Structure handling in data-flow systems
IEEE Transactions on Computers - The MIT Press scientific computation series
Graph allocation in static dataflow systems
ISCA '86 Proceedings of the 13th annual international symposium on Computer architecture
Methods for handling structures in data-flow systems
ISCA '85 Proceedings of the 12th annual international symposium on Computer architecture
Data-Driven and Demand-Driven Computer Architecture
ACM Computing Surveys (CSUR)
Computer Architecture and Parallel Processing
Computer Architecture and Parallel Processing
First version of a data flow procedure language
Programming Symposium, Proceedings Colloque sur la Programmation
A scheme to extract run-time parallelism form sequential loops
ICS '91 Proceedings of the 5th international conference on Supercomputing
Enhancing Functional and Irregular Parallelism: Stateful Functions and their Semantics
International Journal of Parallel Programming
A Hybrid Scheme for Processing Data Structures in a Dataflow Environment
IEEE Transactions on Parallel and Distributed Systems
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A direct structure access approach called token relabeling scheme is presented in which all array operations can be performed without the use of any intermediary structure memory. The graph constructs for both approaches are described. Four numerical algorithms including fast Fourier transform, bitonic sort, LU decomposition, and matrix multiplication are implemented in both approaches. Token relabeling is directly applicable to arrays which are entirely consumed. Graph constructs which allow partial consumption are also designed. The effectiveness and efficiency of this parallel random access construct verifies the feasibility and applicability of the token relabeling scheme. A deterministic simulation of Arvind and K.P. Gostelow's tagged-token data-flow architecture (1982) is undertaken to validate the graph designs and evaluate the performance of the graphs. It is shown that the direct access graphs present better performance with regard to execution time, speedup, and resource utilization.