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Wyniki wyszukiwania dla: TOOLS FOR HIGH PERFORMANCE COMPUTING
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Methodology of Selecting the Hadoop Ecosystem Configuration in Order to Improve the Performance of a Plagiarism Detection System
PublikacjaThe plagiarism detection problem involves finding patterns in unstructured text documents. Similarity of documents in this approach means that the documents contain some identical phrases with defined minimal length. The typical methods used to find similar documents in dig- ital libraries are not suitable for this task (plagiarism detection) because found documents may contain similar content and we have not any war- ranty that...
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Pre‐exascale HPC approaches for molecular dynamics simulations. Covid‐19 research: A use case
PublikacjaExascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified...
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Results and models for Novel high frequency components with non-conventional shape employing smooth geometry deformation of 3D solid with FFD
Dane BadawczeThe project aims to investigate the possibility of developing and manufacturing novel high frequency devices having non-standard geometries, allowing for improved electromagnetic performance over what is achievable with currently available design tools. The non-conventional geometry will be obtained by employing the free-form shape deformation technique...
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Potential Energy Curves of Diatomic Alkali Molecules Datasets
PublikacjaThe datasets described in this article contain potential energy curves for several diatomic systems. The data was obtained via high-performance computing using MOLPRO, a system of ab initio programs for advanced molecular electronic structure calculations. The datasets allow to model bond lengths, energy levels, spectra and time-evolution of molecular dimers for which the data are presented.
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EuroCC Narodowe Centra Kompetencji EuroHPC
ProjektyProjekt realizowany w Centrum Informat. Trójmiejskiej Akadem.Sieci Komputerowej zgodnie z porozumieniem 951732 — EUROCC — H2020-JTI-EuroHPC-2019-2 z dnia 2020-08-31
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Performance of Noise Map Service Working in Cloud Computing Environment
PublikacjaIn the paper a noise map service designated for the user interested in environmental noise subject is presented. It is based on cloud computing. Noise prediction algorithm and source model, developed for creating acoustic maps, are working in cloud computing environment. In the study issues related to noise modeling of sound propagation in urban spaces are discussed with a special focus on road noise. Examples of results obtained...
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Some Artificial Intelligence Driven Algorithms For Mobile Edge Computing in Smart City
PublikacjaSmart mobile devices can share computing workload with the computer cloud that is important when artificial intelligence tools support computer systems in a smart city. This concept brings computing on the edge of the cloud, closer to citizens and it can shorten latency. Edge computing removes a crucial drawback of the smart city computing because city services are usually far away from citizens, physically. Besides, we introduced...
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Performance Analysis of the OpenCL Environment on Mobile Platforms
PublikacjaToday’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...
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The parallel environment for endoscopic image analysis
PublikacjaThe jPVM-oriented environment to support high performance computing required for the Endoscopy Recommender System (ERS) is defined. SPMD model of image matching is considered and its two implementations are proposed: Lexicographical Searching Algorithm (LSA) and Gradient Serching Algorithm (GSA). Three classes of experiments are considered and the relative degree of similarity and execution time of each algorithm are analysed....
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Quality Modeling in Grid and Volunteer-Computing Systems
PublikacjaA model of computational quality in large-scale computing systems was presented in the previous chapter of this book. This model describes three quality attributes: performance, reliability and energy efficiency. We assumed that all processes in the system are incessantly ready to perform calculations and that communication between the processes occurs immediately. These assumptions are not true for grid and volunteer computing...
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Security Mechanisms in the Comcute System
PublikacjaThe aim of this paper is pointing out the basic security problems and mechanisms in the Comcute system - maintenance system of large computing power in the face of critical crisis. Moreover security mechanism and tools useful to apply in laboratory model as well as target version of the Comcute system are presented.
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Simulation of Parallel Applications on Large-scale Distributed Systems
PublikacjaThis chapter has a form of a review article in the field of simulating High-Performance Computing systems. We justify the need for a new versatile simulator considering heterogeneity, energy efficiency and reliability of HPC systems. We sketch the problems that need to be solved by such simulator and rationalize using discrete-event simulation for this purpose. Based on a review of existing discrete-event HPC simulation solutions...
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Application of Web-GIS and Cloud Computing to Automatic Satellite Image Correction
PublikacjaRadiometric calibration of satellite imagery requires coupling of atmospheric and topographic parameters, which constitutes serious computational problems in particular in complex geographical terrain. Successful application of topographic normalization algorithms for calibration purposes requires integration of several types of high-resolution geographic datasets and their processing in a common context. This paper presents the...
