Towards a lightweight generic computational grid framework for biological research

Background: An increasing number of scientific research projects require access to large-scale computational resources. This is particularly true in the biological field, whether to facilitate the analysis of large high-throughput data sets, or to perform large numbers of complex simulations – a characteristic of the emerging field of systems biology. Results: In this paper we present a lightweight generic framework for combining disparate computational resources at multiple sites (ranging from local computers and clusters to established national Grid services). A detailed guide describing how to set up the framework is available from the following URL: http://igrid-ext.cryst.bbk.ac.uk/portal_guide/. Conclusion: This approach is particularly (but not exclusively) appropriate for large-scale biology projects with multiple collaborators working at different national or international sites. The framework is relatively easy to set up, hides the complexity of Grid middleware from the user, and provides access to resources through a single, uniform interface. It has been developed as part of the European ImmunoGrid project

Evaluation of CO2 and Carbonated Water EOR for Chalk Fields

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Open-architecture Implementation of Fragment Molecular Orbital Method for Peta-scale Computing

We present our perspective and goals on highperformance computing for nanoscience in accordance with the global trend toward "peta-scale computing." After reviewing our results obtained through the grid-enabled version of the fragment molecular orbital method (FMO) on the grid testbed by the Japanese Grid Project, National Research Grid Initiative (NAREGI), we show that FMO is one of the best candidates for peta-scale applications by predicting its effective performance in peta-scale computers. Finally, we introduce our new project constructing a peta-scale application in an open-architecture implementation of FMO in order to realize both goals of highperformance in peta-scale computers and extendibility to multiphysics simulations.Comment: 6 pages, 9 figures, proceedings of the 2nd IEEE/ACM international workshop on high performance computing for nano-science and technology (HPCNano06

Massively parallel computing on an organic molecular layer

Current computers operate at enormous speeds of ~10^13 bits/s, but their principle of sequential logic operation has remained unchanged since the 1950s. Though our brain is much slower on a per-neuron base (~10^3 firings/s), it is capable of remarkable decision-making based on the collective operations of millions of neurons at a time in ever-evolving neural circuitry. Here we use molecular switches to build an assembly where each molecule communicates-like neurons-with many neighbors simultaneously. The assembly's ability to reconfigure itself spontaneously for a new problem allows us to realize conventional computing constructs like logic gates and Voronoi decompositions, as well as to reproduce two natural phenomena: heat diffusion and the mutation of normal cells to cancer cells. This is a shift from the current static computing paradigm of serial bit-processing to a regime in which a large number of bits are processed in parallel in dynamically changing hardware.Comment: 25 pages, 6 figure

DSMC investigation of rarefied gas flow through diverging micro- and nanochannels

Direct simulation Monte Carlo (DSMC) method with simplified Bernoulli-trials (SBT) collision scheme has been used to study the rarefied pressure-driven nitrogen flow through diverging microchannels. The fluid behaviours flowing between two plates with different divergence angles ranging between 0$^{\circ}$ to 17$^{\circ}$ are described at different pressure ratios (1.5${\le}{\prod}{\le}$2.5) and Knudsen numbers (0.03${\le}$Kn${\le}$12.7). The primary flow field properties, including pressure, velocity, and temperature, are presented for divergent microchannels and are compared with those of a microchannel with a uniform cross-section. The variations of the flow field properties in divergent microchannels, which are influenced by the area change, the channel pressure ratio and the rarefication are discussed. The results show no flow separation in divergent microchannels for all the range of simulation parameters studied in the present work. It has been found that a divergent channel can carry higher amounts of mass in comparison with an equivalent straight channel geometry. A correlation between the mass flow rate through microchannels, the divergence angle, the pressure ratio, and the Knudsen number has been suggested. The present numerical findings prove the occurrence of Knudsen minimum phenomenon in micro- and Nano- channels with non-uniform cross-sections.Comment: Accepted manuscript; 25 Pages and 11 Figures; "Microfluidics and Nanofluidics

Foam EOR Processes

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