Jan R. Frigo

Learn More
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)
—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)
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)
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)
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)
Compute performance and algorithm design are key problems of image processing and scientific computing in general. For example, imaging spectrometers are capable of producing data in hundreds of spectral bands with millions of pixels. These data sets show great promise for remote sensing applications, but require new and computationally intensive(More)
  • 1