Abstract
This chapter focuses on the problem of more complex systems starting from those made of few atoms (mainly four) to move toward those made of several atoms and/or molecules. It starts from discussing the related formulation of the interactions for increasingly complex systems and continues by defining the quantities to be computed, describing some of the associated computational techniques and selecting the observables to simulate. Further considerations are made on the techniques used to describe the dynamics of large systems. Finally, the impact of the evolution of computer hardware and software on the progress of collaborative molecular science simulations is discussed. References to the open science and service-oriented scenario in computational activities targeting areas of societal relevance are also given.
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- 1.
High-performance computing (HPC) refers presently to machines exhibiting performances at the level of exascale based on massive parallel computing. Typically, HPC technologies require large investments for their establishing, specialized staff for their management, and highly skilled programmers for the exploitation of their performances.
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High-throughput computing (HTC) refers to machines exhibiting an efficient execution of a large number of loosely-coupled tasks. HTC systems are independent sequential jobs that can be individually scheduled on many different computing resources across multiple administrative boundaries. HTC systems achieve this using various grid computing (GC) technologies and techniques. In Europe, a strong impulse to HTC has been given by the last Framework Programmes, especially as a support to the High Energy Physics transnational community initiatives, by funding several international collaborative projects like DATATAG (http://datatag.web.cern.ch/datatag/), EGEE-I-II-III (http://www.egee.eu), WLCG (http://wlcg.web.cern.ch/), EGI-Inspire (https://www.egi.eu/about/egi-inspire/), and EGI-Engage (https://www.egi.eu/about/egi-engage/).
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VOs are groups of researchers bearing similar scientific interests and requirements being able to work collaboratively with other members. VO members share resources (e.g., data, software, expertise, CPU, and storage space) regardless of their geographical location and join a VO to the end of using the grid computing resources provided by the resource provider. According to the VO’s requirements and goals, EGI (European Grid Infrastructure) [125] provides authentication, job allocation, activities monitoring support, services and tools allowing them to make the most of their resources.
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VRCs are self-organized research communities which give individuals within their community a clear mandate to represent the interests of their research field within the EGI ecosystem. They can include one or more VOs and act as the main communication channel between the researchers they represent and EGI.
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VREs are e-infrastructures used for e-science operations that maximize coordination and identify commonalities across the European research infrastructures as well as common solutions to problems, which can then be implemented by the involved communities thanks to synergies across member states, while minimizing overlap of effort. VREs can automate aspects of data recording, including metadata, using customisable workflows.
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SUMO-CHEM: “Supporting Research in computational and experimental chemistry via Research Infrastructure” submitted to the Horizon 2020 framework call H2020-INFRAIA-2016-2017 (Integrating and opening research infrastructures of European interest) by Gabor Terstyanszky. Topic: INFRAIA-02-2017 Type of action: RIA (Research and Innovation action,) Proposal number: 731010-1. Published on the NEWS issue of the e-magazine VIRT&L-COMM of Sept. 2016 http://www.hpc.unipg.it/ojs/index.php/virtlcomm/issue/view/17. As from its abstract of the submitted proposal, SUMO-CHEM is an open molecular science initiative that “will integrate research facilities and infrastructures with computing and data resources into the SUMO-CHEM RI to enable joint research involving computational and experimental chemistry and other research communities. This RI will have an open architecture to allow its extension with further research facilities and resources to be used by the chemistry and other communities. The SUMO-CHEM RI will allow researchers and developers to run industrial simulations and scientific experiments using European, regional and national research facilities and e-infrastructure resources through an intuitive and seamless virtual access considering different levels of their expertise and skills. The major innovation of the project will be in management of scientific data covering the whole life cycle of data using metadata, ontologies, and provenance based on advanced data and computing services. SUMO-CHEM will enable and support multidisciplinary research in cooperation with ESFRI and other major research initiatives to address climate and energy societal challenges.”
Although positively evaluated for the idea of connecting experimental and computational chemistry communities and infrastructures, for its capacity to go beyond the state of the art for the proper selection of use-cases and for its multidisciplinarity and development of networking activities, the proposal was not funded.
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The acronym B2xx means “Business to xx” where xx is the beneficiary of the service.
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As illustrated in Fig. 5.12 GriF is a framework made of two Java servers (YC and YR the Consumer and the Registry servers) and one Java client (YP the Provider). The entry points to the computational platforms are the User Interfaces which are able to capture, out of the data supplied by the monitoring sensors of the DCI, the information relevant to properly manage the computational applications of interest and articulate them in sequential, concurrent or alternative quality paths by adopting a service-oriented architecture (SOA) and Web Services. This allows at the same time the guided search of the compute resources on the DCI and the evaluation of the quality of the users (QoU). The computational services provided, are analyzed and used to compose the submission, the monitoring, and the results recollection of molecular science simulations.
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Laganà, A., Parker, G.A. (2018). Complex Reactive Applications: A Forward Look to Open Science. In: Chemical Reactions. Theoretical Chemistry and Computational Modelling. Springer, Cham. https://doi.org/10.1007/978-3-319-62356-6_5
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DOI: https://doi.org/10.1007/978-3-319-62356-6_5
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