School of Computer Science

Parallel and Distributed Computing


General description

We are interested in parallel, distributed and cloud/edge models, algorithms, protocols, scalable architectures, challenging and emerging applications.

Academic staff: 

Michael Dinneen, Aniket Mahanti, S Manoharan, Radu Nicolescu (coordinator), Bruce Sham, Wanqing Tu, Xinfeng Ye.

PhD students: 

James Cooper, Alec Henderson, Longyu Ma, Raul Valencia Tenorio


Michael Dinneen:

Uses parallel and distributed computing to solve grand challenge problems in combinatorial science  (e.g. finding graph minor obstruction sets), discrete optimization (e.g. computing chromatic sums and clustering), and network design (e.g. building efficient topologies for broadcasting).

Aniket Mahanti:

We are interested in algorithms, architectures, and applications of distributed computing.   Much of the work involves doing characterization, performance evaluation, and analysis of real systems. The work is primarily empirical in nature. Focus areas are content delivery systems, fog computing, edge computing, Internet of Things, smart cities, smart grids, data analytics on distributed systems.

Radu Nicolescu:

We are interested in parallel and distributed models inspired from biology or by logic and functional programming. Potential applications may cover a wide range of areas, such as: high-level scalable multicore and cloud architectures (e.g. actors, serverless, SMACK), parallel and distributed image processing, asynchronous distributed deep learning, distributed combinatorial and graph algorithms.

Bruce Sham:

We focus on solving data, compute and memory intensive problems in the intersection of high speed communication, data-intensive computing such as machine learning and electronic design automation, and high performance computing. We are exploring novel algorithmic optimizations and algorithm-architecture mappings to optimize performance of parallel and heterogeneous architectures including Field-Programmable Gate Arrays (FPGA), general purpose multi-core (CPU) and graphics (GPU) processors.

Research Projects for PhD studies:

Wanqing Tu:

We design parallel and distributed algorithms or protocols to address various communication challenges for both wired and wireless networks. Major topics that we are investigating recently include large-scale wireless and mobile networks, multimedia group communications, smart cities and IoT, cognitive radio networks, edge networking, and wireless information and energy transmissions.

Xinfeng Ye:

We are interested in the mechanisms that support edge computing. We are studying approaches for assigning computing tasks between the edge devices and the cloud computing centres according to various functional and non functional constraints. Our general research interests include:
- efficient data transmission;
- task partitioning for edge computing.