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Performance of interpolating approximation schemes in MLPG meshless solver

AIP Conference Proceedings 2020年第1期2293卷

作者： Roman Trobec Rituraj Singh 1“Jožef Stefan” Institute Parallel and Distributed Systems Laboratory Jamova cesta 39 1000 Ljubljana Slovenia

An interpolating moving least square (MLS) approximation was applied in the Meshless Petrov Galerkin method for a solution of Laplace equation. Accuracy and calculation complexity have been analyzed. Results show that original and interpolating MLS schemes are comparable in accuracy, with a small advantage for MLS. The interpolating MLS supports the direct imposition of essential boundary conditions, like in FEM.

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FCloudless: A Performance-Aware Collaborative Mechanism for JointCloud Serverless

FCloudless: A Performance-Aware Collaborative Mechanism for ...

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IEEE International Conference on Joint Cloud Computing (JCC)

作者： Jianfei Liu Huaimin Wang Peichang Shi Yaojie Li Penghui Ma Guodong Yi National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha 410073 China Key Laboratory of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha 410073 China Xiangjiang Lab Changsha 410073 China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha 410073 China

As a new stage in the development of the cloud computing paradigm, serverless computing has the high-level abstraction characteristic of shielding underlying details. This makes it extremely challenging for users to choose a suitable serverless platform. To address this, targeting the jointcloud computing scenario of heterogeneous serverless platforms across multiple clouds, this paper presents a jointcloud collaborative mechanism called FCloudless with cross-cloud detection of the full lifecycle performance of serverless platforms. Based on the benchmark metrics set that probe performance critical stages of the full lifecycle, this paper proposes a performance optimization algorithm based on detected performance data that takes into account all key stages that affect the performance during the lifecycle of a function and predicts the overall performance by combining the scores of local stages and dynamic weights. We evaluate FCloudless on AWS, AliYun, and Azure. The experimental results show that FCloudless can detect the underlying performance of serverless platforms hidden in the black box and its optimization algorithm can select the optimal scheduling strategy for various applications in a jointcloud environment. FCloudless reduces the runtime by 23.3% and 24.7% for cold and warm invocations respectively under cost constraints.

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Integration of the gUSE/WS-PGRADE and InSilicoLab portals with DIRAC

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Journal of Physics: Conference Series 2012年第3期396卷

作者： A Puig Navarro D Viana Casals R Graciani Díaz A Casajús Ramo Á Balaskó P Kacksuk J Kocot D Harezlak ICC University of Barcelona MTA SZTAKI Laboratory of Parallel and Distributed Systems Institute of Computer Science AGH ACC Cyfronet AGH

The gUSE (Grid User Support Environment) framework allows to create, store and distribute application workflows. This workflow architecture includes a wide variety of payload execution operations, such as loops, conditional execution of jobs and combination of output. These complex multi-job workflows can easily be created and modified by application developers through the WS-PGRADE portal. The portal also allows end users to download and use existing workflows, as well as executing them. The DIRAC framework for distributed computing, a complete Grid solution for a community of users needing access to distributed computing resources, has been integrated into the gUSE/WS-PGRADE system. This integration allows the execution of gUSE workflows in a distributed computing environment, thus greatly expanding the capability of the portal to several Grids and Cloud Computing facilities. The main features and possibilities of the gUSE/WS-PGRADE-DIRAC system, as well as the benefits for users, will be outlined and discussed.

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On h-refined meshless solution to Navier-Stokes problem in porous media: comparing meshless Lattice Boltzman Method with ACM RBF-FD approach

arXiv

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arXiv 2024年

作者： Strzelczyk, Dawid Rot, Miha Kosec, Gregor Matyka, Maciej Institute of Theoretical Physics Faculty of Physics and Astronomy University of Wroclaw pl. M. Borna 9 Wroclaw50-204 Poland Parallel and Distributed Systems Laboratory Jožef Stefan Institute Jamova cesta 39 Ljubljana1000 Slovenia Jožef Stefan International Postgraduate School Jamova cesta 39 Ljubljana1000 Slovenia

In this paper, two mesh-free CFD solvers for pore-scale fluid flow through porous media are considered, namely the Lattice Boltzmann Method with the two relaxation time collision term and the direct Navier-Stokes solver under the artificial compressibility limit. The porous media is built with a regular arrangement of spherical grains with variable radii, which allows control of the porosity. Both solvers use the same h-refined meshless spatial discretization to adequately capture the underlying geometry and the same Radial Basis Function (RBF) method to approximate the involved fields and partial differential operators. First, the results are compared with the data from the literature in terms of drag coefficient and permeability at different porosities achieving excellent agreement with the reported results. Next, the simulations are extended beyond the porosity range reported in the literature using proposed h-refined CFD solvers. The results are supported by convergence and timing analyses and discussions on meshless parameters such as stencil size and refinement settings. © 2024, CC BY.

