W. Kramer

{"title":"Fault prediction under the microscope: A closer look into HPC systems","authors":"Ana Gainaru, F. Cappello, M. Snir, W. Kramer","doi":"10.1109/SC.2012.57","DOIUrl":"https://doi.org/10.1109/SC.2012.57","url":null,"abstract":"A large percentage of computing capacity in today's large high-performance computing systems is wasted because of failures. Consequently current research is focusing on providing fault tolerance strategies that aim to minimize fault's effects on applications. By far the most popular technique is the checkpointrestart strategy. A complement to this classical approach is failure avoidance, by which the occurrence of a fault is predicted and preventive measures are taken. This requires a reliable prediction system to anticipate failures and their locations. Thus far, research in this field has used ideal predictors that were not implemented in real HPC systems. In this paper, we merge signal analysis concepts with data mining techniques to extend the ELSA (Event Log Signal Analyzer) toolkit and offer an adaptive and more efficient prediction module. Our goal is to provide models that characterize the normal behavior of a system and the way faults affect it. Being able to detect deviations from normality quickly is the foundation of accurate fault prediction. However, this is challenging because component failure dynamics are heterogeneous in space and time. To this end, a large part of the paper is focused on a detailed analysis of the prediction method, by applying it to two large-scale systems and by investigating the characteristics and bottlenecks of each step of the prediction process. Furthermore, we analyze the prediction's precision and recall impact on current checkpointing strategies and highlight future improvements and directions for research in this field.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121701878","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: 131

Early evaluation of directive-based GPU programming models for productive exascale computing 用于百亿亿次计算的基于指令的GPU编程模型的早期评估

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.51

Seyong Lee, J. Vetter

{"title":"Early evaluation of directive-based GPU programming models for productive exascale computing","authors":"Seyong Lee, J. Vetter","doi":"10.1109/SC.2012.51","DOIUrl":"https://doi.org/10.1109/SC.2012.51","url":null,"abstract":"Graphics Processing Unit (GPU)-based parallel computer architectures have shown increased popularity as a building block for high performance computing, and possibly for future Exascale computing. However, their programming complexity remains as a major hurdle for their widespread adoption. To provide better abstractions for programming GPU architectures, researchers and vendors have proposed several directive-based GPU programming models. These directive-based models provide different levels of abstraction, and required different levels of programming effort to port and optimize applications. Understanding these differences among these new models provides valuable insights on their applicability and performance potential. In this paper, we evaluate existing directive-based models by porting thirteen application kernels from various scientific domains to use CUDA GPUs, which, in turn, allows us to identify important issues in the functionality, scalability, tunability, and debuggability of the existing models. Our evaluation shows that directive-based models can achieve reasonable performance, compared to hand-written GPU codes.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125628541","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: 80

Optimizing fine-grained communication in a biomolecular simulation application on Cray XK6 在Cray XK6上优化生物分子模拟应用程序中的细粒度通信

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.87

Yanhua Sun, G. Zheng, Chao Mei, Eric J. Bohm, James C. Phillips, Laximant V. Kalé, T. Jones

引用次数: 32