Systems Research at Rochester

The department’s core faculty in Systems consists of Chen Ding, Sandhya Dwarkadas, Michael Scott, and Kai Shen, In addition, Wendi Heinzelman, and Michael Huang of Electrical and Computer Engineering have joint appointments in CS, and are active in department research.

Chen Ding is the recipient of a DOE Early Career Principal Investigator award and an NSF CAREER award. He joined URCS in July, 2000, after receiving his Ph.D. at Rice University. His research is in compiler technology, specifically in using compilers to generate programs that make better use of the caches on modern machines. For large scientific applications drawn from major benchmark suites, Chen’s tools have been able to reduce the demand for memory bandwidth by as much as 80%.

Sandhya Dwarkadas is the recipient of an NSF Postdoctoral Fellowship and an NSF CAREER award, and has done work in the areas of software distributed shared memory, parallel architecture, and performance evaluation. She co-led the Cashmere and InterWeave distributed sharing projects, and leads the ARCH (Architecture, Run-time, and Compiler integration for High-performance computing) project.

Michael Scott is the recipient of an IBM Faculty Development Award, the University’s Goergen Teaching Award, and the 2006 Dijkstra Prize in Distributed Computing. He is widely known for his work on parallel operating systems and synchronization algorithms. He co-led the Cashmere and InterWeave distributed sharing projects. His textbook on programming language design and implementation (Programming Language Pragmatics, Morgan Kaufmann, second edition, 2006) is a leading reference in the field, with adoptions at over 100 schools.

Kai Shen is the recipient of an NSF CAREER award. He joined the department in September, 2002, after receiving his Ph.D. from the University of California at Santa Barbara. His thesis work focused on clustering, replication, and resource management for scalable network services; results from this work have been adopted by the Ask.com Internet search site. Other contributions include compiler and run-time support for threaded MPI execution and sparse Gaussian elimination. At Rochester he heads the Neptune project.

Wendi Heinzelman is the recipient of an NSF CAREER award, an ONR Young Investigator award, and the University’s Curtis Teaching Award. She came to Rochester in January 2001, after receiving her Ph.D. from MIT. Her research involves algorithms and protocols for wireless sensor networks and wireless video delivery. She leads the Wireless Communications and Networking group.

Michael Huang joined the faculty in September 2002, after receiving his Ph.D. from the University of Illinois at Urbana-Champaign. His interests lie in computer architecture, processor microarchitecture, energy-efficient system and processor architecture, and processing-in-memory.

Parallel systems has been a central part of the department’s research focus since its founding in 1974. Early work on the Rochester Intelligent Gateway (RIG) project was the direct predecessor to the Accent and Mach projects at CMU, led by UR alum Rick Rashid (now Senior Vice President for Research at Microsoft). These in turn led to such commercially important operating systems as Compaq Tru64 and Apple MacOS X. In the mid to late 1980s, the department’s 128-node Butterfly Parallel Processor was the largest parallel computer anywhere in academia. It supported a wide variety of projects, including the Instant Replay debugging system, the Bridge parallel file system, the Elmwood and Psyche parallel operating systems, and the development of contention-free synchronization. Our work from this era is very heavily cited, and has influenced the research of many other groups. Our synchronization algorithms, for example, have been adopted by many commercial systems; several appear in the java.util.concurrent standard library. In the early 1990s we moved increasingly into architectural issues, with a heavy emphasis on detailed simulation. Our Mint simulation testbed has been exported to more than a hundred sites worldwide, and forms the basis for more recent simulators from at least three other groups.

As a group, our research spans a range of topics, including compiler technology, cluster-based parallel computing, distributed shared state, distributed and mobile computing, low-power hardware and software, processor and memory architecture, synchronization algorithms, client-server partitioning, and interactive data mining. We also maintain active interests in a wide variety of related topics, including parallel architectures, programming environments, computational science, and programming language design.

One of the strengths of the group is the way in which each faculty member’s research interests tie into the others’, allowing us to leverage infrastructure developed by the group as a whole. We therefore interact closely with the parallel user community, including researchers in Astrophysics, Chemistry, Biology, Laser Energetics, and, within our own department, Computer Vision, Robotics, Planning, and Data Mining. The multi-PI Computer Systems and Engineering Group spans the CS and ECE departments. Together with colleagues in AI, we have also received an unprecedented four consecutive major 5-year awards from the National Science Foundation Research Infrastructure program. Prof. Dwarkadas’s work on the TreadMarks and FASTLINK projects, in collaboration with colleagues at Rice University and at the National Institutes of Health, was instrumental in discovering the gene believed responsible for Parkinson’s disease.

The systems group enjoys outstanding computational resources. Current large-scale machines include a 72-node (144-processor) Linux cluster, a 32-processor IBM p690 machine (acquired with the assistance of a $1.2M grant from IBM), 8 and 16-processor SunFire multiprocessors (supported by grants of over $750K from Sun Microsystems Labs), an 8-core, 32-thread Sun T1000 (Niagara) machine, a 4-processor, 8-core Dell PowerEdge server, and a variety of smaller Sun, SGI, and Pentium machines. The group also has access to a variety of machines at the University’s Center for Research Computing, the Laboratory for Laser Energetics, the Pittsburgh Supercomputing Center, and other sites. For a more detailed list of department research facilities, click here.