关键词： Porous materials

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Deep reinforcement learning for combinatorial optimization: Covering salesman problems

arXiv

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arXiv 2021年

作者： Li, Kaiwen Zhang, Tao Wang, Rui Wang, Yuheng Han, Yi College of Systems Engineering National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology HKL-MSI2T Changsha410073 China Graduate College National University of Defense Technology Changsha410073 China Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha410073 China

This paper introduces a new deep learning approach to approximately solve the Covering Salesman Problem (CSP). In this approach, given the city locations of a CSP as input, a deep neural network model is designed to directly output the solution. It is trained using the deep reinforcement learning without supervision. Specifically, in the model, we apply the Multi-head Attention to capture the structural patterns, and design a dynamic embedding to handle the dynamic patterns of the problem. Once the model is trained, it can generalize to various types of CSP tasks (different sizes and topologies) with no need of re-training. Through controlled experiments, the proposed approach shows desirable time complexity: it runs more than 20 times faster than the traditional heuristic solvers with a tiny gap of optimality. Moreover, it significantly outperforms the current state-of-the-art deep learning approaches for combinatorial optimization in the aspect of both training and inference. In comparison with traditional solvers, this approach is highly desirable for most of the challenging tasks in practice that are usually large-scale and require quick decisions. Copyright © 2021, The Authors. All rights reserved.

关键词： Combinatorial optimization

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Radial basis function-generated finite differences solution of natural convection problem in 3D

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AIP Conference Proceedings 2020年第1期2293卷

作者： Gregor Kosec Jure Slak 1“Jožef Stefan” Institute E6 Parallel and Distributed Systems Laboratory Jamova cesta 39 1000 Ljubljana Slovenia

The goal of the paper is to present the complete meshless solution procedure, i.e. without meshing or using the regular nodes in any part of the solution procedure, for a thermo-fluid problem governed by Navier-Stokes and heat equations. The core of the solution procedure is an approximation of differential operators with Radial basis function-generated finite differences (RBF- FD) meshless method, iterative pressure-velocity coupling, and implicit time stepping. The flexibility of the presented solution procedure and its implementation is demonstrated by solving a natural convection problem in 2D and 3D irregular domains on scattered nodes. The results, presented in terms of maximal cross-section velocities, are compared against available published data, with good agreement achieved.

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Towards Serialization/Deserialization-free State Transfer in Serverless Workflows

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ACM Transactions on Computer systems 1000年

作者： Xingda Wei Fangming Lu Zhuobin Huang Rong Chen Mingyu Wu Haibo Chen Institute of Parallel and Distributed Systems Shanghai Jiao Tong University Shanghai China Institute of Parallel and Distributed Systems Shanghai Jiao Tong University Shanghai China University of Electronic Science and Technology of China Chengdu China Key Laboratory of System Software Chinese Academy of Sciences Beijing China

Serialization and deserialization dominate the state transfer time of serverless workflows, leading to substantial performance penalties when executing various serverless workflow applications. We identify the key reason for serialization and deserialization as a lack of ability to efficiently access the (remote) memory of another function. To this end, we propose RMMap, an OS primitive for remote memory map, which allows a serverless function to directly access the memory of another function, even if it is located remotely. RMMap is the first to completely eliminate serialization and deserialization overhead when transferring states between any pairs of functions in (unmodified) serverless workflows. To make remote memory map efficient and feasible, we co-design it with modern networking (RDMA), OS, language runtime, and serverless platform. Evaluations using real-world serverless workloads show that integrating RMMap with Knative reduces the serverless workflow execution time on Knative by up to 2.6 × and improves resource utilizations by 86.3%.

关键词： Serverless workflow state transfer serialization and deserialization RDMA

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The demand for consistent web-based workflow editors 8

The demand for consistent web-based workflow editors

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8th Workshop on Workflows in Support of Large-Scale Science, WORKS 2013

作者： Gesing, Sandra Atkinson, Malcolm Klampanos, Iraklis Galea, Michelle Berthold, Michael R. Barbera, Roberto Scardaci, Diego Terstyanszky, Gabor Kiss, Tamas Kacsuk, Peter University of Notre Dame Ctr for Research Computing University of Edinburgh Informatics Forum 111 Information Technology Center Notre DameIN46556 United States University of Edinburgh Informatics Forum EdinburghEH8 9AB United Kingdom Universität Konstanz FB Informatik and Informationswissenschaft Box 712 Konstanz78457 Germany Italian National Institute of Nuclear Physics Catania95123 Italy University of Westminster 115 New Cavendish Street LondonW1W 6UW United Kingdom Laboratory of Parallel and Distributed Systems MTA SZTAKI Kende Street 13-17 Budapest1111 Hungary

