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Journal ArticleDOI

A survey of stream processing

Robert Stephens
- 14 Jul 1997 - 
- Vol. 34, Iss: 7, pp 491-541
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TLDR
An analysis of the development of each of these specialized topics to determine if a general theory of stream processing has emerged is presented, including a comparison of the semantic models that are used to formalize stream based computation.
Abstract
Stream processing is a term that is used widely in the literature to describe a variety of systems. We present an overview of the historical development of stream processing and a detailed discussion of the different languages and techniques for programming with streams that can be found in the literature. This includes an analysis of dataflow, specialized functional and logic programming with streams, reactive systems, signal processing systems, and the use of streams in the design and verification of hardware.

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Citations
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Proceedings ArticleDOI

Mining time-changing data streams

TL;DR: An efficient algorithm for mining decision trees from continuously-changing data streams, based on the ultra-fast VFDT decision tree learner is proposed, called CVFDT, which stays current while making the most of old data by growing an alternative subtree whenever an old one becomes questionable, and replacing the old with the new when the new becomes more accurate.
Book ChapterDOI

StreamIt: A Language for Streaming Applications

TL;DR: The StreamIt language provides novel high-level representations to improve programmer productivity and program robustness within the streaming domain and the StreamIt compiler aims to improve the performance of streaming applications via stream-specific analyses and optimizations.
Proceedings ArticleDOI

Cg: a system for programming graphics hardware in a C-like language

TL;DR: A programming language and supporting system that are designed for programming programmable floating-point vertex and fragment processors, with support for data-dependent control flow in the vertex processor.
Proceedings ArticleDOI

Exploiting coarse-grained task, data, and pipeline parallelism in stream programs

TL;DR: This paper demonstrates an end-to-end stream compiler that attains robust multicore performance in the face of varying application characteristics and exploits all types of parallelism in a unified manner in order to achieve this generality.
Proceedings ArticleDOI

A stream compiler for communication-exposed architectures

TL;DR: This paper describes a fully functional compiler that parallelizes StreamIt applications for Raw, including several load-balancing transformations, and demonstrates that the StreamIt compiler can automatically map a high-level stream abstraction to Raw without losing performance.
References
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Book ChapterDOI

Learning internal representations by error propagation

TL;DR: This chapter contains sections titled: The Problem, The Generalized Delta Rule, Simulation Results, Some Further Generalizations, Conclusion.
Journal ArticleDOI

A logical calculus of the ideas immanent in nervous activity

TL;DR: In this article, it is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under another and gives the same results, although perhaps not in the same time.
Book

Learning internal representations by error propagation

TL;DR: In this paper, the problem of the generalized delta rule is discussed and the Generalized Delta Rule is applied to the simulation results of simulation results in terms of the generalized delta rule.
Journal ArticleDOI

Communicating sequential processes

TL;DR: It is suggested that input and output are basic primitives of programming and that parallel composition of communicating sequential processes is a fundamental program structuring method.