dataflow has proven to be an attractive computation model for programming digital signal processing (DSP) applications. A restricted version of dataflow, termed synchronous dataflow (SDF), offers strong compile-time p...
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ISBN:
(纸本)9781424443345
dataflow has proven to be an attractive computation model for programming digital signal processing (DSP) applications. A restricted version of dataflow, termed synchronous dataflow (SDF), offers strong compile-time predictability properties, but has limited expressive power. In this paper we propose a new type of hierarchy in the SDF domain allowing more expressivity while maintaining its predictability. This new hierarchy semantic is based on interfaces that fix the number of tokens consumed/produced by a hierarchical vertex in a manner that is independent or separate from the specified internal dataflow structure of the encapsulated subsystem. This interface-based hierarchy gives the application designer more flexibility in iterative construction of hierarchical representations, and experimentation with different optimization choices at different levels of the design hierarchy.
The problem of software development for distributed and parallel computing systems is considered in the paper. Its original issue is in extending our projecting work on parallel programming languages and operational t...
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ISBN:
(纸本)9789898111517
The problem of software development for distributed and parallel computing systems is considered in the paper. Its original issue is in extending our projecting work on parallel programming languages and operational tools for their realization on large scale computing systems.
The paper gives an overview on the DSPL programming environment, an integrated approach to automate system design and implementation of applications run on dedicated parallel systems. The programming environment consi...
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The paper gives an overview on the DSPL programming environment, an integrated approach to automate system design and implementation of applications run on dedicated parallel systems. The programming environment consists of a data-flow language and an integrated set of tools. The tools automatically derive a software model from the given application program. Based on the model, the design decisions as the network topology, the task mapping and schedule as well as the optimal use of buffers are computed. Finally, the design decisions are automatically implemented by transforming the application program in executable code for the chosen processor network. The DSPL programming environment integrates model-based optimization techniques and program transformation techniques. The integration allows to include new aspects in the optimization process. Especially optimizations crucial to the semantics of the program can be included. The most important examples of such optimizations are the enforcement of the schedule in case of data-dependent execution of tasks and the transformation of buffered communication to unbuffered communication. Both aspects are crucial to the generation of efficient parallel implementations. The integration of the two aspects is supported by a formal framework. This allows to formally prove the correctness of the program optimizations performed by the programming environment. (C) 1999 Elsevier Science B.V. All rights reserved.
The synchronous dataflow (SDF) programming paradigm has been used extensively in design environments for multirate signal processing applications. In this paradigm, the repetition of computations is specified by the r...
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The synchronous dataflow (SDF) programming paradigm has been used extensively in design environments for multirate signal processing applications. In this paradigm, the repetition of computations is specified by the relative rates at which the computations consume and produce data. This implicit specification of iteration allows a compiler to easily explore alternative nested loop structures for the target code with respect to their effects on code size, buffering requirements and throughput. In this paper, we develop important relationships between the SDF description of an algorithm and the range of looping structures offered by this description, and we discuss how to improve code efficiency by applying these relationships.
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