Cost-effective parallel processing for remote sensing applications

Hyoung Joong Kim, Hyung Soo Kim

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)


Network-based computing with cluster of personal computers or workstations recently has become an important and successful technique. Network-based computing enables fast computation and resolves short of storage with computers on the desks. Cluster of inexpensive computers offers them aggregated computing power and storage to challenge very large-scale problems. Iterative solvers are used for the large sparse linear systems. Preconditioners accelerate the rate of convergence of the iterative solvers. However, parallelization of preconditioners is far from satisfaction so far. Thus, the simplest diagonal scaling is a good alternative for improved convergence and easy parallelization. In order to reduce communication overhead, a data compression technique is considered. Data communication time can be reduced at the cost of convergence rate. MATLAB simulation result is given in this paper. This method is effective to cluster of computers connected through slow networks.

Original languageEnglish
Number of pages3
Publication statusPublished - 1996
Externally publishedYes
EventProceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4) - Lincoln, NE, USA
Duration: 1996 May 281996 May 31


OtherProceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4)
CityLincoln, NE, USA

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)


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