2012 SC Companion: High Performance Computing, Networking Storage and Analysis最新文献_第8页

Abstract: MemzNet: Memory-Mapped Zero-Copy Network Channel for Moving Large Datasets over 100Gbps Network MemzNet:内存映射零拷贝网络通道，用于在100Gbps网络上移动大数据集

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.294

Mehmet Balman

引用次数: 2

FRIEDA: Flexible Robust Intelligent Elastic Data Management in Cloud Environments FRIEDA:云环境中灵活稳健的智能弹性数据管理

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.132

D. Ghoshal, L. Ramakrishnan

引用次数: 18

Poster: Bringing Task and Data Parallelism to Analysis of Climate Model Output 海报:将任务和数据并行性引入气候模式输出分析

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.283

R. Jacob, Jayesh Krishna, Xiabing Xu, S. Mickelson, T. Tautges, M. Wilde, R. Latham, Ian T Foster, R. Ross, M. Hereld, J. Larson, P. Bochev, K. Peterson, M. Taylor, K. Schuchardt, Jain Yin, D. Middleton, Mary Haley, David Brown, Wei Huang, D. Shea, R. Brownrigg, M. Vertenstein, K. Ma, Jingrong Xie

{"title":"Poster: Bringing Task and Data Parallelism to Analysis of Climate Model Output","authors":"R. Jacob, Jayesh Krishna, Xiabing Xu, S. Mickelson, T. Tautges, M. Wilde, R. Latham, Ian T Foster, R. Ross, M. Hereld, J. Larson, P. Bochev, K. Peterson, M. Taylor, K. Schuchardt, Jain Yin, D. Middleton, Mary Haley, David Brown, Wei Huang, D. Shea, R. Brownrigg, M. Vertenstein, K. Ma, Jingrong Xie","doi":"10.1109/SC.Companion.2012.283","DOIUrl":"https://doi.org/10.1109/SC.Companion.2012.283","url":null,"abstract":"Climate models are both outputting larger and larger amounts of data and are doing it on more sophisticated numerical grids. The tools climate scientists have used to analyze climate output, an essential component of climate modeling, are single threaded and assume rectangular structured grids in their analysis algorithms. We are bringing both task- and data-parallelism to the analysis of climate model output. We have created a new data-parallel library, the Parallel Gridded Analysis Library (ParGAL) which can read in data using parallel I/O, store the data on a compete representation of the structured or unstructured mesh and perform sophisticated analysis on the data in parallel. ParGAL has been used to create a parallel version of a script-based analysis and visualization package. Finally, we have also taken current workflows and employed task-based parallelism to decrease the total execution time.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"12 1","pages":"1495"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76674227","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

New ASHRAE Thermal Guidelines for Air and Liquid Cooling 新的ASHRAE空气和液体冷却热指南

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.122

M. Ellsworth

引用次数: 1

An Evolutionary Path to Object Storage Access 对象存储访问的进化路径

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.17

David Goodell, S. Kim, R. Latham, M. Kandemir, R. Ross

{"title":"An Evolutionary Path to Object Storage Access","authors":"David Goodell, S. Kim, R. Latham, M. Kandemir, R. Ross","doi":"10.1109/SC.Companion.2012.17","DOIUrl":"https://doi.org/10.1109/SC.Companion.2012.17","url":null,"abstract":"High-performance computing (HPC) storage systems typically consist of an object storage system that is accessed via the POSIX file interface. However, rapid increases in system scales and storage system complexity have uncovered a number of limitations in this model. In particular, applications and libraries are limited in their ability to partition data into units with independent concurrency control, and mapping complex science data models into the POSIX file model is inconvenient at best. In this paper we propose an alternative interface for use by applications and libraries that provides direct access to underlying storage objects. This model allows applications and libraries to organize storage access around these objects in order to avoid lock contention without needing to create many separate files. Additionally, complex data models are more readily organized into multiple object data streams, simplifying the storage of variable-length data and allowing a choice of degree of parallelism related to access needs. Our approach provides for datasets stored in this new model to coexist with POSIX files, allowing evolution to the new model over time. We apply these concepts in the PVFS, PLFS, and Parallel netCDF packages to prototype the model and describe our experiences.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"108 1","pages":"36-41"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74661813","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

Array Databases 数组的数据库

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.365

P. Baumann

引用次数: 8

Understanding Cloud Data Using Approximate String Matching and Edit Distance 使用近似字符串匹配和编辑距离理解云数据

