Warehouse-Scale and Parallel Systems

Warehouse-Scale and Parallel Systems photo
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.


Improving Efficiency in Warehouse Scale Computers
Parallel Computing and Supercomputing
Storage Systems

Related Links

Computer Engineering Lab
Software Systems Lab
Theory of Computation Lab

CSE Faculty

Austin, Todd
Bertacco, Valeria
Cafarella, Michael J.
Chen, Peter M.
Chowdhury, Mosharaf
Das, Reetuparna
Dreslinski, Ronald
Flinn, Jason
Kasikci, Baris
Madhyastha, Harsha
Mahlke, Scott
Mars, Jason
Mudge, Trevor
Narayanasamy, Satish
Noble, Brian
Shin, Kang G.
Stout, Quentin F.
Tang, Lingjia
Wenisch, Thomas F.