Computer
Algorithmic skeletons: structured management of parallel computation
Algorithmic skeletons: structured management of parallel computation
An overview of Manifold and its implementation
Concurrency: Practice and Experience
A library-based approach to task parallelism in a data-parallel language
Journal of Parallel and Distributed Computing
Approaches for Integrating Task and Data Parallelism
IEEE Concurrency
Integrating Task and Data Parallelism by Means of Coordination Patterns
HIPS '01 Proceedings of the 6th International Workshop on High-Level Parallel Programming Models and Supportive Environments
Control-Driven Coordination Programming in Shared Dataspace
PaCT '97 Proceedings of the 4th International Conference on Parallel Computing Technologies
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Standard Templates Adaptive Parallel Library (STAPL)
LCR '98 Selected Papers from the 4th International Workshop on Languages, Compilers, and Run-Time Systems for Scalable Computers
Pattern-Based Parallel Programming
ICPP '02 Proceedings of the 2002 International Conference on Parallel Processing
ACM Turing award lectures
Hi-index | 0.00 |
We propose a semantic framework for parallel programming based on the orthogonalization of data access and control concerns by means of set of abstraction mechanisms. Such mechanisms regard the description of how data has to be accessed, the description of how data has to be computed and the description of how coupling data accesses and patterns of control. Each description is represented by an abstraction mechanism formalized through a formal semantics. The set of semantics specifications defines a method to investigate the structure of the whole application. We demonstrate how this semantics provides a formal, provable method to statically or dynamically evaluate the overall performance of the application and, eventually, apply optimization rules.