ISBN: (纸本)9781450325028

This paper identifies the high value to researchers in many disciplines of having web-based graphical editors for scientific workflows and draws attention to two technological transitions: good quality editors can now run in a browser and workflow enactment systems are emerging that manage multiple workflow languages and support multi-lingual workflows. We contend that this provides a unique opportunity to introduce multi-lingual graphical workflow editors which in turn would yield substantial benefits: workflow users would find it easier to share and combine methods encoded in multiple workflow languages, the common framework would stimulate conceptual convergence and increased workflow component sharing, and the many workflow communities could share a substantial part of the effort of delivering good quality graphical workflow editors in browsers. The paper examines whether such a common framework is feasible and presents an initial design for a web-based editor, tested with a preliminary prototype. It is not a fait accompli but rather an urgent rallying cry to explore collaboratively a generic web-based framework before investing in many divergent individual implementations.

关键词： Interoperability

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Big data collaborative artificial intelligence and high-performance computing to drive physical design of fusion

Big data collaborative artificial intelligence and high-perf...

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Cloud Computing, Big Data Applications and Software Engineering (CBASE), International Conference on

作者： Pan Liu Gongjie Liu Jie Liu Chencheng Liu Wenbin Xiong Zhangcun Tang Yinzhao Zhou Yonggang Wang Zhouming Yuan Tianfu Innovation Energy Establishment Chengdu China Beijng PARATERA Technology Corp. Ltd Beijing China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China Central South University of Forestry and Technology Changsha China Nuclear and Radiation Safety Center MEE Beijing China University of Electronic Science and Technology of China Chengdu China

Controlled thermonuclear fusion has always been a dream pursued by mankind. However, the physical processes of controlled thermonuclear fusion are complex, requiring numerical simulations with high performance computing, and the amount of data generated by the physical processes on spatial, temporal and temperature scales is too large to be captured, managed, processed and collated in a reasonable time frame by mainstream software tools to achieve more aggressive fusion physical design. The data are too large to be captured, managed, processed, and collated into more aggressive targets for fusion physical design in a reasonable time by mainstream software tools. At the same time, the failure of fusion ignition can be caused by the distortion of various key physical quantities, and only by decomposing the process step by step and clarifying the changes of key physical quantities in the fusion physics process, can an effective mechanism be formed to prevent the distortion of key physical quantities from causing ignition failure in experimental physics. Big data in collaboration with artificial intelligence and high performance computing to drive the physical design of fusion is a novel avenue. By data acquisition with and pre-processing, this allows the creation of small sample libraries and deep learning. With supervised learning function convergence, incorporating solid/fluid computational methods, further network layering and cell expansion, the parameters of the physical model conforming to Lawson’s criterion will become experimental physical parameters, and we find the new approach in Data capacity, Model combination approach, Type of material, Calculation speed, Optimisation of design iteration times, etc. are superior to the traditional approach.

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On Adaptive Self-Organization in Artificial Robot Organisms

On Adaptive Self-Organization in Artificial Robot Organisms

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Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, Computation World:

作者： Serge Kernbach Heiko Hamann Jürgen Stradner Ronald Thenius Thomas Schmickl Karl Crailsheim A.C. van Rossum Michele Sebag Nicolas Bredeche Yao Yao Guy Baele Yves Van de Peer Jon Timmis Maizura Mohktar Andy Tyrrell A.E. Eiben S.P. McKibbin Wenguo Liu Alan F.T. Winfield Institute of Parallel and Distributed Systems University of Stuttgart Germany Artificial Life Lab Karl-Franzens-University Graz Graz Austria Almende B. V. Rotterdam Netherlands TAO LRI Univ. Paris-Sud CNRS INRIA Saclay France VIB Department Plant Systems Biology Ghent University Belgium University of York York United Kingdom Free University Amsterdam Netherlands Materials and Engineering Research Institute (MERI) Sheffield Hallam University Bristol Robotics Laboratory (BRL) UWE Bristol UK Bristol Robotics Laboratory (BRL) UWE Bristol

Self-organization in natural systems demonstrates very reliable and scalable collective behavior without using any central elements. When providing collective robotic systems with self-organizing principles, we are facing new problems of making self-organization purposeful, self-adapting to changing environments and faster, in order to meet requirements from a technical perspective. This paper describes on-going work of creating such an artificial self-organization within artificial robot organisms, performed in the framework of several European projects.

关键词： Robots Organisms Peer to peer computing Centralized control Control systems Scalability Cognitive robotics Plants (biology) systems biology Biological materials

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