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 reactive systems, specialized logic and functional programming, dataflow and the use of streams in the design and verification of hardware. In particular, we discuss and classify stream processing techniques from the perspective of programming primitives, implementation techniques, and computability issues. This includes a comparison of the different semantic models that are used to formalize stream based comp...
In the era of big data, an unprecedented amount of data is generated every second. The real time ana...
Stream processors, developed for the stream programming model, perform well on media applications. I...
The stream programming paradigm aims to expose coarsegrained parallelism in applications that must p...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
Stream processing languages and stream processing engines have become more popu-lar as they emerged ...
Stream processing languages and stream processing engines have become more popular as they emerged f...
Stream programs represent an important class of high-performance computations. Defined by their reg...
Stream processing has a long history as a way of describing and implementing specific kinds of compu...
In this tutorial paper we present the results of recent research findings in the area of data stream...
Many application areas for embedded systems, such as DSP, media coding, and image processing, are ba...
Various research communities have independently arrived at stream processing as a programming model ...
We introduce RATE TYPES, a novel type system to reason about and optimize data-intensive programs. B...
Most automatic programming research has focused on programs which terminate and which produce output...
In this paper we study the timing aspects of the operation of stream-processing applications that ru...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
In the era of big data, an unprecedented amount of data is generated every second. The real time ana...
Stream processors, developed for the stream programming model, perform well on media applications. I...
The stream programming paradigm aims to expose coarsegrained parallelism in applications that must p...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
Stream processing languages and stream processing engines have become more popu-lar as they emerged ...
Stream processing languages and stream processing engines have become more popular as they emerged f...
Stream programs represent an important class of high-performance computations. Defined by their reg...
Stream processing has a long history as a way of describing and implementing specific kinds of compu...
In this tutorial paper we present the results of recent research findings in the area of data stream...
Many application areas for embedded systems, such as DSP, media coding, and image processing, are ba...
Various research communities have independently arrived at stream processing as a programming model ...
We introduce RATE TYPES, a novel type system to reason about and optimize data-intensive programs. B...
Most automatic programming research has focused on programs which terminate and which produce output...
In this paper we study the timing aspects of the operation of stream-processing applications that ru...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
In the era of big data, an unprecedented amount of data is generated every second. The real time ana...
Stream processors, developed for the stream programming model, perform well on media applications. I...
The stream programming paradigm aims to expose coarsegrained parallelism in applications that must p...