Development of GPU-Accelerated Algorithms for Protein Structure Prediction

EasyChair Preprint 14906

Abstract

The accurate prediction of protein structures is crucial for understanding biological functions and developing therapeutics. Traditional computational methods for protein structure prediction are often limited by their computational complexity and time constraints. This study explores the development and application of GPU-accelerated algorithms to enhance the efficiency and accuracy of protein structure prediction. By leveraging the parallel processing capabilities of GPUs, we propose novel algorithms that significantly reduce computational time while maintaining high precision in structural predictions. Our approach integrates advanced machine learning techniques with GPU acceleration to handle large-scale protein data and complex structural models. The results demonstrate a substantial improvement in predictive performance and computational efficiency compared to conventional methods. This work represents a significant advancement in the field of computational biology and opens new avenues for real-time protein structure analysis.

Keyphrases: GPU acceleration, computational biology, machine learning, protein structure prediction

@booklet{EasyChair:14906,
  author    = {Adaan Ahsun},
  title     = {Development of GPU-Accelerated Algorithms for Protein Structure Prediction},
  howpublished = {EasyChair Preprint 14906},
  year      = {EasyChair, 2024}}