Generative communication in Linda
ACM Transactions on Programming Languages and Systems (TOPLAS)
Software and the Concurrency Revolution
Queue - Multiprocessors
Scientific Programming - Exploring Languages for Expressing Medium to Massive On-Chip Parallelism
Data-Driven Tasks and Their Implementation
ICPP '11 Proceedings of the 2011 International Conference on Parallel Processing
Habanero-Java: the new adventures of old X10
Proceedings of the 9th International Conference on Principles and Practice of Programming in Java
High-performance language interoperability for scientific computing through Babel
International Journal of High Performance Computing Applications
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We present CnC-Python (CP), an approach to implicit multicore parallelism based on Intel's Concurrent Collections model. CP enables programmers to achieve task, data and pipeline parallelism in a declarative fashion while only being required to describe the program as a coordination graph with serial Python code for individual nodes.