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Daniel Goodman

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Research Associate
Email: Daniel.Goodman [at]

Since the completion of the Teraflux project I have moved to Oracle Labs Cambridge.

I worked as a research associate on the TeraFlux project, looking at programming models for combining dataflow and transactional Memory. Within this project I produced a suite of software transactional memories for Scala called Manchester University Transactions for Scala (MUTS) and a Scala based dataflow library called DFScala. I then worked on memory analysis and categorisation of the resulting model. My wider research interests are novel computation models and user friendly programming models.

Prior Work

Prior to taking up the post with Teraflux I held a position with Fujitsu Laboratories of Europe working as a Senior Researcher, and a position as a Research Associate and Junior Research Fellow at the Oxford e-Research Centre, Oxford University and Pembroke College, Oxford University respectively. During this time I looked at tooling and programming models for high performance computing on machines ranging from small clusters, to clusters of GPGPU's, to Japan's next generation 10 PFlop super computer. In all cases this work was based on constructing tools and programming constructs/models that made high performance computing more accessible to application scientists in areas ranging from astronomy, to medical imagery to simulating the visual cortex.


  • Daniel Goodman, Behram Khan, Mikel Luján, and Ian Watson. Improved Dataflow Executions with User Assisted Scheduling. In Proceedings of the 3rd International Workshop on Data-Flow Models For Extreme Scale Computing (DFM), 2013. [.pdf]

  • Marco Solinas, Rosa M. Badia, François Bodin, Albert Cohen, Paraskevas Evripidou, Paolo Faraboschi, Bernhard Fechner, Guang R. Gao, Arne Garbade, Sylvain Girbal, Daniel Goodman, Behran Khan, Souad Koliai, Feng Li, Mikel Luján, Laurent Morin, Avi Mendelson, Nacho Navarro, Antoniu Pop, Pedro Trancoso, Theo Ungerer, Mateo Valero, Sebastian Weis, Ian Watson, Stéphane Zuckermann, Roberto Giorgi.The TERAFLUX Project: Exploiting the DataFlow Paradigm in Next Generation Teradevices In Proceedings of the 16th Euromicro Conference on Digital System Design 2013. [.pdf]

  • Daniel Goodman, Salman Khan, Behram Khan, Mikel Luján, and Ian Watson. Software transactional memories for Scala. In the Journal of Parallel and Distributed Computing, October 2012. [.pdf]

  • Daniel Goodman, Salman Khan, Chris Seaton, Yegor Guskov, Behram Khan, Mikel Luján, and Ian Watson. DFScala: High level dataflow support for Scala. In Proceedings of the 2nd International Workshop on Data-Flow Models For Extreme Scale Computing (DFM), 2012. [.pdf]

  • Isuru Herath, Demian Rosas, Daniel Goodman, Mikel Lujan, Ian Watson. A case for Exiting a Transaction in the Context of Hardware Transactional Memory ACM SIGPLAN Workshop on Transactional Computing (Transact), February 2012. [.pdf]

  • Chis Seaton, Daniel Goodman, Mikel Lujan, and Ian Watson. Applying dataflow and transactions to Lee routing In Workshop on Programmability Issues for Heterogeneous Multicores (MultiProg), January 2012. Winner of Best paper [.pdf]

  • Jeyarajan Thiyagalingam, Daniel Goodman, Julia Schnabel, Anne Trefethen and Vicente Grau. On the usage of GPUs for Efficient Motion Estimation in Medical Image Sequences. International Journal of Biomedical Imaging, special issue: Parallel Computation in Medical Imaging Applications, June 2011.[.pdf]

  • Daniel Goodman, Behram Khan, Salman Khan, Chris Kirkham, Mikel Lujan and Ian Watson. MUTS: Native Scala Constructs for Software Transactional Memory In Proceedings of Scala Days 2011, Stanford CA, June 2011. [.pdf]

