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Parallel and Distributed Algorithms

Simultaneous computation by multiple processing units is a fundamental concept in modern computing. The number of processing units may vary from two to several thousand. The action of individual units may be centrally coordinated (parallel computation), or autonomous (distributed computation). Parallel algorithms have numerous applications in computational science and processing of massive datasets on parallel computers, processor clusters and multicore processors. Distributed algorithms form the basis of modern networking technologies and the internet.

DIMAP members have contributed to research on parallel and distributed algorithms for several decades. These contributions include efficient parallel algorithms for a variety of combinatorial, matrix and string problems; new important techniques for network routing and network design; studies on limits of parallel and distributed computation in various contexts.

A common theme of the current research of DIMAP in this area is the analysis of resource limitations inherent in parallel and distributed algorithms, and the design of efficient techniques for optimising the use of limited resources. Depending on a particular application, the resources in question may include processing power, communication bandwidth, synchronisation frequency, or network congestion. We aim at developing models and techniques that capture the essential features of modern computers and networks, and provide solutions that are both efficient and widely applicable.

Sample publications: