{"657233":{"#nid":"657233","#data":{"type":"event","title":"PhD Defense by  Kasimir Georg Gabert","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;Finding Dense Regions of Rapidly Changing Graphs\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate:\u003C\/strong\u003E\u0026nbsp;Thursday, April 21st, 2022\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime:\u003C\/strong\u003E\u0026nbsp;\u003Cstrong\u003E2pm - 4pm\u003C\/strong\u003E EDT\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation (virtual):\u003C\/strong\u003E\u0026nbsp;\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/94304662522\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/94304662522\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EKasimir Georg Gabert\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPhD\u0026nbsp;Candidate\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Computer Science \/ School of Computational Science and Engineering\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECollege of Computing\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/kasimir.co\u0022\u003Ehttps:\/\/kasimir.co\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. \u0026Uuml;mit V. \u0026Ccedil;ataly\u0026uuml;rek (advisor), CSE, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Srinivas Aluru, CSE, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. B. Aditya Prakash, CSE, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Srijan Kumar, CSE, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Ali P\u0131nar, Data Science and Cyber Analytics, Sandia National Laboratories\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMany of today\u0026#39;s massive and rapidly changing graphs contain internal structure---hierarchies of locally dense regions---and finding and tracking this structure is key to detecting emerging behavior, exposing internal activity, summarizing for downstream tasks, identifying important regions, and more.\u0026nbsp; Existing techniques to track these regions fundamentally cannot handle the scale, rate of change, and temporal nature of today\u0026#39;s graphs.\u0026nbsp; We identify the crucial missing piece as the need to address the significant variability in graph change rates, algorithm runtimes, temporal behavior, and dense structures themselves.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe tackle tracking dense regions in three parts.\u0026nbsp; First, we extend algorithms and theory around dense region computation.\u0026nbsp; We computationally unify nuclei into computing hypergraph cores, providing significant improvements over hand-tuned nuclei algorithms and enabling higher-order nuclei.\u0026nbsp; We develop new batch algorithms for maintaining core hierarchies.\u0026nbsp; We then define new temporal dense regions, called core chains, that build on nuclei hierarchy maintenance and enable effective and powerful dense region tracking.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESecond, we scale up on shared-memory systems.\u0026nbsp; We provide a parallel input and output library that reduces start-up costs of all known graph systems.\u0026nbsp; We provide the first parallel scalable core and hypergraph core maintenance algorithms, building on the connection between h-indices and cores.\u0026nbsp; This addresses computation on rapidly changing graphs during bursty periods with large numbers of graph changes.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThird, we address scaling out to support massive graphs.\u0026nbsp; We develop the first parallel h-index algorithm, the key kernel for tracking dense regions.\u0026nbsp; We identify that system elasticity is imperative to handle large bursts of changes.\u0026nbsp; We develop a dynamic and elastic graph system, using consistent hashing and sketches, and demonstrate competitive performance against static, inelastic graph systems while enabling new, dynamic applications.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBy addressing variability directly---in algorithm and system design---we break through previous barriers and bring dense region tracking to massive, rapidly changing graphs.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":" Finding Dense Regions of Rapidly Changing Graphs"}],"uid":"27707","created_gmt":"2022-04-13 12:21:39","changed_gmt":"2022-04-13 12:21:39","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2022-04-21T15:00:00-04:00","event_time_end":"2022-04-21T17:00:00-04:00","event_time_end_last":"2022-04-21T17:00:00-04:00","gmt_time_start":"2022-04-21 19:00:00","gmt_time_end":"2022-04-21 21:00:00","gmt_time_end_last":"2022-04-21 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}