{"436681":{"#nid":"436681","#data":{"type":"event","title":"The School of Computer Science and the School of Electrical and Computer Engineering Seminar - Scott Mahlke, University of Michigan","body":[{"value":"\u003Cp class=\u0022p1\u0022\u003ETitle: Energy Efficient Computing is Easy if You Don\u0027t Care about Programmability\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003ESpeaker: Scott Mahlke, University of Michigan\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003EAbstract:\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003EIn recent years, advances in semiconductor technologies have pushed the instrumentation of our world to unprecedented levels. Sensors are now all around us: cell phones contain GPS receivers, video cameras, and audio recorders, watches sense heart rates, and unmanned aerial vehicles flying overhead are constantly imaging the Earth.\u0026nbsp; However, computing in this abundant data world has not kept pace in large part due to energy constraints.\u0026nbsp; From data centers, where electricity costs dominate operating expenses, to mobile phones, where battery life is precious to all users, fundamental increases in energy efficiency are critical to drive abundant data computing.\u0026nbsp; To scale energy efficiency, engineers have traditionally employed hardwired accelerators.\u0026nbsp; Hardwired accelerators provide the most efficient hardware implementations of specific functionality at orders of magnitude lower power or higher performance compared to traditional processors, but at the cost of programmability.\u0026nbsp; Such accelerators cannot execute a spectrum of applications, some of which have not even been written yet.\u0026nbsp; Throughput processors provide an opportunity to bridge this gap by scaling efficiency while still providing a programmable substrate for data-parallel workloads that dominate abundant data processing including image\/signal processing, natural language processing, computer vision, and deep learning.\u0026nbsp; But throughput processors are not a panacea, commercial realizations in the form of graphics processing units (GPUs) face their own challenges of high peak power consumption and high software development costs where even the best experts struggle to extract only a small fraction of the peak performance.\u0026nbsp; In this talk, I will examine the hardware\/software challenges of designing and exploiting energy-efficient throughput processors. \u0026nbsp; \u0026nbsp;By rethinking the conventional GPU architecture with an energy-first approach and creating a source-to-source compiler toolchain to tame the programming complexity, a new generation of throughput processors can be created.\u003C\/p\u003E\u003Cp class=\u0022p2\u0022\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003EBio:\u003C\/p\u003E\u003Cp class=\u0022p1\u0022\u003EScott Mahlke is a Professor in the Electrical Engineering and Computer Science Department at the University of Michigan where he leads the Compilers Creating Custom Processors group (\u003Ca href=\u0022http:\/\/cccp.eecs.umich.edu\/\u0022\u003Ehttp:\/\/cccp.eecs.umich.edu\u003C\/a\u003E).\u0026nbsp; The CCCP group delivers technologies in the areas of customized processors for energy-efficient computing, reliable system design, and compiler code generation for heterogeneous systems.\u0026nbsp; Prior to joining academia, Scott was a Senior Researcher at Hewlett-Packard Laboratories. \u0026nbsp; \u0026nbsp;He was one of the original contributors to both the OpenImpact and Trimaran compilers for VLIW processors.\u0026nbsp; Scott\u0027s achievements were recognized by several awards, including the Morris Wellman Professorship in 2004, ACM SIGARCH\/IEEE-CS TCCA Most Influential Paper Award in 2006, Young Alumni Achievement Award in 2007, Ted Kennedy Family Team Excellence Award in 2009, the EECS Outstanding Achievement Award in 2011, and the 2014 Monroe-Brown Foundation Education Excellence Award.\u0026nbsp; Scott received the Ph.D. degree in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1997 and is an IEEE Fellow.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The School of Computer Science and the School of Electrical and Computer Engineering Seminar - Scott Mahlke, University of Michigan"}],"uid":"28150","created_gmt":"2015-08-18 16:56:27","changed_gmt":"2017-04-13 21:18:44","author":"Birney Robert","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2015-08-25T12:00:00-04:00","event_time_end":"2015-08-25T13:00:00-04:00","event_time_end_last":"2015-08-25T13:00:00-04:00","gmt_time_start":"2015-08-25 16:00:00","gmt_time_end":"2015-08-25 17:00:00","gmt_time_end_last":"2015-08-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"hg_media":{"440301":{"id":"440301","type":"image","title":"Mahlke","body":null,"created":"1449256175","gmt_created":"2015-12-04 19:09:35","changed":"1475895179","gmt_changed":"2016-10-08 02:52:59","alt":"Mahlke","file":{"fid":"203051","name":"mahlke-ieee.jpg","image_path":"\/sites\/default\/files\/images\/mahlke-ieee_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/mahlke-ieee_0.jpg","mime":"image\/jpeg","size":104337,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/mahlke-ieee_0.jpg?itok=rOn205sd"}}},"media_ids":["440301"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[{"id":"654","name":"College of Computing"},{"id":"2435","name":"ECE"},{"id":"138721","name":"Electrical Computer Engineering"},{"id":"109","name":"Georgia Tech"},{"id":"166941","name":"School of Computer Science"},{"id":"166940","name":"SCS"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EDani Denton\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022mailto:denton@cc.gatech.edu\u0022\u003Edenton@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}