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.149

Joseph Jupin, Justin Y. Shi, Z. Obradovic

{"title":"Understanding Cloud Data Using Approximate String Matching and Edit Distance","authors":"Joseph Jupin, Justin Y. Shi, Z. Obradovic","doi":"10.1109/SC.Companion.2012.149","DOIUrl":"https://doi.org/10.1109/SC.Companion.2012.149","url":null,"abstract":"For health and human services, fraud detection and other security services, identity resolution is a core requirement for understanding big data in the cloud. Due to the lack of a globally unique identifier and captured typographic differences for the same identity, identity resolution has high spatial and temporal complexities. We propose a filter and verify method to substantially increase the speed of approximate string matching using edit distance. This method has been found to be almost 80 times faster (130 times when combined with other optimizations) than Damerau-Levenshtein edit distance and preserves all approximate matches. Our method creates compressed signatures for data fields and uses Boolean operations and an enhanced bit counter to quickly compare the distance between the fields. This method is intended to be applied to data records whose fields contain relatively short-length strings, such as those found in most demographic data. Without loss of accuracy, the proposed Fast Bitwise Filter will provide substantial performance gain to approximate string comparison in database, record linkage and deduplication data processing systems.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"59 1","pages":"1234-1243"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73140971","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

Scalable Cyber-Security for Terabit Cloud Computing 太比特云计算的可扩展网络安全

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.338

Jordi Ros-Giralt, Péter Szilágyi, R. Lethin

{"title":"Scalable Cyber-Security for Terabit Cloud Computing","authors":"Jordi Ros-Giralt, Péter Szilágyi, R. Lethin","doi":"10.1109/SC.Companion.2012.338","DOIUrl":"https://doi.org/10.1109/SC.Companion.2012.338","url":null,"abstract":"This paper addresses the problem of scalable cyber-security using a cloud computing architecture. Scalability is treated in two contexts: (1) performance and power efficiency and (2) degree of cyber security-relevant information detected by the cyber-security cloud (CSC). We provide a framework to construct CSCs, which derives from a set of fundamental building blocks (forwarders, analyzers and grounds) and the identification of the smallest functional units (atomic CSC cells or simply aCS C cells) capable of embedding the full functionality of the cyber-security cloud. aCSC cells are then studied and several high-performance algorithms are presented to optimize the system's performance and power efficiency. Among these, a new queuing policy - called tail early detection (TED) - is introduced to proactively drop packets in a way that the degree of detected information is maximized while saving power by avoiding spending cycles on less relevant traffic components. We also show that it is possible to use aCSC cells as core building blocks to construct arbitrarily large cyber-security clouds by structuring the cells using a hierarchical architecture. To demonstrate the utility of our framework, we implement one cyber-security \"mini-cloud\" on a single chip prototype based on the Tilera's TILEPro64 processor demonstrating performance of up to 10Gbps.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"1 1","pages":"1607-1616"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76311938","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: 2

Poster: Numeric Based Ordering for Preconditioned Conjugate Gradient 海报:预条件共轭梯度的基于数值的排序

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.309

J. Booth

引用次数: 1

DS-CUDA: A Middleware to Use Many GPUs in the Cloud Environment DS-CUDA:在云环境中使用多个gpu的中间件

2012 SC Companion: High Performance Computing, Networking Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.Companion.2012.146

Minoru Oikawa, A. Kawai, K. Nomura, K. Yasuoka, Kazuyuki Yoshikawa, T. Narumi

{"title":"DS-CUDA: A Middleware to Use Many GPUs in the Cloud Environment","authors":"Minoru Oikawa, A. Kawai, K. Nomura, K. Yasuoka, Kazuyuki Yoshikawa, T. Narumi","doi":"10.1109/SC.Companion.2012.146","DOIUrl":"https://doi.org/10.1109/SC.Companion.2012.146","url":null,"abstract":"GPGPU (General-purpose computing on graphics processing units) has several difficulties when used in cloud environment, such as narrow bandwidth, higher cost, and lower security, compared with computation using only CPUs. Most high performance computing applications require huge communication between nodes, and do not fit a cloud environment, since network topology and its bandwidth are not fixed and they affect the performance of the application program. However, there are some applications for which little communication is needed, such as molecular dynamics (MD) simulation with the replica exchange method (REM). For such applications, we propose DS-CUDA (Distributed-shared compute unified device architecture), a middleware to use many GPUs in a cloud environment with lower cost and higher security. It virtualizes GPUs in a cloud such that they appear to be locally installed GPUs in a client machine. Its redundant mechanism ensures reliable calculation with consumer GPUs, which reduce the cost greatly. It also enhances the security level since no data except command and data for GPUs are stored in the cloud side. REM-MD simulation with 64 GPUs showed 58 and 36 times more speed than a locally-installed GPU via InfiniBand and the Internet, respectively.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"132 1","pages":"1207-1214"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80011066","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: 73