Quantitative analysis of sequence alignment applications on multiprocessor architectures

The exponential growth of databases that contains biological information (such as protein and DNA data) demands great efforts to improve the performance of computational platforms. In this work we investigate how bioinformatics applications benefit from parallel architectures that combine different alternatives to exploit coarseand fine-grain parallelism. As a case of analysis we study the performance behavior of the Ssearch application that implements the Smith-Waterman algorithm, which is a dynamic programing approach that explores the similarity between a pair of sequences. The inherent large parallelism of the algorithm makes it ideal for architectures supporting multiple dimensions of parallelism (TLP, DLP and ILP). We study how this algorithm can take advantage of different parallel machines like the SGI Altix, IBM Power6, Cell BE machines and MareNostrum. Our results show that a share memory architecture like the PowerPC 970MP of Marenostrum can surpass a heterogeneous machin...

• Type: Conference
• Year: 2009
• Where: CF
• Authors: Friman Sánchez, Alex Ramírez, Mateo Valero
• Keywords: Applied Computing, Cell BE Machines, CF 2009, Coarseand fine-grain Parallelism, Inherent Large Parallelism