Parallel and Distributed Computation

Research Areas -> Theory of Computation -> Parallel and Distributed Computation
 
Overview
For decades, the speed of processors was growing exponentially, but this has abruptly stopped. Instead, now the number of processor cores on a chip is growing exponentially. A graphics processing unit (GPU) in a laptop may have 100 cores, and supercomputers may have 1,000,000. At Michigan, we are developing algorithms and data structures that use parallelism to help solve large problems such as climate modeling and the design of ethical clinical trials. Abstract models of parallelism are also investigated, such as having a vast array of tiny processors all working synchronously on the same problem. We also study abstract models of distributed computation, where a large number of independent, unsynchronized computers are arranged in a (possibly unknown) network and must solve a problem only through local communication.
 
Faculty
Pettie, Seth
Stout, Quentin F.


Related Labs, Centers, and Groups
Software Systems Laboratory