Summary ‘Science gateway’ (SG) ideology means a user‐friendly intuitive interface between scientists (or scientific communities) and different software components + various distributed computing infrastructures (DCIs), where researchers can focus on their scientific goals and less on the peculiarities of software/DCI. G.V.Kurdyumov Institute for Metal Physics ‘IMP Science Gateway Portal’ (http://scigate.imp.kiev.ua) is presented for complex workflow management and integration of distributed computing resources (like clusters, service grids, desktop grids, and clouds). It is created on the basis of Web Service – Parallel Grid Run‐time and Application Development Environment (WS‐PGRADE) and gUSE (grid and cloud User Support Environment) technologies, where WS‐PGRADE is designed for science workflow operation and gUSE — for smooth integration of available resources for parallel and distributed computing in various heterogeneous DCIs. Some use cases (scientific workflows) are considered for molecular dynamics simulations of complex behavior of various nanostructures. The modular approach allows scientists to use SG portals as research hubs of various virtual experimental labs in the context of practical applications in material science, physics, and nanotechnologies. In addition, workflows and their components are proposed to be used as Lego‐style construction units for learning modules of various scale by duration, complexity, targeted audience, and so on. These workflows can be used also in e‐Learning infrastructures as constituent elements of learning hubs for the management of learning content, tools, resources, and users in the regular, vocational, lifelong, and informal learning. Copyright © 2015 John Wiley & Sons, Ltd.

Science gateway" (SG) ideology means a userfriendly intuitive interface between scientists (or scientific communities) and different software components + various distributed computing infrastructures (DCIs) (like grids, clouds, clusters), where researchers can focus on their scientific goals and less on peculiarities of software/DCI. "IMP Science Gateway Portal" (http://scigate.imp.kiev.ua) for complex workflow management and integration of distributed computing resources (like clusters, service grids, desktop grids, clouds) is presented. It is created on the basis of WS-PGRADE and gUSE technologies, where WS-PGRADE is designed for science workflow operation and gUSE -for smooth integration of available resources for parallel and distributed computing in various heterogeneous distributed computing infrastructures (DCI). The typical scientific workflows with possible scenarios of its preparation and usage are presented. Several typical use cases for these science applications (scientific workflows) are considered for molecular dynamics (MD) simulations of complex behavior of various nanostructures (nanoindentation of graphene layers, defect system relaxation in metal nanocrystals, thermal stability of boron nitride nanotubes, etc.). The user experience is analyzed in the context of its practical applications for MD simulations in materials science, physics and nanotechnologies with available heterogeneous DCIs. In conclusion, the "science gateway" approach -workflow manager (like WS-PGRADE) + DCI resources manager (like gUSE)-gives opportunity to use the SG portal (like "IMP Science Gateway Portal") in a very promising way, namely, as a hub of various virtual experimental labs (different software components + various requirements to resources) in the context of practical MD applications in materials science, physics, and nanotechnologies.

The distributed computing infrastructure (DCI) on the basis of BOINC and EDGeS-bridge technologies for high-performance distributed computing is used for porting the sequential molecular dynamics (MD) application to its parallel version for DCI with Desktop Grids (DGs) and Service Grids (SGs). The actual metrics of the working DG-SG DCI were measured, and the normal distribution of host performances, and signs of log-normal distributions of other characteristics (CPUs, RAM, and HDD per host) were found. The practical feasibility and high efficiency of the MD simulations on the basis of DG-SG DCI were demonstrated during the experiment with the massive MD simulations for the large quantity of aluminum nanocrystals (∼ 10 2 -10 3 ). Statistical analysis (Kolmogorov-Smirnov test, moment analysis, and bootstrapping analysis) of the defect density distribution over the ensemble of nanocrystals had shown that change of plastic deformation mode is followed by the qualitative change of defect density distribution type over ensemble of nanocrystals. Some limitations (fluctuating performance, unpredictable availability of resources, etc.) of the typical DG-SG DCI were outlined, and some advantages (high efficiency, high speedup, and low cost) were demonstrated. Deploying on DG DCI allows to get new scientific quality from the simulated quantity of numerous configurations by harnessing sufficient computational power to undertake MD simulations in a wider range of physical parameters (configurations) in a much shorter timeframe.

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