A list of book releases compiled by Dr. Dobb's to keep you up-to-date on parallel programming and multicore technology.
CUDA by Example: An Introduction to General-Purpose GPU Programming
by Jason Sanders and Edward Kandrot
Now available in paperback, this book, written by two senior members of the CUDA software platform team, shows programmers how to employ this technology. CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of GPUs when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required–just the ability to program in a modestly extended version of C.
Host Your Web Site On The Cloud:
Amazon Web Services Made Easy: Amazon EC2 Made Easy
by Jeffrey Barr
This book is a step-by-step guide to hosting web sites on Amazon EC2. Authored by Amazon's Senior Manager of Cloud Computing Solutions, Jeffrey Barr, this book covers all aspects of best-practice cloud hosting; including file and database storage, server management, querying services, application management, performance and maintenance, scaling, and load balancing.
Bioinformatics: High Performance Parallel Computer Architectures
edited by Bertil Schmidt
Presenting key information about how to make optimal use of parallel architectures, this book:
- Describes algorithms and tools including pairwise sequence alignment, multiple sequence alignment, BLAST, motif finding, pattern matching, sequence assembly, hidden Markov models, proteomics, and evolutionary tree reconstruction
- Addresses GPGPU technology and the associated massively threaded CUDA programming model
- Reviews FPGA architecture and programming
- Presents several parallel algorithms for computing alignments on the Cell/BE architecture, including linear-space pairwise alignment, syntenic alignment, and spliced alignment
- Covers several effective techniques to fully exploit the computing capability of many-core CUDA-enabled GPUs to accelerate protein sequence database searching, multiple sequence alignment, and motif finding
- Explains a parallel CUDA-based method for correcting sequencing base-pair errors in HTSR data
Because the amount of publicly available sequence data is growing faster than single processor core performance speed, modern bioinformatics tools need to take advantage of parallel computer architectures. Beneficial to anyone actively involved in research and applications, this book helps you to get the most out of these tools and create optimal HPC solutions for bioinformatics.