Efficiently computing static single assignment form and the control dependence graph
ACM Transactions on Programming Languages and Systems (TOPLAS)
Lava: hardware design in Haskell
ICFP '98 Proceedings of the third ACM SIGPLAN international conference on Functional programming
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Microsoft DirectX 9 Programmable Graphics Pipeline
Microsoft DirectX 9 Programmable Graphics Pipeline
Cg: a system for programming graphics hardware in a C-like language
ACM SIGGRAPH 2003 Papers
Linear algebra operators for GPU implementation of numerical algorithms
ACM SIGGRAPH 2003 Papers
Representation-based just-in-time specialization and the psyco prototype for python
Proceedings of the 2004 ACM SIGPLAN symposium on Partial evaluation and semantics-based program manipulation
ACM SIGGRAPH 2004 Papers
Programming graphics processors functionally
Haskell '04 Proceedings of the 2004 ACM SIGPLAN workshop on Haskell
Real-Time 3D Fluid Simulation on GPU with Complex Obstacles
PG '04 Proceedings of the Computer Graphics and Applications, 12th Pacific Conference
Fast genetic programming on GPUs
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Obsidian: a domain specific embedded language for parallel programming of graphics processors
IFL'08 Proceedings of the 20th international conference on Implementation and application of functional languages
Firepile: run-time compilation for GPUs in scala
Proceedings of the 10th ACM international conference on Generative programming and component engineering
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Dynamic languages typically allow programs to be written at a very high level of abstraction. But their dynamic nature makes it very hard to compile such languages, meaning that a price has to be paid in terms of performance. However under certain restricted conditions compilation is possible. In this paper we describe how a domain specific language for image processing in Python can be compiled for execution on high speed graphics processing units. Previous work on similar problems have used either translative or generative compilation methods, each of which has its limitations. We propose a strategy which combine these two methods thereby achieving the benefits of both.