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However, it is not a trivial task to take advantage of the potential performance that these platforms provide to the scientific community. In this task, we develop scientific application from different fields such as linear algebra, system biology, natural computing, image processing, etc. On these emergent platforms, providing insight into the peculiarities of their programming models and architectures. Currently, we are researching in applying those models to challenging problems, mainly derived from Bioinformatics.
Our studies began with a performance study of the GPU as general purpose computing device, providing some insights into the peculiarities of CUDA programming model [Cecilia][Ceciliaa]. In addition, we discuss alternative ways of computation inspired on natural computing and their efficient design on GPUs. Currently, we have worked on two of those models: Performance Study and Contributions. Conference on Parallel Computing ParCo Lyon, France, pp , Briefings in Bioinformatics, Vol. In biomedical research, experimentation can be unfeasible in relevant study cases due, among other factors, to the intrinsic complexity of nature.
Theoretical and computational methods jointly with biophysical and biochemical modeling can overcome these limitations providing new understanding and solutions for world health problems. Nevertheless, they need to process huge amounts of data with high accuracy and this can be a serious limitation for the applicability of bioinformatics methods. Our main objectives are related with the development, implementation and exploitation of bioinformatics applications in massively parallel architectures like GPUs and Supercomputers, its experimental validation, and its application to relevant world health problems.
Accelerating multiple target drug screening on GPUs. Fast parallel solvent accessible surface area calculation on GPUs and application to drug discovery and molecular visualization.
Architecture of Massively Parallel Microprocessor Systems (Computer Architecture) [Patrick Stakem] on donnsboatshop.com *FREE* shipping on qualifying offers. By the Series: Computer Architecture (Book 9); Paperback: pages; Publisher. 4- and 8-bit Microprocessors, Architecture and History. . Architecture of Massively Parallel Microprocessor Systems (Computer Architecture Book 9) Jan
Implementation of an effective non-bonded interactions kernel for biomolecular simulations on the Cell processor. Volume of Lecture Notes in Informatics, Method and system for determining the solvent accessible surface area and its derivatives of a molecule.
European Patent Application Cubesat Engineering Space Book 1 Feb 02, Available for download now. Interplanetary Cubesats Mar 05, How to fly a Cubesat Cubesats Book 2 Feb 03, Graphics Processing Units, an overview.
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He has researched the Industrial Revolution era in Western Maryland, the conjunction of the railroads, the canal, and the National Road. He was able to visit Millholland's Victorian mansion in Cumberland, and photographed the T. Teramac is a massively parallel experimental computer built at Hewlett-Packard Laboratories to investigate a wide range of different computational architectures. The impact of parallelism, which is defined as the number of bits involved in the parallel adding, is evaluated based on the RS array simulations. Abstract Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies.
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Learn more at Author Central. Popularity Popularity Featured Price: Low to High Price: High to Low Avg. Cubesat Engineering Space Book 1 Feb 02, Available for download now. Interplanetary Cubesats Mar 05, How to fly a Cubesat Cubesats Book 2 Feb 03, Graphics Processing Units, an overview. Computer Architecture Book 16 Mar 09, Computer Architecture Book 1 Jun 02, A Resource Guide for Educators Aug 29, Provide feedback about this page.