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Tools, Methods and Services Enhancing the Usage of the Kepler-based Scientific Workflow Framework
PublikacjaScientific workflow systems are designed to compose and execute either a series of computational or data manipulation steps, or workflows in a scientific application. They are usually a part of a larger eScience environment. The usage of workflow systems, however very beneficial, is mostly not irrelevant for scientists. There are many requirements for additional functionalities around scientific workflows systems that need to be...
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Performance/energy aware optimization of parallel applications on GPUs under power capping
PublikacjaIn the paper we present an approach and results from application of the modern power capping mechanism available for NVIDIA GPUs to the bench- marks such as NAS Parallel Benchmarks BT, SP and LU as well as cublasgemm- benchmark which are widely used for assessment of high performance computing systems’ performance. Specifically, depending on the benchmarks, various power cap configurations are best for desired trade-off of performance...
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Qualitative evaluation of distributed clinical systems supporting research teams working on large-scale data
PublikacjaInthispaper,fivecontemporaryscalablesystemstosupportmedicalresearchteams are presented. Their functionalities extend from heterogeneous unstructured data acquisition through large-scale data storing, to on-the-fly analyzing by using robust methods. Such kinds of systems can be useful in the development of new medical procedures and recommendation rules for decision support systems. A short description of each of them is provided....
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Use of ICT infrastructure for teaching HPC
PublikacjaIn this paper we look at modern ICT infrastructure as well as curriculum used for conducting a contemporary course on high performance computing taught over several years at the Faculty of Electronics Telecommunications and Informatics, Gdansk University of Technology, Poland. We describe the infrastructure in the context of teaching parallel programming at the cluster level using MPI, node level using OpenMP and CUDA. We present...
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Data Partitioning and Task Management in the Clustered Server Layer of the Volunteer-based Computation System
PublikacjaWhile the typical volunteer-based distributed computing system focus on the computing performance, the Comcute system was designed especially to keep alive in the emergency situations. This means that designers had to take into account not only performance, but the safety of calculations as well. Quadruple-layered architecture was proposed to separate the untrusted components from the core of the system. The main layer (W) consists...
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Modeling Volunteer Based Systems
PublikacjaThere are two main approaches to processing tasks requiring high amounts of computational power. One approach is using clusters of mostly identical hardware, placed in dedicated locations [1, 2, 3]. The other approach is outsourcing computing resources from large numbers of volunteers connected to the Internet [7]. This chapter presents an application of a mathematical model of the volunteer computing presented in Volume 1 of this...
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FPGA implementation of the multiplication operation in multiple-precision arithmetic
PublikacjaAlthough standard 32/64-bit arithmetic is sufficient to solve most of the scientific-computing problems, there are still problems that require higher numerical precision. Multiple-precision arithmetic (MPA) libraries are software tools for emulation of computations in a user-defined precision. However, availability of a reconfigurable cards based on field-programmable gate arrays (FPGAs) in computing systems allows one to implement...
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Affective Learning Manifesto – 10 Years Later
PublikacjaIn 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....
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Mobile Cloud computing architecture for massively parallelizablegeometric computation
PublikacjaCloud Computing is one of the most disruptive technologies of this century. This technology has been widely adopted in many areas of the society. In the field of manufacturing industry, it can be used to provide advantages in the execution of the complex geometric computation algorithms involved on CAD/CAM processes. The idea proposed in this research consists in outsourcing part of the load to be com- puted in the client machines...
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Verification and Benchmarking in MPA Coprocessor Design Process
PublikacjaThis paper presents verification and benchmarking required for the development of a coprocessor digital circuit for integer multiple-precision arithmetic (MPA). Its code is developed, with the use of very high speed integrated circuit hardware description language (VHDL), as an intellectual property core. Therefore, it can be used by a final user within their own computing system based on field-programmable gate arrays (FPGAs)....
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Numerical analysis of the container vessel's self-propulsion at different rudder deflection angles
PublikacjaNowadays, CFD becomes one of the most commonly used research method in ship hydrodynamics, limited to the analyses of hull resistance in calm water. With continuously improving computing power and increasingly more accurate numerical methods it is possible to simulate more complex cases. State of the art CFD tools also enable development of new ways of assessing ship maneuvering performance. This paper presents an attempt on...
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Numerical analysis of the container vessel's self-propulsion at different rudder deflection angles
PublikacjaNowadays, CFD becomes one of the most commonly used research method in ship hydrodynamics, limited to the analyses of hull resistance in calm water. With continuously improving computing power and increasingly more accurate numerical methods it is possible to simulate more complex cases. State of the art CFD tools also enable development of new ways of assessing ship maneuvering performance. This paper presents an attempt on using...
