Chiminey: Reliable Computing and Data Management Platform in the Cloud

The enabling of scientific experiments that are embarrassingly parallel, long running and data-intensive into a cloud-based execution environment is a desirable, though complex undertaking for many researchers. The management of such virtual environments is cumbersome and not necessarily within the core skill set for scientists and engineers. We present here Chiminey, a software platform that enables researchers to (i) run applications on both traditional high-performance computing and cloud-based computing infrastructures, (ii) handle failure during execution, (iii) curate and visualise execution outputs, (iv) share such data with collaborators or the public, and (v) search for publicly available data.Comment: Preprint, ICSE 201

IMP Science Gateway: from the Portal to the Hub of Virtual Experimental Labs in Materials Science

"Science gateway" (SG) ideology means a user-friendly 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 its practical MD applications in materials science, physics, chemistry, biology, and nanotechnologies.Comment: 6 pages, 5 figures, 3 tables; 6th International Workshop on Science Gateways, IWSG-2014 (Dublin, Ireland, 3-5 June, 2014). arXiv admin note: substantial text overlap with arXiv:1404.545

HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges

High Performance Computing (HPC) clouds are becoming an alternative to on-premise clusters for executing scientific applications and business analytics services. Most research efforts in HPC cloud aim to understand the cost-benefit of moving resource-intensive applications from on-premise environments to public cloud platforms. Industry trends show hybrid environments are the natural path to get the best of the on-premise and cloud resources---steady (and sensitive) workloads can run on on-premise resources and peak demand can leverage remote resources in a pay-as-you-go manner. Nevertheless, there are plenty of questions to be answered in HPC cloud, which range from how to extract the best performance of an unknown underlying platform to what services are essential to make its usage easier. Moreover, the discussion on the right pricing and contractual models to fit small and large users is relevant for the sustainability of HPC clouds. This paper brings a survey and taxonomy of efforts in HPC cloud and a vision on what we believe is ahead of us, including a set of research challenges that, once tackled, can help advance businesses and scientific discoveries. This becomes particularly relevant due to the fast increasing wave of new HPC applications coming from big data and artificial intelligence.Comment: 29 pages, 5 figures, Published in ACM Computing Surveys (CSUR