study parallel algorithms multiple de al neama mohammed (6 résultats)

Paperback. Etat : Brand New. 180 pages. 8.66x5.91x0.41 inches. In Stock.

Taschenbuch. Etat : Neu. A Study of Parallel Algorithms for Multiple Sequence Alignment | Mohammed Wajid Al-Neama | Taschenbuch | 180 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659883781 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. Traditional approaches to sequence analysis techniques are expensive in terms of time and memory. This leads to the use of HPC which is a widely used method to improve performance. The emergence of accelerator technologies such as multi-core architecture has made it possible to achieve an excellent improvement in execution time for many bioinformatics applications, compared to current general-purpose platforms. Therefore, using multi-cores to solve sequence analysis problems is a promising and challenging research field because large-scale computational bioinformatics problems can benefit greatly from this kind of processing power. Providing a comparison between the parallel methods available for MSA. Guiding biologists to the most convenient tool to align multiple sequences. Designing and implementing a new parallel and effective method to align multiple sequences using both multi-cores and cluster systems. 180 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Al-Neama Mohammed WajidMohammed Wajid Al-Neama is a lecturer of Computer Science. Teaching and training more than 10 years at University of Mosul, Iraq. PhD in Mathematics Computing, from Al-Azhar University. His main research intere.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. Traditional approaches to sequence analysis techniques are expensive in terms of time and memory. This leads to the use of HPC which is a widely used method to improve performance. The emergence of accelerator technologies such as multi-core architecture has made it possible to achieve an excellent improvement in execution time for many bioinformatics applications, compared to current general-purpose platforms. Therefore, using multi-cores to solve sequence analysis problems is a promising and challenging research field because large-scale computational bioinformatics problems can benefit greatly from this kind of processing power. Providing a comparison between the parallel methods available for MSA. Guiding biologists to the most convenient tool to align multiple sequences. Designing and implementing a new parallel and effective method to align multiple sequences using both multi-cores and cluster systems.Books on Demand GmbH, Überseering 33, 22297 Hamburg 180 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. Traditional approaches to sequence analysis techniques are expensive in terms of time and memory. This leads to the use of HPC which is a widely used method to improve performance. The emergence of accelerator technologies such as multi-core architecture has made it possible to achieve an excellent improvement in execution time for many bioinformatics applications, compared to current general-purpose platforms. Therefore, using multi-cores to solve sequence analysis problems is a promising and challenging research field because large-scale computational bioinformatics problems can benefit greatly from this kind of processing power. Providing a comparison between the parallel methods available for MSA. Guiding biologists to the most convenient tool to align multiple sequences. Designing and implementing a new parallel and effective method to align multiple sequences using both multi-cores and cluster systems.