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Dr Patrick Maier

Lecturer


Summary

Patrick Maier holds a PhD from the Max-Planck Institute for Computer Science, Saarbruecken, Germany. Prior to joining Sheffield Hallam as a Lecturer, he has worked as a research associate/fellow at the University of Edinburgh, at Heriot Watt University, and at the University of Glasgow.

About

His research is concerned with designing programming languages and systems for large-scale parallel computation, specifically for problems with irregular parallelism. His research interests also include fault tolerance, programming language semantics, and parallel computational algebra.

Specialist areas of interest

Functional Programming
Parallel Programming
Domain Specific Languages
Symbolic Computation

Teaching

Subject area

Software Engineering

Publications

Journal articles

Archibald, B., Maier, P., McCreesh, C., Stewart, R., & Trinder, P. (2017). Replicable parallel branch and bound search. Journal of Parallel and Distributed Computing, 113, 92-114. http://doi.org/10.1016/j.jpdc.2017.10.010

Morton, J.M., Maier, P., & Trinder, P. (2016). JIT-Based cost analysis for dynamic program transformations. Electronic Notes in Theoretical Computer Science, 330, 5-25. http://doi.org/10.1016/j.entcs.2016.12.012

Behrends, R., Hammond, K., Janjic, V., Konovalov, A., Linton, S., Loidl, H.-.W., ... Trinder, P. (2016). HPC-GAP: engineering a 21st-century high-performance computer algebra system. Concurrency and Computation: Practice and Experience, 28 (13), 3606-3636. http://doi.org/10.1002/cpe.3746

Stewart, R., Maier, P., & Trinder, P. (2016). Transparent fault tolerance for scalable functional computation. Journal of Functional Programming, 26, e5. http://doi.org/10.1017/S095679681600006X

Maier, P., Stewart, R., & Trinder, P.W. (2014). Reliable scalable symbolic computation: The design of SymGridPar2. Computer Languages, Systems & Structures, 40 (1), 19-35. http://doi.org/10.1016/j.cl.2014.03.001

Conference papers

Archibald, B., Maier, P., Stewart, R., & Trinder, P. (2019). Implementing YewPar: a framework for parallel tree search. In Euro-Par 2019, 26 August 2019 - 30 August 2019 (pp. 184-196). Springer: https://link.springer.com/chapter/10.1007%2F978-3-030-29400-7_14

Archibald, B., Maier, P., Stewart, R., Trinder, P., & De Beule, J. (2017). Towards Generic Scalable Parallel Combinatorial Search. In PASCO 2017, Kaiserslautern, Germany, 23 July 2017 - 24 July 2017 (pp. 1-10). ACM: http://doi.org/10.1145/3115936.3115942

Maier, P., Morton, J.M., & Trinder, P. (2016). JIT costing adaptive skeletons for performance portability. In Proceedings of the 5th International Workshop on Functional High-Performance Computing - FHPC 2016, (pp. 23-30). ACM: http://doi.org/10.1145/2975991.2975995

Book chapters

Maier, P., Stewart, R., & Trinder, P. (2014). The HdpH DSLs for scalable reliable computation. In Proceedings of the 2014 ACM SIGPLAN symposium on Haskell - Haskell '14. (pp. 65-76). ACM: http://doi.org/10.1145/2633357.2633363

Maier, P., Livesey, D., Loidl, H.-.W., & Trinder, P. (2014). High-Performance Computer Algebra: A Hecke Algebra Case Study. In Euro-Par 2014 Parallel Processing. (pp. 415-426). Springer: http://doi.org/10.1007/978-3-319-09873-9_35

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