TDFL: a task-level dataflow language
Journal of Parallel and Distributed Computing - Special issue: software tools for parallel programming and visualization
Executing a Program on the MIT Tagged-Token Dataflow Architecture
IEEE Transactions on Computers
ACM SIGPLAN Notices
ACM SIGPLAN Notices
DAMP—a dynamic reconfigurable multiprocessor system with a distributed switching network
EDMCC2 Proceedings of the 2nd European conference on Distributed memory computing
Code Parallelization for the LGDG Large-Grain Dataflow Computation
CONPAR 90/VAPP IV Proceedings of the Joint International Conference on Vector and Parallel Processing
A Distributed Algorithm for Dynamic Task Scheduling
CONPAR 90/VAPP IV Proceedings of the Joint International Conference on Vector and Parallel Processing
ADAM: A Coarse-Grain Dataflow Architecture that Addresses the Load Balancing and Throttling Problems
CONPAR 90/VAPP IV Proceedings of the Joint International Conference on Vector and Parallel Processing
Development of Portable Parallel Programs with Large-Grain Data Flow 2
CONPAR 90/VAPP IV Proceedings of the Joint International Conference on Vector and Parallel Processing
First version of a data flow procedure language
Programming Symposium, Proceedings Colloque sur la Programmation
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The task-level dataflow language D2R ("Dynamic Dataflow Representation") is suggested (Version 1.0). D2R uses dynamic branching, loops with data-dependent numbers of iterations and alternatives. The dataflow information can be expressed either as a program text or as graph. Primarily the model has been developed for cooperation with dynamic task scheduling algorithms. Its suitability is demonstrated by examples. The representation supports environments allowing to simultaneously execute multiple user programs ("space sharing") as well as to restrict the assignments of task and data nodes to special processors (e.g. I/O nodes). The system has been implemented using the multi transputer system "DAMP" /Bauch-91/.