GPU Acceleration Techniques for Analyzing the Photochemical Properties of Nanoparticles in Bioinformatics Frameworks

EasyChair Preprint 14999

Abstract

The integration of nanoparticles in biomedical applications requires precise analysis of their photochemical properties. However, computational simulations of these properties are computationally intensive, hindering rapid advancement. This study explores the implementation of Graphics Processing Unit (GPU) acceleration techniques to enhance computational efficiency in analyzing nanoparticle photochemistry within bioinformatics frameworks.

By leveraging GPU parallel processing capabilities, we developed optimized algorithms for photochemical property simulations, achieving significant speedup over traditional Central Processing Unit (CPU)-based methods. Our GPU-accelerated framework demonstrated substantial performance gains in computing photochemical properties, such as absorption spectra and energy transfer rates.

Keyphrases: Biomedical applications, GPU acceleration, bioinformatics frameworks, computational simulations, nanoparticle photochemistry

@booklet{EasyChair:14999,
  author    = {Abey Litty},
  title     = {GPU Acceleration Techniques for Analyzing the Photochemical Properties of Nanoparticles in Bioinformatics Frameworks},
  howpublished = {EasyChair Preprint 14999},
  year      = {EasyChair, 2024}}