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Parallel Computing for Bioinformatics and Computational Biology
Discover how to streamline complex bioinformatics applications with parallel computing This publication enables readers to handle more complex bioinformatics applications and larger and richer data sets. As the editor clearly shows, using powerful parallel computing tools can lead to significant breakthroughs in deciphering genomes, understanding genetic disease, designing customized drug therapies, and understanding evolution. A broad range of bioinformatics applications is covered with demonstrations on how each one can be parallelized to improve performance and gain faster rates of computation. Current parallel computing techniques and technologies are examined, including distributed comp...
Parallel Computing on Distributed Memory Multiprocessors
Advances in microelectronic technology have made massively parallel computing a reality and triggered an outburst of research activity in parallel processing architectures and algorithms. Distributed memory multiprocessors - parallel computers that consist of microprocessors connected in a regular topology - are increasingly being used to solve large problems in many application areas. In order to use these computers for a specific application, existing algorithms need to be restructured for the architecture and new algorithms developed. The performance of a computation on a distributed memory multiprocessor is affected by the node and communication architecture, the interconnection network ...
Algorithms and Computation
This volume presents the proceedings of the fourth annual International Symposium on Algorithms and Computation, held in Hong Kong in December 1993.Numerous selected papers present original research in such areas as design and analysis of algorithms, computational complexity, and theory of computation. Topics covered include: - automata, languages, and computability, - combinatorial, graph, geometric, and randomized algorithms, - networks and distributed algorithms, - VLSIand parallel algorithms, - theory of learning and robotics, - number theory and robotics. Three invited papers are also included.
Parallel Programming and Compilers
The second half of the 1970s was marked with impressive advances in array/vector architectures and vectorization techniques and compilers. This progress continued with a particular focus on vector machines until the middle of the 1980s. The major ity of supercomputers during this period were register-to-register (Cray 1) or memory-to-memory (CDC Cyber 205) vector (pipelined) machines. However, the increasing demand for higher computational rates lead naturally to parallel comput ers and software. Through the replication of autonomous processors in a coordinated system, one can skip over performance barriers due technology limitations. In princi ple, parallelism offers unlimited performance p...
Supercomputing Research Advances
Supercomputers are used for highly calculation-intensive tasks such as problems involving quantum mechanical physics, weather forecasting, climate research (including research into global warming), molecular modelling (computing the structures and properties of chemical compounds, biological macromolecules, polymers, and crystals), physical simulations (such as simulation of aeroplanes in wind tunnels, simulation of the detonation of nuclear weapons, and research into nuclear fusion), cryptanalysis, and the like. Major universities, military agencies and scientific research laboratories are heavy users. This book presents the latest research in the field from around the world.
Supercomputer Architecture
Supercomputers are the largest and fastest computers available at any point in time. The term was used for the first time in the New York World, March 1920, to describe "new statistical machines with the mental power of 100 skilled mathematicians in solving even highly complex algebraic problems. " Invented by Mendenhall and Warren, these machines were used at Columbia University'S Statistical Bureau. Recently, supercomputers have been used primarily to solve large-scale prob lems in science and engineering. Solutions of systems of partial differential equa tions, such as those found in nuclear physics, meteorology, and computational fluid dynamics, account for the majority of supercomputer ...