  • Daniel Goodman. Environmental Considerations When Measuring Relative Performance of Graphics Cards In Proceedings of GPUs and Accelerators in HPC, Daresbury, September 2010. [.pdf]

  • Daniel Goodman. Provenance in Dynamically Adjusted and Partitioned Workflows. In Proceedings of eScience 2008, December 2008. [.pdf]

  • Maria Susana Avila-Garcia, Anne Trefethen, Mike Brady, Fergus Gleeson and Daniel Goodman. Lowering the Barriers to Cancer Imaging. In Proceedings of eScience 2008, December 2008. [.pdf]

  • Daniel Goodman. Introduction and evaluation of Martlet, a scientific workflow language for abstracted parallelisation. In Proceedings of the Sixteenth International World Wide Web Conference, pages 983-992. International World Wide Web Conference Committee, ACM, May 2007. Nominated for best student paper award. [.pdf]

  • Daniel Goodman. Martlet: A scientific work-flow language for abstracted parallelisation. In UK e-Science All Hands Meeting, September 2006. Winner of best student paper award [.pdf]

  • N. Massey, T. Aina, M. Allen, C. Christensen, D. Frame, D. Goodman, J. Kettleborough, A. Martin, S. Pascoe and D. Stainforth. Data access and analysis with distributed federated data servers in Advances in Geosciences, 8, p49-56, 2006. [.pdf]

  • Daniel Goodman. Scientific middleware for abstracted parallelisation. OUCL, 2006. [.pdf]

  • Daniel Goodman and Andrew Martin. Grid style web services for In S. Newhouse and S. Parastatidis, editors, GGF workshop on building Service-Based Grids, Honolulu, Hawaii. Global Grid Forum, 2004. [.pdf]

Conference Abstracts

  • Daniel Goodman and Mikel Lujan Scientific GPU Programming with Data-Flow Languages Multi-Core and Reconfigurable Super Computing Conference, Bristol, 2011. [abstract] [poster]

  • Maria Susana Avila-Garcia, Anne Trefethen, Mike Brady, Fergus Gleeson and Daniel Goodman. Cloud Computing Framework Design for Cancer Imaging Research. Microsoft e-Science Meeting 2008. December 2008. [abstract] [slides]

  • Daniel Goodman. Decentralised Middleware and Workflow Enactment for the Martlet Workflow Language. UK e-Science All Hands Meeting, Edinburgh, 2008. [abstract] [slides]

  • Daniel Goodman, Anne Trefethen and Douglas Creager. The influence of "the Grid" on Multi-Core computing. UK e-Science All Hands Meeting, Edinburgh, 2008. [abstract] [slides]

  • Daniel Goodman, Anne Treffethen and Douglas Creager. A dynamic world, what can Grids do for Multi-core computing? Many-core and Reconfigurable Super Computing Conference, Belfast, 2008. [abstract] [slides]

  • Daniel Goodman, Stef Salvini, and Anne Trefethen. Experiences with Distributed and Parallel MATLAB on a Microsoft CCS cluster. SIAM Conference on Parallel Programming for Scientific Computing, Atlanta, Georgia, 2008. [poster]

  • Daniel Goodman, Stef Salvini and Anne Trefethen. Experiences with Distributed and Parallel MATLAB on CCS. Microsoft e-Science Meeting, Durham, North Carolina, 2007. [slides]

Doctoral Thesis


I graduated from Oxford University in 2003 where I was awarded the Hoare Prize for the highest 1st in Computer Science that year. I then started a doctorate working with under the supervision of Dr Andrew Martin and Dr Raphael Hauser looking at techniques for the analysis of large quantities of distributed data in a Grid environment. This resulted in the development of the Martlet workflow language. Building on ideas from data-flow and functional programming Martlet abstracts from the user the distribution and partitioning of large data sets, allowing them to construct functions that would automatically adjust to the changing environment without the user having to be aware. This work was well received with best student paper at UK e-Science AHM 2006 a nomination for best student paper at WWW2007 and the awarding of the doctorate in 2007.