A Formal Definition of Data Flow Graph Models
IEEE Transactions on Computers
Executing a Program on the MIT Tagged-Token Dataflow Architecture
IEEE Transactions on Computers
A bridging model for parallel computation
Communications of the ACM
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Proceedings of the eighth international conference on Architectural support for programming languages and operating systems
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Journal of the ACM (JACM)
Communications of the ACM
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CC '02 Proceedings of the 11th International Conference on Compiler Construction
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Proceedings of the 31st annual international symposium on Computer architecture
Computer
Sealing OS processes to improve dependability and safety
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
IEEE Transactions on Software Engineering
Using simple abstraction to reinvent computing for parallelism
Communications of the ACM
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HotOS'13 Proceedings of the 13th USENIX conference on Hot topics in operating systems
Pursue robust indefinite scalability
HotOS'13 Proceedings of the 13th USENIX conference on Hot topics in operating systems
The tao of parallelism in algorithms
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
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The processor industry has reached the point where sequential improvements have plateaued and we are being flooded with parallel hardware we don't know how to utilise. An efficient, general-purpose and easy-touse parallel model is urgently needed to replace the von Neumann model. We introduce and discuss the selfmodifying dataflow graph, an unusual model of computation which combines the naturally parallel dataflow model with local graph transformations to eliminate the need for a global memory. We justify why it is a promising candidate.