Efficient memory management for cellular Monte Carlo algorithm

Julien Branlard, S. J. Aboud, Stephen Goodnick, Marco Saraniti

Research output: Contribution to journalArticlepeer-review


Data compression techniques aimed to the reduction of the memory usage of the Cellular Monte Carlo (CMC) approach are presented in this work. Two approaches have been investigated and implemented, resulting in memory savings of 25 and 50% of computer random access memory (RAM). The loss of precision due to the proposed techniques is measured, and its consequences are studied. The validity and accuracy of the results obtained with compression is verified and robustness is tested on various semiconductor materials. Some applications of the proposed approach are discussed as well.

Original languageEnglish (US)
Pages (from-to)323-327
Number of pages5
JournalJournal of Computational Electronics
Issue number3-4
StatePublished - Oct 2004


  • Compression algorithms
  • Full-band particle-based simulation
  • Monte Carlo techniques

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Modeling and Simulation
  • Electrical and Electronic Engineering


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