Bioinformatics: High Performance Parallel Computer Architectures(Embedded Multi-Core Systems)

New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data. This expansion of biological databases established the need for new ways to harness and apply the astounding amount of available genomic information and convert it into substantive biological

Table of Contents:
Algorithms for Bioinformatics.Introduction to GPGPUs and Massively Threaded Programming. FPGA: Architecture and Programming. Parallel Algorithms for Alignments on the Cell BE. Orchestrating the Phylogenetic Likelihood Function on Emerging Parallel Architectures. Parallel Bioinformatics Algorithms for CUDA-enabled GPUs. CUDA Error Correction Method for High-Throughput Short-Read Sequencing Data. FPGA Acceleration of Seeded Similarity Searching. Seed-Based Parallel Protein Sequence Comparison Combining Multithreading, GPU, and FPGA Technologies. Database Searching with Profi le Hidden Markov Models on Reconfi gurable and Many-Core Architectures. COPACOBANA: A Massively Parallel FPGA-Based Computer Architecture. Accelerating String Set Matching for Bioinformatics Using FPGA Hardware. Reconfigurable Neural System and its Application to Dimeric Protein Binding Site Identification. Parallel FPGA Search Engine for Protein Identification. Index.

About the Author :
Bertil Schmidt is Associate Professor at the School of Computer Engineering at Nanyang Technological University (NTU), Singapore. Prior to that, he was faculty member at the University of New South Wales and Senior Researcher at the University of Melbourne, Australia. At NTU he also held appointments as Program Director M.Sc. in Bioinformatics and Deputy Director of BMERC. Before coming to Singapore, he held research appointments at the Karlsruhe Institute of Technology (KIT) and RWTH Aachen. Bertil has been involved in the design and implementation of parallel algorithms and architectures for over a decade. He has worked extensively with fine-grained (e.g. GPUs, FPGAs, Cell BE), coarse-grained (clusters, grids) as well as hybrid parallel architectures. He has successfully applied these technologies to various domains including bioinformatics, image processing, multimedia video compression, and cryptography. He has published more than 35 journal papers in leading journals such as Journal of VLSI Signal Processing, Microelectronic Engineering, IEEE Transactions on Circuits and Systems II, IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on IT in Biomedicine, Journal of Parallel and Distributed Computing, Parallel Computing, Concurrency and Computation: Practice and Experience, Future Generation Computer Systems, Bioinformatics, BMC Bioinformatics, Autoimmunity, and Computer Physics Communications.