Max-Planck-Institut für Informatik
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What and Who
Title:Sharing-Aware Resource Management for Performance and Protection
Speaker:Sandhya Dwarkadas
coming from:Department of Computer Science, University of Rochester
Speakers Bio:Sandhya Dwarkadas is the Albert Arendt Hopeman Professor of Engineering, and Professor and Chair of Computer Science with a secondary appointment in Electrical and Computer Engineering, at University of Rochester, where she has been on the faculty since 1996. She received her Bachelor's degree from the Indian Institute of Technology, Madras, India, and her M.S. and Ph.D. from Rice University. She is a fellow of the ACM and IEEE. She is also a member of the board and steering committee for the computing Research Association's Committee on the Status of Women in Computing Research (CRA-W). Her areas of research interest include parallel and distributed computing, computer architecture and the interaction and interface between the compiler, runtime/operating system, and underlying architecture. Her research lies at the intersection of computer hardware and software with a particular focus on support for parallelism. She has made fundamental contributions to the design and implementation of shared memory both in hardware and in software, and to hardware and software energy- and resource-aware configurability. URL:
Event Type:SWS Distinguished Lecture Series
Visibility:D1, D2, D3, INET, D4, D5, SWS, RG1, MMCI
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Level:AG Audience
Date, Time and Location
Date:Thursday, 2 May 2019
Please note: New Time!
Duration:60 Minutes
Building:E1 5
Recognizing that applications (whether in mobile, desktop, or server environments) are rarely executed in isolation today, I will discuss some practical challenges in making best use of available hardware and our approach to addressing these challenges. I will describe two independent and complementary control mechanisms using low-overhead hardware performance counters that we have developed: a sharing- and resource-aware mapper (SAM) to effect task placement with the goal of localizing shared data communication and minimizing resource contention based on the offered load; and an application parallelism manager (MAPPER) that controls the offered load with the goal of improving system parallel efficiency. If time permits, I will also outline our work on streamlining instruction memory management and address translation to eliminate redundancy and improve efficiency, especially in mobile environments. Our results emphasize the need for low-overhead monitoring of application behavior under changing environmental conditions in order to adapt to environment and application behavior changes.
Name(s):Gretchen Gravelle
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:YesTo Location:Kaiserslautern
To Building:G26To Room:111
Meeting ID:SWS Space 2 (6312)
Tags, Category, Keywords and additional notes
Attachments, File(s):
  • Gretchen Gravelle, 04/26/2019 02:54 PM
  • Gretchen Gravelle, 04/23/2019 11:04 AM -- Created document.