On the parallel scalability of hybrid linear solvers for large 3D problems

Large-scale scientific applications and industrial simulations are nowadays fully integrated in many engineering areas. They involve the solution of large sparse linear systems. The use of large high performance computers is mandatory to solve these problems. The main topic of this research work was the study of a numerical technique that had attractive features for an efficient solution of large scale linear systems on large massively parallel platforms. The goal is to develop a high performance hybrid direct/iterative approach for solving large 3D problems. We focus specifically on the associated domain decomposition techniques for the parallel solution of large linear systems. We have investigated several algebraic preconditioning techniques, discussed their numerical behaviours, their parallel implementations and scalabilities. We have compared their performances on a set of 3D grand challenge problems

Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions

News creation and consumption has been changing since the advent of social media. An estimated 2.95 billion people in 2019 used social media worldwide. The widespread of the Coronavirus COVID-19 resulted with a tsunami of social media. Most platforms were used to transmit relevant news, guidelines and precautions to people. According to WHO, uncontrolled conspiracy theories and propaganda are spreading faster than the COVID-19 pandemic itself, creating an infodemic and thus causing psychological panic, misleading medical advises, and economic disruption. Accordingly, discussions have been initiated with the objective of moderating all COVID-19 communications, except those initiated from trusted sources such as the WHO and authorized governmental entities. This paper presents a large-scale study based on data mined from Twitter. Extensive analysis has been performed on approximately one million COVID-19 related tweets collected over a period of two months. Furthermore, the profiles of 288,000 users were analyzed including unique users profiles, meta-data and tweets context. The study noted various interesting conclusions including the critical impact of the (1) exploitation of the COVID-19 crisis to redirect readers to irrelevant topics and (2) widespread of unauthentic medical precautions and information. Further data analysis revealed the importance of using social networks in a global pandemic crisis by relying on credible users with variety of occupations, content developers and influencers in specific fields. In this context, several insights and findings have been provided while elaborating computing and non-computing implications and research directions for potential solutions and social networks management strategies during crisis periods.Comment: 11 pages, 10 figures, Journal Articl

Divide and Conquer Symmetric Tridiagonal Eigensolver for Multicore Architectures

International audienceComputing eigenpairs of a symmetric matrix is a problem arising in many industrial applications, including quantum physics and finite-elements computation for automo-biles. A classical approach is to reduce the matrix to tridiagonal form before computing eigenpairs of the tridiagonal matrix. Then, a back-transformation allows one to obtain the final solution. Parallelism issues of the reduction stage have already been tackled in different shared-memory libraries. In this article, we focus on solving the tridiagonal eigenproblem, and we describe a novel implementation of the Divide and Conquer algorithm. The algorithm is expressed as a sequential task-flow, scheduled in an out-of-order fashion by a dynamic runtime which allows the programmer to play with tasks granularity. The resulting implementation is between two and five times faster than the equivalent routine from the INTEL MKL library, and outperforms the best MRRR implementation for many matrices

HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi

This paper presents the design and implementation of several fundamental dense linear algebra (DLA) algorithms for multicore with Intel Xeon Phi coprocessors. In particular, we consider algorithms for solving linear systems. Further, we give an overview of the MAGMA MIC library, an open source, high performance library, that incorporates the developments presented here and, more broadly, provides the DLA functionality equivalent to that of the popular LAPACK library while targeting heterogeneous architectures that feature a mix of multicore CPUs and coprocessors. The LAPACK-compliance simplifies the use of the MAGMA MIC library in applications, while providing them with portably performant DLA. High performance is obtained through the use of the high-performance BLAS, hardware-specific tuning, and a hybridization methodology whereby we split the algorithm into computational tasks of various granularities. Execution of those tasks is properly scheduled over the heterogeneous hardware by minimizing data movements and mapping algorithmic requirements to the architectural strengths of the various heterogeneous hardware components. Our methodology and programming techniques are incorporated into the MAGMA MIC API, which abstracts the application developer from the specifics of the Xeon Phi architecture and is therefore applicable to algorithms beyond the scope of DLA

Perancangan Sistem Penyiraman Otomatis Pada Greenhouse Guna Meningkatkan Kualitas Bibit Tanaman Anggur (Vitis vinivera) Di Daerah Sidoarjo

