{"641349":{"#nid":"641349","#data":{"type":"event","title":"PhD Proposal by Joshua Kimball","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPerfDB + PerfML: Supporting 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. Student in Computer Science\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Computer Science\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 November 20, 2020\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime: \u003C\/strong\u003E10:00 AM to 12:00PM EST\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E \u003Ca href=\u0022https:\/\/bluejeans.com\/287403017\u0022\u003Ehttps:\/\/bluejeans.com\/287403017\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E**Note: this proposal is remote-only. complete meeting info. below.**\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. Arulaj 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-documented problem in large-scale system topologies like cloud platforms. Long-tail latency can lead to degraded quality of experience, potential economic loss and less predictable system performance overall. In the past, platforms have over-provisioned to mitigate tail latency and its effects. Instead, we propose studying these performance bugs systematically and addressing their underlying root cause. In this proposal, we present the first-generation population study of VLRT requests using PerfDB, our data management system. Specifically, we present the first study of VLRT periods on integrated data from 500 experiments. We find evidence that many VLRT coincide with Cross-Tier Queue Overflow (CTQO) induced by millibottlenecks. In our second analysis, we conduct the first study of a phenomenon called Localized Latency Requests (LLR)\u0026mdash;requests with latency between 100-500ms. Finally, we propose a machine learning system, PerfML, which employs a teamed-classifier method to automatically isolate and diagnose fine-grained performance anomalies found in a collection of fine-grained (sampling at 50ms intervals) resource monitoring data covering a wide variety of hardware and software configurations spanning hundreds of experiments and terabytes of experimental data.\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E-----------------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMeeting URL\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/bluejeans.com\/287403017\u0022\u003Ehttps:\/\/bluejeans.com\/287403017\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMeeting ID\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E287 403 017\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWant to dial in from a phone?\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDial one of the following numbers:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E+1.408.419.1715 (United States(San Jose))\u003C\/p\u003E\r\n\r\n\u003Cp\u003E+1.408.915.6290 (United States(San Jose))\u003C\/p\u003E\r\n\r\n\u003Cp\u003E(see all numbers - \u003Ca href=\u0022https:\/\/www.bluejeans.com\/numbers\u0022\u003Ehttps:\/\/www.bluejeans.com\/numbers\u003C\/a\u003E)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEnter the meeting ID and passcode followed by #\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EConnecting from a room system?\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDial: bjn.vc or 199.48.152.152 and enter your meeting ID \u0026amp; passcode\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"PerfDB + PerfML: Supporting Big Data-Driven Research on Fine-Grained Performance Phenomena"}],"uid":"27707","created_gmt":"2020-11-16 18:05:05","changed_gmt":"2020-11-16 18:05:05","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2020-11-20T10:00:00-05:00","event_time_end":"2020-11-20T12:00:00-05:00","event_time_end_last":"2020-11-20T12:00:00-05:00","gmt_time_start":"2020-11-20 15:00:00","gmt_time_end":"2020-11-20 17:00:00","gmt_time_end_last":"2020-11-20 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"102851","name":"Phd proposal"}],"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":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}