Warehouse-Scale and Parallel Systems
Our society is increasingly relying on massive-scale computing systems "in the cloud" for all facets of life, from transportation and communication to business, governing, and scientific discovery. These applications are enabled by highly-parallel, warehouse-scale computing infrastructure operated by service providers like Amazon, Facebook, Microsoft and Google as well as other private and government entities. Designers of the next-generation of data intensive applications and warehouse-scale systems face enormous challenges, including improving performance, enabling greater programmer productivity, guaranteeing quality of service, using energy efficiently, provisioning power, maintaining reliability, controlling temperature, ensuring manageability, etc.|
In this research space, CSE faculty are pursuing the design of the hardware and software infrastructure for massive-scale computing systems. Major research topics include server architecture, hardware specialization, accelerators and general-purpose GPU computing, computational science, emerging memory technologies, data center physical infrastructure, distributed software and storage systems, virtualization, high-performance networking, and programming systems for cloud computing.
SpecialtiesImproving Efficiency in Warehouse Scale Computers
Parallel Computing and Supercomputing
Related LinksComputer Engineering Lab
Theory of Computation Lab
Related News Articles2017-02-17 Harsha Madhyastha Selected for Google Faculty Award 2016-02-16 Mosharaf Chowdhury Receives Google Faculty Research Award to Develop... 2015-10-28 The Future of Data Science: Kicking Off U-Ms Proactive Step into an... 2015-03-25 Voice Control Will Force an Overhaul of the Whole Internet 2015-03-16 Researchers just built a free, open-source version of Siri 2015-03-16 Engineers Bring A New Open-Source Siri To Life 2015-03-16 Free Sirius One-Ups Siri 2015-03-12 Sirius Is the Google-Backed Open Source Siri 2015-03-12 Meet Sirius: An Open-Source Digital Assistant 2014-12-19 Protean Code Allows Data Center Servers to Adapt to Changing... 2011-07-28 Wenisch: WEMU Issues of the Environment - Interview on Data Centers... 2011-04-22 David Meisner Receives Yahoo! 2011 Key Scientific Challenges (KSC)... 2009-03-12 PowerNap and RAILS provide roadmap for reduced data center energy...
CSE FacultyAustin, Todd
Cafarella, Michael J.
Chen, Peter M.
Shin, Kang G.
Stout, Quentin F.
Wenisch, Thomas F.