Term rewriting and all that
The design of a class mechanism for Moby
Proceedings of the ACM SIGPLAN 1999 conference on Programming language design and implementation
Automated scientific software scripting with SWIG
Future Generation Computer Systems - Tools for program development and analysis
Application-specific foreign-interface generation
Proceedings of the 5th international conference on Generative programming and component engineering
Sequoia: programming the memory hierarchy
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Sequoia: programming the memory hierarchy
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Implementing the PGI Accelerator model
Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units
CUDA by Example: An Introduction to General-Purpose GPU Programming
CUDA by Example: An Introduction to General-Purpose GPU Programming
Offload – automating code migration to heterogeneous multicore systems
HiPEAC'10 Proceedings of the 5th international conference on High Performance Embedded Architectures and Compilers
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Numerous programming models have been introduced to allow programmers to utilize new accelerator-based architectures. While OpenCL and CUDA provide low-level access to accelerator programming, the task cries out for a higher-level abstraction. Of the higher-level programming models which have emerged, few are intended to co-exist with mainstream, general-purpose languages while supporting tunability, composability, and transparency of implementation. In this paper, we propose extensions to the type systems (implementable as syntactically neutral annotations) of traditional, general-purpose languages can be made which allow programmers to work at a higher level of abstraction with respect to memory, deferring much of the tedium of data management and movement code to an automatic code generation tool. Furthermore, our technique, based on formal term rewriting, allows for user-defined reduction rules to optimize low-level operations and exploit domain- and/or application-specific knowledge.