Copenhagen Programming Language Seminar
Flat data parallelism provides a fast, scalable execution model for parallel computation, but its programming model is limiting. In contrast, nested data parallelism provides a flexible programming model, but efficient execution is a challenge. NESL showed that, in principle, once can combine the nested data parallel programming model with the efficient execution model of flat data parellelism. In this talk I will describe Data Parallel Haskell, a modern realization of the ideas behind NESL as implemented in the GHC compiler. I will also discuss an alternative approach to executing nested data parallel programs that we have recently begun implementing in GHC.
Bio: Geoffrey Mainland obtained an A.B. in Physics and, in 2011, a Ph.D. in computer science from Harvard University under the supervision of Greg Morrisett and Matt Welsh. He is presently a post doc with the Programming Principles and Tools group at Microsoft Research Cambridge. His research focuses on tools and techniques for building correct systems from resource-constrained components.
Ken Friis Larsen Administrative host:Jette Møller.
All are welcome.
The Copenhagen Programming Language Seminar (COPLAS) is a collaboration between DIKU, DTU, ITU, and RUC.
COPLAS is part of the FIRST Research School.
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