The LifeV library: engineering mathematics beyond the proof of concept

LifeV is a library for the finite element (FE) solution of partial differential equations in one, two, and three dimensions. It is written in C++ and designed to run on diverse parallel architectures, including cloud and high performance computing facilities. In spite of its academic research nature, meaning a library for the development and testing of new methods, one distinguishing feature of LifeV is its use on real world problems and it is intended to provide a tool for many engineering applications. It has been actually used in computational hemodynamics, including cardiac mechanics and fluid-structure interaction problems, in porous media, ice sheets dynamics for both forward and inverse problems. In this paper we give a short overview of the features of LifeV and its coding paradigms on simple problems. The main focus is on the parallel environment which is mainly driven by domain decomposition methods and based on external libraries such as MPI, the Trilinos project, HDF5 and ParMetis. Dedicated to the memory of Fausto Saleri.Comment: Review of the LifeV Finite Element librar

Computational Physics on Graphics Processing Units

The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various different algorithms. In this review, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics, and on quantum simulations for electronic structure calculations using the density functional theory, wave function techniques, and quantum field theory.Comment: Proceedings of the 11th International Conference, PARA 2012, Helsinki, Finland, June 10-13, 201

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Non regression testing for the JOREK code

Non Regression Testing (NRT) aims to check if software modifications result in undesired behaviour. Suppose the behaviour of the application previously known, this kind of test makes it possible to identify an eventual regression, a bug. Improving and tuning a parallel code can be a time-consuming and difficult task, especially whenever people from different scientific fields interact closely. The JOREK code aims at investing Magnetohydrodynamic (MHD) instabilities in a Tokamak plasma. This paper describes the NRT procedure that has been tuned for this simulation code. Automation of the NRT is one keypoint to keeping the code healthy in a source code repository.Comment: No. RR-8134 (2012

Software tools for management of conjunctive use of surface- and ground-water in the rural environment: integration of the Farm Process and the Crop Growth Module in the FREEWAT platform

Abstract The coordinated use of surface- and ground-water over time and space as two components of a single irrigation system is of outmost importance in many rural areas of the world, in order to assure crop production sustainability, to restore ongoing and to prevent future issues related to freshwater quality and quantity mismanagement/deterioration. New technological solutions, such as GIS-integrated simulation models, may provide reliable tools in order to evaluate impacts in space and time and to properly manage conjunctive use of surface water and groundwater and water-constrained agricultural production. After presenting the common open source simulation programs for dealing with conjunctive use, we discuss and present the integration of the Farm Process (FMP; embedded in the USGS's MODFLOW One-Water Hydrologic Model) coupled to a Crop Growth Module (CGM) within the open source and public domain QGIS-integrated FREEWAT platform. Using FMP in FREEWAT gains the benefit of the spatial environment and data management tools of a GIS solution, and to perform proper analysis of dynamically integrated terms of the hydrological cycle, to effectively balance crop water demand and supply from different sources of water. A simple hypothetic, yet realistic, application of the proposed approach with FMP and CGM is presented, simulating the yield of irrigated sunflower at harvest in a Mediterranean area. Results provide an insight on the potential exploitation of the developed solution, including, but not limited, to: quantitative temporal analysis of irrigation water sources, detailed analysis of evaporation and transpiration terms (from irrigation, groundwater or rainfall). The coupling of FMP with CGM to estimate crop yield at harvest provides further management tools when dealing with crop productivity. In the simulated case study, the analysis of the water balance terms allowed identifying the relevance of the groundwater contribution to ETc-act, highlighting the role of natural root uptake. The proposed solution is thought to be deployed by water authorities, large farms and public/private companies managing irrigation areas. The use of these tools calls for dedicated capacity building to boost digitalization in the agricultural water sector in order to achieve data-based agricultural water management

Albany: Using Component-based Design to Develop a Flexible, Generic Multiphysics Analysis Code

Abstract: Albany is a multiphysics code constructed by assembling a set of reusable, general components. It is an implicit, unstructured grid finite element code that hosts a set of advanced features that are readily combined within a single analysis run. Albany uses template-based generic programming methods to provide extensibility and flexibility; it employs a generic residual evaluation interface to support the easy addition and modification of physics. This interface is coupled to powerful automatic differentiation utilities that are used to implement efficient nonlinear solvers and preconditioners, and also to enable sensitivity analysis and embedded uncertainty quantification capabilities as part of the forward solve. The flexible application programming interfaces in Albany couple to two different adaptive mesh libraries; it internally employs generic integration machinery that supports tetrahedral, hexahedral, and hybrid meshes of user specified order. We present the overall design of Albany, and focus on the specifics of the integration of many of its advanced features. As Albany and the components that form it are openly available on the internet, it is our goal that the reader might find some of the design concepts useful in their own work. Albany results in a code that enables the rapid development of parallel, numerically efficient multiphysics software tools. In discussing the features and details of the integration of many of the components involved, we show the reader the wide variety of solution components that are available and what is possible when they are combined within a simulation capability. Key Words: partial differential equations, finite element analysis, template-based generic programmin