Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
GPU parallelism for real applications can achieve enormous performance gain. CPU-GPU Communication is one of the major bottlenecks that limit this performance gain. Among several libraries developed so far to optimize this communication, DyManD (Dynamically Managed Data) provides better communication optimization strategies and achieves better performance on a single GPU. Smith-Waterman is a well-known algorithm in the field of computational biology for finding functional similarities in a protein database. CUDA implementation of this algorithm speeds up the process of sequence matching in the protein database.

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