{"646728":{"#nid":"646728","#data":{"type":"event","title":"PhD Defense by Joshua Kimball","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp;\u003C\/strong\u003EPerfDB + PerfML: Enabling Big Data-Driven Research on Fine-Grained Performance Phenomena\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EJoshua Kimball\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPh.D. Candidate\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Computer Science\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\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate:\u003C\/strong\u003E May 5, 2021\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime: \u003C\/strong\u003E1:00 PM to 3:00PM EDT\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E Online (Bluejeans)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E-------------\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EMeeting URL \u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E\u003Ca href=\u0022https:\/\/bluejeans.com\/857372648\u0022\u003Ehttps:\/\/bluejeans.com\/857372648\u003C\/a\u003E\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EMeeting ID\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E857 372 648\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EWant to dial in from a phone?\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EDial one of the following numbers:\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E+1.408.419.1715 (United States(San Jose))\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E+1.408.915.6290 (United States(San Jose))\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E(see all numbers - \u003Ca href=\u0022https:\/\/www.bluejeans.com\/numbers\u0022\u003Ehttps:\/\/www.bluejeans.com\/numbers\u003C\/a\u003E)\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EEnter the meeting ID and passcode followed by #\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EConnecting from a room system?\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EDial: bjn.vc or 199.48.152.152 and enter your meeting ID \u0026amp; passcode\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003E-------------\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\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\u003EDr. Calton Pu (Advisor) - School of Computer Science, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Arulraj Joy - School of Computer Science, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Ling Liu - School of Computer Science, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Sham Navathe - School of Computer Science, Georgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Qingyang Wang - School of Computer Science, Louisiana State University\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\u003EThe long-tail latency problem is a well-known problem in large-scale system topologies like cloud platforms. Long-tail latency can lead to less predictable system performance, degraded quality of experience and potential economic loss. Previous research has focused on coarse-grained, symptomatic treatments like redundant request executions to mitigate tail latency and its effects. Instead, we propose studying these performance bugs systematically and addressing their underlying root cause.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe millibottleneck theory of performance bugs provides a testable hypothesis for explaining at least some requests comprising the latency long tail. The theory posits that transient performance anomalies cause a non-negligible number of requests to complete in seconds, called Very Long Response Time Requests (VLRT), instead of tens of milliseconds like the vast majority of other requests.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn this dissertation, we enable the systematic evaluation of the millibottleneck theory across a big data-scale experimental data collection. First, we present perftables, a performance log parser, that extracts resource monitoring data across a wide variety of hardware and software configurations. Secondly, we use our data management system, PerfDB, to load and integrate fine-grained system performance data from approximately 400 experiments. We conduct the first-generation population study of VLRT, and our data support millibottlenecks inducing VLRT through CTQO (Cross-Tier Queue Overflow). We also enable the study of a second latency class called Less Long Requests (LLRs). Finally, we present our ensemble-based, supervised machine learning system, PerfML, that handles data characterized by heterogenous feature space and hierarchical, imbalanced classes\u0026mdash;characteristics inherent to the data needed to study millibottlenecks and latency performance bugs. The analytics results from PerfML demonstrate its ability to isolate different kinds of millibottlenecks across a range of systems and configurations with high recall and acceptable precision.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"PerfDB + PerfML: Enabling Big Data-Driven Research on Fine-Grained Performance Phenomena"}],"uid":"27707","created_gmt":"2021-04-21 19:07:41","changed_gmt":"2021-04-21 19:07:41","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-05-05T14:00:00-04:00","event_time_end":"2021-05-05T16:00:00-04:00","event_time_end_last":"2021-05-05T16:00:00-04:00","gmt_time_start":"2021-05-05 18:00:00","gmt_time_end":"2021-05-05 20:00:00","gmt_time_end_last":"2021-05-05 20:00:00","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":""}}}