VLSI array processors
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Architectures for high performance image procesing: the future
Journal of Systems Architecture: the EUROMICRO Journal - Special issue on parallel image proccesing (PIP)
DISCWorld: an environment for service-based matacomputing
Future Generation Computer Systems - Special issue on metacomputing
Massively parallel computing using commodity components
Parallel Computing - Parallel computing on clusters of workstations
Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
Journal of Systems Architecture: the EUROMICRO Journal
MODTRAN on supercomputers and parallel computers
Parallel Computing
Systolic Parallel Processing
A software architecture for user transparent parallel image processing
Parallel Computing - Parallel computing in image and video processing
Optimizing parallel performance of unstructured volume rendering for the Earth Simulator
Parallel Computing - Parallel graphics and visualisation
Parallel Computing on Heterogeneous Networks
Parallel Computing on Heterogeneous Networks
A distributed spectral-screening PCT algorithm
Journal of Parallel and Distributed Computing
Computer Architecture: A Quantitative Approach
Computer Architecture: A Quantitative Approach
Distributed frameworks and parallel algorithms for processing large-scale geographic data
Parallel Computing - Special issue: High performance computing with geographical data
A dynamic earth observation system
Parallel Computing - Special issue: High performance computing with geographical data
Hyperspectral Imaging: Techniques for Spectral Detection and Classification
Hyperspectral Imaging: Techniques for Spectral Detection and Classification
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
On performance analysis of heterogeneous parallel algorithms
Parallel Computing
IEEE Micro
On-Board Partial Run-Time Reconfiguration for Pico-Satellite Constellations
AHS '06 Proceedings of the first NASA/ESA conference on Adaptive Hardware and Systems
Commodity cluster-based parallel processing of hyperspectral imagery
Journal of Parallel and Distributed Computing
A robust framework for real-time distributed processing of satellite data
Journal of Parallel and Distributed Computing
HeteroMPI: Towards a message-passing library for heterogeneous networks of computers
Journal of Parallel and Distributed Computing
Efficient FPGA implementation of DWT and modified SPIHT for lossless image compression
Journal of Systems Architecture: the EUROMICRO Journal
High Performance Computing in Remote Sensing
High Performance Computing in Remote Sensing
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
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Advances in sensor technology are revolutionizing the way remotely sensed data is collected, managed and analyzed. The incorporation of latest-generation sensors to airborne and satellite platforms is currently producing a nearly continual stream of high-dimensional data, and this explosion in the amount of collected information has rapidly created new processing challenges. For instance, hyperspectral signal processing is a new technique in remote sensing that generates hundreds of spectral bands at different wavelength channels for the same area on the surface of the Earth. Many current and future applications of remote sensing in Earth science, space science, and soon in exploration science will require (near) real-time processing capabilities. In recent years, several efforts have been directed towards the incorporation of high-performance computing (HPC) systems and architectures in remote sensing missions. With the aim of providing an overview of current and new trends in parallel and distributed systems for remote sensing applications, this paper explores three HPC-based paradigms for efficient implementation of the Pixel Purity Index (PPI) algorithm, available from the popular Kodak's Research Systems ENVI software package, as a representative case study for demonstration purposes. Several different parallel programming techniques are used to improve the performance of the PPI on a variety of parallel platforms, including a set of message passing interface (MPI)-based implementations on a massively parallel Beowulf cluster at NASA's Goddard Space Flight Center in Maryland and on a variety of heterogeneous networks of workstations at University of Maryland; a Handel-C implementation of the algorithm on a Virtex-II field programmable gate array (FPGA); and a compute unified device architecture (CUDA)-based implementation on graphical processing units (GPUs) of NVidia. Combined, these parts deliver an excellent snapshot of the state-of-the-art in those areas, and offer a thoughtful perspective on the potential and emerging challenges of adapting HPC systems to remote sensing problems.