Developers increasingly use streaming languages to write applications that process large volumes of data with high throughput. Unfortunately, when picking which streaming language to use, they face a difficult choice. On the one hand, dynamically ...

At one level, this paper is about River, a virtual execution environment for stream processing. Stream processing is a paradigm well-suited for many modern data processing systems that ingest high-volume data streams from the real world, such as audio/...

Because multicore architectures have become the industry standard, programming abstractions for concurrent programming are of key importance. Stream programming languages facilitate application domains characterized by regular sequences of data, such as ...

Graphics processing units leverage on a large array of parallel processing cores to boost the performance of a specific streaming computation pattern frequently found in graphics applications. Unfortunately, while many other general purpose applications ...

We present a novel 2-approximation algorithm for deploying stream graphs on multicore computers and a stream graph transformation that eliminates bottlenecks. The key technical insight is a data rate transfer model that enables the computation of a "...

Stream programs represent an important class of high-performance computations. Defined by their regular processing of sequences of data, stream programs appear most commonly in the context of audio, video, and digital signal processing, though also in ...

A compressed-domain transformation is one that operates directly on the compressed format, rather than requiring conversion to an uncompressed format prior to processing. Performing operations in the compressed domain offers large speedups, as it ...

While multicore hardware has become ubiquitous, explicitly parallel programming models and compiler techniques for exploiting parallelism on these systems have noticeably lagged behind. Stream programming is one model that has wide applicability in the ...

Digital Signal Processing (DSP) is becoming increasingly widespread in portable devices. Due to harsh constraints on power, latency, and throughput in embedded environments, developers often appeal to signal processing experts to hand-optimize ...