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The study was about women's opportunity for socio-economic development based on their experiences on Functional Adult Literacy (FAL) and integrated vocational training in Apac District-Northern Uganda. The main objective of this study was to explore whether and how women participants in Apac District derived socio-economic benefits from FAL as well as integrated vocational training. The study was informed by agency theory from Freire's literacy theory and Kabeer's socio-economic perspective which contend on the component of awareness or by making marginalised non-literate's agents of socio-economic development. These theories helped to explore and establish the socio-economic transformation experienced by women as a result of their participation in FAL in addition to integrated vocational training. These transformations were captured by comparing the kinds of life led by the women prior to and after FAL and integrated vocational training, in terms of participating in communities, family settings, awareness on the value of training and participating on income generating group projects. The study mainly used qualitative case study research design focusing on the experiences of 35 participants both in the rural and urban setting. Using Focused Group Discussions (FGDs) and key informant interviews, this study revealed the conditions of women before and after benefiting from FAL with integrated vocational skills. The findings of this study inductively generated from the participants revealed that women who acquired FAL in addition to integrated vocational skills significantly transformed their socio-economic lives. Opportunity for FAL and integrated vocational training improved women's daily lives in terms of confidence to participate in community undertakings and local council leadership. In addition, the women became self-employed, profited from income generating group projects, made re-investments of savings from the income generated. In turn, the well-being for themselves and their families greatly improved. Therefore, the study recommends that the Ministry of Gender, Labour and Social Development (MGLSD) which coordinates FAL training in Uganda along with other departments, such as international partners, NGO's and civil society organisations should prioritise, support and strengthen the FAL learning with integrated vocational training policies. [The research was funded by DAAD (German Academic Exchange Service).]

The International Fusion Materials Irradiation Facility (IFMIF), presently in its Engineering Validation and Engineering Design Activities (EVEDA) phase under the frame of the Broader Approach Agreement between Europe and Japan, accomplished in summer 2013, on schedule, its EDA phase with the release of the engineering design report of the IFMIF plant, which is here described. Many improvements of the design from former phases are implemented, particularly a reduction of beam losses and operational costs thanks to the superconducting accelerator concept, the re-location of the quench tank outside the test cell (TC) with a reduction of tritium inventory and a simplification on its replacement in case of failure, the separation of the irradiation modules from the shielding block gaining irradiation flexibility and enhancement of the remote handling equipment reliability and cost reduction, and the water cooling of the liner and biological shielding of the TC, enhancing the efficiency and economy of the related sub-systems. In addition, the maintenance strategy has been modified to allow a shorter yearly stop of the irradiation operations and a more careful management of the irradiated samples. The design of the IFMIF plant is intimately linked with the EVA phase carried out since the entry into force of IFMIF/EVEDA in June 2007.

This paper deals with linear algebra operations on Graphics Processing Unit (GPU) with complex number arithmetic using double precision. An analysis of their uses within iterative Krylov methods is presented to solve acoustic problems. Numerical experiments performed on a set of acoustic matrices arising from the modelisation of acoustic phenomena inside a car compartment are collected, and outline the performance, robustness and effectiveness of our algorithms, with a speed-up up to 28x for dot product, 9.8x for sparse matrix-vector product and solvers.

In this paper, we aim to introduce a new perspective when comparing highly parallelized algorithms on GPU: the energy consumption of the GPU. We give an analysis of the performance of linear algebra operations, including addition of vectors, element-wise product, dot product and sparse matrix-vector product, in order to validate our experimental protocol. We also analyze their uses within conjugate gradient method for solving the gravity equations on Graphics Processing Unit (GPU). Cusp library is considered and compared to our own implementation with a set of real matrices arrising from the Chicxulub crater and obtained by the finite element discretization of the gravity equations. The experiments demonstrate the performance and robustness of our implementation in terms of energy efficiency.

This paper gives an analysis and an evaluation of linear algebra operations on Graphics Processing Unit (GPU) with complex number arithmetics with double precision. Knowing the performance of these operations, iterative Krylov methods are considered to solve the acoustic problem efficiently. Numerical experiments carried out on a set of acoustic matrices arising from the modelisation of acoustic phenomena within a cylinder and a car compartment are exposed, exhibiting the performance, robustness and efficiency of our algorithms, with a ratio up to 27x for dot product, 10x for sparse matrix-vector product and solvers in complex double precision arithmetics.

Low order, sequential or non-massively parallel finite elements are generaly used for three-dimensional gravity modelling. In this paper, in order to obtain better gravity anomaly solutions in heterogeneous media, we solve the gravimetry problem using massively parallel high order finite elements on hybrid multi-CPU/GPU clusters. Parallel algorithms well suited for such hybrid architectures have to be designed. A new stochastic-based optimization procedure for the optimized Schwarz method is here presented, implemented and tuned to graphical cards processors units. Numerical experiments performed on a reallistic test case, demonstrates the robustness and efficiency of the proposed method and of its implementation on massive multi-CPU/GPU architectures.

