Jan R. Frigo

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Both for offline searches through large data archives and for onboard computation at the sensor head, there is a growing need for ever-more rapid processing of remote sensing data. For many algorithms of use in remote sensing, the bulk of the processing takes place in an " inner loop " with a large number of simple operations. For these algorithms, dramatic(More)
Cellular computing architectures represent an important class of computation that are characterized by simple processing elements, local interconnect and massive parallelism. These architectures are a good match for many image and video processing applications and can be substantially accelerated with Reconfigurable Computers. We present a flexible software(More)
—Typically, for energy efficiency and scalability purposes , sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones.(More)
In this paper, we discuss a low power embedded sensor node architecture we are developing for distributed sensor network systems deployed in a natural environment. In particular, we examine the sensor node for energy efficient <i>processing-at-the-sensor</i>. We analyze the following modes of operation; event detection, data acquisition, and data processing(More)
The authors propose a run-time re-configurable architecture for local neighborhood image processing. Discussion of how the new architecture can offer improved flexibility to the developer. The authors show that for a satellite image feature extraction application, our architecture, implemented on Stratix II and Virtex 2 field programmable gate arrays,(More)
Date The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. Thesis directed by Prof. Dirk Grunwald This research investigates a reconfigurable processing approach to a signal processing application that runs(More)
We propose a run-time re-configurable parametric architecture (fabric) for local neighborhood image processing. The proposed architecture is composed of polymorphous cells where each cell accesses neighborhood data from a local cell memory, and executes a neighborhood function sequentially. The architecture is flexible since different neighborhood functions(More)
sc2 is a new, open source implementation of the Streams-C language and compiler [1] that uses the Stanford SUIF 1.3 compiler infrastructure [2]. sc2 has been improved through various standard compiler optimizations and retargetted to Xilinx Virtex technology. The sc2 compiler passes are freely available for non-commercial use in source form from Los Alamos(More)
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