High Performance Optimizations in Runtime Speculative Parallelization for Multicore Architectures. Paraskevas Yiapanis. PhD Thesis, School of Computer Science, The University of Manchester, 2013.
[Available upon Request]
Optimizing Software Runtime Systems for Speculative Parallelization. Paraskevas Yiapanis, Demian Rosas, Gavin Brown, Mikel Luján. In ACM Transactions on Architecture and Code Optimization (TACO), 9 (4), 39, January 2013.
[Bibtex][PDF][DOI]
Architectural Support for Exploiting Fine Grain Parallelism. Demian Rosas-Ham, Isuru Herath, Paraskevas Yiapanis, Mikel Lujan, Ian Watson. In Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, June 2012.
[Bibtex][PDF][IEEE link]
Toward a More Accurate Understanding of the Limits of the TLS Execution Paradigm.
Nikolas Ioannou, Jeremy Singer, Salman Khan, Polychronis Xekalakis,
Paraskevas Yiapanis, Adam Pocock, Gavin Brown, Mikel Luján, Ian Watson
and Marcelo Cintra.
In Proceedings of the International Symposium on Workload
Characterization (IISWC), December 2010.
[Bibtex] [PDF]
Online Nonstationary Boosting. Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, Mikel Luján
and and Gavin Brown. In Proceedings of the
International Workshop on Multiple Classifier Systems (MCS), LNCS 5997, pp 205-214, 2010.
[Bibtex] [PDF]
Static Java Program Features for Intelligent Squash Prediction. Jeremy Singer, Paraskevas Yiapanis, Adam Pocock, Mikel Luján, Gavin
Brown, Nikolas Ioannou and Marcelo Cintra. In Proceedings of the 4th
Workshop on Statistical and Machine Learning Approaches to Architecture
and Compilation (SMART), January 2010.
[Bibtex] [PDF]
Mining Static Features for Squash Prediction in Thread-Level Speculation. Paraskevas Yiapanis, Jeremy Singer, Adam Pocock, Mikel Luján, Gavin
Brown. In the 5th International Summer School on Advanced Computer
Architecture and Compilation for Embedded Systems (ACACES), July
2009.
[Bibtex] [PDF]
Fundamental Nano-Patterns to Characterize and Classify Java Methods.
Jeremy Singer, Gavin Brown, Mikel Luján, Adam Pocock and Paraskevas
Yiapanis. In Proceedings of the Workshop on Language Descriptions,
Tools and Applications (LDTA), March 2009.
[Bibtex] [PDF]
Variable-grain and Dynamic Work Generation for Minimal Unique Itemset Mining. Paraskevas Yiapanis, David J. Haglin, Anna M. Manning, Ken Mayes, and
John Keane. In Proceedings of the 2008 IEEE International Conference on Cluster Computing
(Cluster 2008), Tsukuba, Japan, pp. 33-41, September 2008.
[Bibtex] [PDF]
Parallel Mining of Minimal Sample Unique Itemsets. Paraskevas Yiapanis. MSc Thesis, School of Computer Science, The University of Manchester, 2007.
[Available upon request]