In this paper, we present, evaluate and analyse the performance of parallel synchronous Jacobi algorithms by different partitioned procedures including band-row splitting, band-row sparsity pattern splitting and substructuring splitting, when solving sparse large linear systems. Numerical experiments performed on a set of academic 3D Laplace equation and on a real gravity matrices arising from the Chicxulub crater are exhibited, and show the impact of splitting on parallel synchronous iterations when solving sparse large linear systems. The numerical results clearly show the interest of substructuring methods compared to band-row splitting strategies., Comment: arXiv admin note: text overlap with arXiv:2108.13162

In this paper, the authors propose an analysis of the frequency response function in a car compartment, subject to some fluctuating pressure distribution along the open cavity of the sun-roof at the top of a car. Coupling of a computational fluid dynamics and of a computational acoustics code is considered to simulate the acoustic fluid-structure interaction problem. Iterative Krylov methods and domain decomposition methods, tuned on Graphic Processing Unit (GPU), are considered to solve the acoustic problem with complex number arithmetics with double precision. Numerical simulations illustrate the efficiency, robustness and accuracy of the proposed approaches.

Due to their highly parallel multi-cores architecture, GPUs are being increasingly used in a wide range of computationally intensive applications. Compared to CPUs, GPUs can achieve higher performances at accelerating the programs' execution in an energy-efficient way. Therefore GPGPU computing is useful for high performance computing applications and in many scientific research fields. In order to bring further performance improvements, GPU clusters are increasingly adopted. The energy consumed by GPUs cannot be neglected. Therefore, an energy-efficient time scheduling of the programs that are going to be executed by the parallel GPUs based on their deadline as well as the assigned priorities could be deployed to face their energetic avidity. For this reason, we present in this paper a model enabling the measure of the power consumption and the time execution of some elementary operations running on a single GPU using a new developed energy measurement protocol. Consequently, using our methodology, energy needs of a program could be predicted, allowing a better task scheduling.

One of the most promising applications in nanoscience is the design of new materials to improve water permeability and selectivity of nanoporous membranes. Understanding the molecular architecture behind these fascinating structures and how it impacts the water flow is an intricate but necessary task. We studied here, the water flux through multi-layered nanoporous molybdenum disulfide (MLNMoS$_2$) membranes with different nanopore sizes and length. Molecular dynamics simulations show that the permeability do not increase with the inverse of the membrane thickness, violating the classical hydrodynamic behavior. The data also reveals that the water dynamics is slower than that observed in frictionless carbon nanotubes and multi-layer graphene membranes, which we explain in terms of an anchor mechanism observed in between layers. We show that the membrane permeability is critically dependent on the nanopore architecture, bringing important insights into the manufacture of new desalination membranes.

The main objective of this work consists in analyzing sub-structuring method for the parallel solution of sparse linear systems with matrices arising from the discretization of partial differential equations such as finite element, finite volume and finite difference. With the success encountered by the general-purpose processing on graphics processing units (GPGPU), we develop an hybrid multiGPUs and CPUs sub-structuring algorithm. GPU computing, with CUDA, is used to accelerate the operations performed on each processor. Numerical experiments have been performed on a set of matrices arising from engineering problems. We compare C+MPI implementation on classical CPU cluster with C+MPI+CUDA on a cluster of GPU. The performance comparison shows a speed-up for the sub-structuring method up to 19 times in double precision by using CUDA.

Nanoscale materials are a promising desalination technology. While fast water flow in nanotubes is well understood, this is not the case for water permeability in single-layer membranes. The physical-chemical balance between nanopore size, shape, and charge might be the answer.

The shift in water security demands improvements in alternative solutions such as saltwater desalination. One of the most efficient technologies in this scope is the reverse osmosis systems, a technology based on a membrane separation process. MoS$_2$ nanoporous membranes are gained attention as a promise for the next-generation high selective and permeable membranes technology. Besides that, one aspect of nanoconfined fluid flow not yet investigated but studied from the fluid mechanics calculations is the impact of induced pressure fields in the water flux in neighboring microfilters, described as hydrodynamic interactions. For this purpose, we studied the water flow through adjacent MoS$_2$ nanopores by running Non-Equilibrium Molecular Dynamics simulations and obtained that in this scale the hydrodynamics interactions are not significant as expected.

Water scarcity is a reality in our world, and scenarios predicted by leading scientists in this area indicate that it will worsen in the next decades. However, new technologies based in low-cost seawater desalination can prevent the worst scenarios, providing fresh water for humanity. With this goal, membranes based in nanoporous materials have been suggested in recent years. One of the materials suggested is MoS$_2$, and classical Molecular Dynamics (MD) simulation is one of the most powerful tools to explore these nanomaterials. However, distinct Force Fields employed in MD simulations are parameterized based on distinct experimental quantities. In this paper, we compare two models of salt that were build based on distinct properties of water-salt mixtures. One model fits the hydration free energy and lattice properties, the second fits the crystal density and the density and the dielectric constant of water and salt mixtures. To compare the models, MD simulations for salty water flow through two nanopores sizes were used -- one pore big enough to accommodate hydrated ions, and one smaller in which the ion has to dehydrate to enter, and two rigid water models from the TIP4P family -- the TIP4P/2005 and TIP4P/$\epsilon$. Our results indicate that the water permeability and salt rejection by the membrane are more influenced by the salt model than by the water model, especially for the narrow pore. In fact, completely distinct mechanisms were observed, and they are related to the characteristics employed in the ion model parameterization. The results show that not only the water model can influence the outcomes, but the ion model plays a crucial role., Comment: 15 pages, 17 figures