Teknologi di bidang industri pertanian dan perkebunan belum banyak dikembangkan, sehingga masih banyak petani yang melakukan penyiraman tanaman anggur dengan menggunakan cara manual. Penyiraman yang masih menggunakan cara konvensional memiliki kekurangan, seperti waktu dan tenaga yang banyak dan berulangnya pekerjaan dapat menimbulkan rasa jenuh. Untuk memaksimalkan hasil yang didapat, dibutuhkan teknologi yang dapat membantu petani dalam menyirami tanaman secara efisien dan tentunya efisien. Dari permasalahan diatas, penelitian ini ingin membuat alat agar dapat memudahkan petani dalam melakukan penyiraman tanaman anggur agar tidak membutuhkan banyakdan tenaga yang memakan waktu lama. Dengan hadirnya desain penyiraman diharapkan memudahkan petani dalam melakukan penyiraman tanaman anggur dengan efisiensi tinggi. Alat ini berguna untuk mendeteksi kelembapan dan suhu yang ada di dalam Greenhouse. Saat alat ini bekerja maka sensor akan otomatis mendeteksi kelembapan dan suhu yang berada di dalam Greenhouse tersebut, jika suhu kurang dari 23°C maka penyiraman akan otomatis aktif untuk meningkatkan suhu di dalam Greenhouse, sedangkan sudah mencapai 32°C maka penyiraman akan dilakukan secara otomatis . otomatis. akan otomatis berhenti

Parallel algebraic domain decomposition solver for the solution of augmented systems

International audienceWe consider the parallel iterative solution of indefinite linear systems given as augmented systems. Our numerical technique is based on an algebraic non overlapping domain decomposition technique that only exploits the graph of the sparse matrix. This approach to high-performance, scalable solution of large sparse linear systems in parallel scientific computing, is to combine direct and iterative methods. We report numerical and parallel performance of the scheme on large matrices arising from the finite element discretization of linear elasticity in structural mechanics problems

Sur l'extensibilité parallèle de solveurs linéaires hybrides pour des problèmes tridimensionels de grandes tailles

Large-scale scientific applications and industrial simulations are nowadays fully integrated in many engineering areas. They involve the solution of large sparse linear systems. The use of large high performance computers is mandatory to solve these problems. The main topic of this research work was the study of a numerical technique that had attractive features for an efficient solution of large scale linear systems on large massively parallel platforms. The goal is to develop a high performance hybrid direct/iterative approach for solving large 3D problems. We focus specifically on the associated domain decomposition techniques for the parallel solution of large linear systems. We have investigated several algebraic preconditioning techniques, discussed their numerical be- haviours, their parallel implementations and scalabilities. We have compared their performances on a set of 3D grand challenge problems.La résolution de très grands systèmes linéaires creux est une composante de base algorithmique fondamentale dans de nombreuses applications scientifiques en calcul intensif. La résolution per- formante de ces systèmes passe par la conception, le développement et l'utilisation d'algorithmes parallèles performants. Dans nos travaux, nous nous intéressons au développement et l'évaluation d'une méthode hybride (directe/itérative) basée sur des techniques de décomposition de domaine sans recouvrement. La stratégie de développement est axée sur l'utilisation des machines mas- sivement parallèles à plusieurs milliers de processeurs. L'étude systématique de l'extensibilité et l'efficacité parallèle de différents préconditionneurs algébriques est réalisée aussi bien d'un point de vue informatique que numérique. Nous avons comparé leurs performances sur des systèmes de plusieurs millions ou dizaines de millions d'inconnues pour des problèmes réels 3D

Parallel algebraic hybrid solvers for large 3D convection-diffusion problems

International audienc

Sur l'extensibilité parallèle de solveurs linéaires hybrides pour des problèmes tridimensionnels de grandes tailles

La résolution de très grands systèmes linéaires creux est une composante de base algorithmique fondamentale dans de nombreuses applications scientifiques de calcul intensif. La résolution performante de ces systèmes passe par la conception, le développement et l'utilisation d'algorithmes parallèles performants. Dans nos travaux, nous nous intéressons au développement et l'évaluation d'une méthode hybride (directe/itérative) basée sur des techniques de décomposition de domaine sans recouvrement. La stratégie de développement est axée sur l'utilisation des machines massivement parallèles de plusieurs milliers de processeurs. L'étude systématique de l'extensibilité et l'efficacité parallèle de différents préconditionneurs algébrique est réalisée aussi bien d'un point de vue informatique que numérique. On a comparé leurs performances sur des systèmes de plusieurs millions ou dizaines de millions d'inconnues pour des problèmes réels 3D.Large-scale scientific applications and industrial simulations are nowadays fully integrated in many engineering areas. They involve the solution of large sparse linear systems. The use of large high performance computers is mandatory to solve these problems. The main topic of this research work was the study of a numerical technique that had attractive features for an efficient solution of large scale linear systems on large massively parallel platforms. The goal is to develop a high performance hybrid direct/iterative approach for solving large 3D problems. We focus specifically on the associated domain decomposition techniques for the parallel solution of large linear systems. We have investigated several algebraic preconditioning techniques, discussed their numerical behaviors, their parallel implementations and scalabilities. We have compared their performances on a set of 3D grand challenge problems.TOULOUSE-ENSEEIHT (315552331) / SudocSudocFranceF