{"title":"Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis","authors":"Scott A. Lathrop, J. Costa, W. Kramer","doi":"10.1145/2063384","DOIUrl":"https://doi.org/10.1145/2063384","url":null,"abstract":"","PeriodicalId":199020,"journal":{"name":"Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"286 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123071511","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}
{"title":"Analyst Crossfire","authors":"Peter J. Ungaro, Donald Becker, E. Dodd, K. Gray","doi":"10.1145/2063384.2134409","DOIUrl":"https://doi.org/10.1145/2063384.2134409","url":null,"abstract":"","PeriodicalId":199020,"journal":{"name":"Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133843023","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}
{"title":"SC 2011 Keynote","authors":"Jen-Hsun Huang","doi":"10.1145/2063384.2070751","DOIUrl":"https://doi.org/10.1145/2063384.2070751","url":null,"abstract":"The supercomputing industry is in a global race for better science. This race has some parallels to the space race in the 1960s. Much like then, today there are daunting challenges facing today's supercomputer designers in their pursuit of exascale and advanced computational science; in particular power, programmability, and scalability. Mr. Huang will share his perspective on these challenges as they pertain to developers, scientists, and the industry overall. An update on recent technical and scientific milestones in parallel computing and an assessment of new, disruptive technologies from outside the supercomputing industry will be given.","PeriodicalId":199020,"journal":{"name":"Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131497266","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}
{"title":"A distributed look-up architecture for text mining applications using MapReduce","authors":"A. S. Balkir, Ian T Foster, A. Rzhetsky","doi":"10.1145/2063384.2063463","DOIUrl":"https://doi.org/10.1145/2063384.2063463","url":null,"abstract":"We study text analysis algorithms that use global optimization methods to compute local characteristics that are consistent with properties of the entire corpus rather than computed locally based on exogenous parameters. In the iterative implementations that we consider, each step both reads and updates a database of parameter values. Motivated by a need for rapid analysis of large corpora, we have developed methods for efficient access to such databases on parallel computers. These methods combine Bloom filters, in-memory caches, and an HBase cluster to reduce communication costs greatly relative to simpler approaches that either fully distribute or fully replicate the database. We also describe how this method can be incorporated into the MapReduce programming model, and illustrate its use within phrase segmentation programs. Our design can achieve considerable run time, latency and storage space improvements relative to other methods. In one phrase segmentation application, we improve performance by a factor of six relative to an HBase-based implementation.","PeriodicalId":199020,"journal":{"name":"Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124138469","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}