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Some Optimization Methods for Simulations in Volunteer and Grid Systems
PublikacjaIn this chapter, some optimization methods have been presented for improving performance of simulations in the volunteer and grid computing system called Comcute. Some issues related to the cloud computing can be solved by presented approaches as well as the Comcute platform can be used to simulate execution of expensive and energy consuming long-term tasks in the cloud environment. In particular, evolutionary algorithms as well...
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A Human Behaviour Model Agent for Testing of Voluntary Computing Systems
PublikacjaPaper presents a design and performance of a voluntary-based distributed computing system testing agent, implementing a human behaviour model. The agent, nicknamed iRobot, was designed and implemented to enable controlled, large scale testing of core algorithms of Comcute - a new voluntary distributed computing platform complementary to BOINC. The main agent design goals were: emulation of human behaviour when browsing web pages,...
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Mobile Offloading Framework: Solution for Optimizing Mobile Applications Using Cloud Computing
PublikacjaNumber of mobile devices and applications is growing rapidly in recent years. Capabilities and performance of these devices can be tremendously extended with the integration of cloud computing. However, multiple challenges regarding implementation of these type of mobile applications are known, like differences in architecture, optimization and operating system support. This paper summarizes issues with mobile cloud computing and...
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublikacjaIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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Towards an efficient multi-stage Riemann solver for nuclear physics simulations
PublikacjaRelativistic numerical hydrodynamics is an important tool in high energy nuclear science. However, such simulations are extremely demanding in terms of computing power. This paper focuses on improving the speed of solving the Riemann problem with the MUSTA-FORCE algorithm by employing the CUDA parallel programming model. We also propose a new approach to 3D finite difference algorithms, which employ a GPU that uses surface memory....
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Theoretical designing of selenium heterocyclic non-fullerene acceptors with enhanced power conversion efficiency for organic solar cells: a DFT/TD-DFT-based prediction and understanding
PublikacjaIn this study, we have designed and explored a new series of non-fullerene acceptors for possible applications in organic solar cells. We have designed four molecules named as APH1 to APH4 after end-capped modification of recently synthesized Y6-Se-4Cl molecule. Density functional theory and time dependent-density functional theory have been employed for computing geometric and photovoltaic parameters of the designed molecules....
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Modeling of Performance, Reliability and Energy Efficiency in Large-Scale Computational Environment
PublikacjaLarge scale of complexity of distributed computational systems imposes special challanges for prediction of quality in such systems.Existing quality models for lower-scale systems include functionality,performance,reliability,flexibility and usability.Among these attributes,performance and reliability have a particular significance to the large-scale systems computing quality modeling due to their strong dependence on the system...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublikacjaPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Modeling of Performance, Reliability and Energy Efficiency in Large-Scale Computational Environments
PublikacjaLarge scale of complexity of distributed computational systems imposes special challenges for prediction of quality in such systems. Existing quality models for lower-scale systems include functionality, performance, reliability, flexibility and usability. Among these attributes, performance and reliability have a particular significance to the large-scale systems computing quality modeling due to their strong dependence on the...
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Optimization issues in distributed computing systems design
PublikacjaIn recent years, we observe a growing interest focused on distributed computing systems. Both industry and academia require increasing computational power to process and analyze large amount of data, including significant areas like analysis of medical data, earthquake, or weather forecast. Since distributed computing systems – similar to computer networks – are vulnerable to failures, survivability mechanisms are indispensable...
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NUMERICAL ESTIMATION OF HULL HYDRODYNAMIC DERIVATIVES IN SHIP MANOUVERING PREDICTION
PublikacjaOperating in crowded waterways pose a risk of accidents and disasters due to maneuvering limitations of the ship. In order to predict ship’s maneuvering characteristics at the design stage, model tests are often executed as the most accurate prediction tool. Two approaches can be distinguished here: free running model tests and numerical simulations based on planar motion model with the use of hydrodynamic derivatives obtained...
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Category-Based Workload Modeling for Hardware Load Prediction in Heterogeneous IaaS Cloud
PublikacjaThe paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.
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Process arrival pattern aware algorithms for acceleration of scatter and gather operations
PublikacjaImbalanced process arrival patterns (PAPs) are ubiquitous in many parallel and distributed systems, especially in HPC ones. The collective operations, e.g. in MPI, are designed for equal process arrival times (PATs), and are not optimized for deviations in their appearance. We propose eight new PAP-aware algorithms for the scatter and gather operations. They are binomial or linear tree adaptations introducing additional process...
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Optimization of parallel implementation of UNRES package for coarse‐grained simulations to treat large proteins
PublikacjaWe report major algorithmic improvements of the UNRES package for physics-based coarse-grained simulations of proteins. These include (i) introduction of interaction lists to optimize computations, (ii) transforming the inertia matrix to a pentadiagonal form to reduce computing and memory requirements, (iii) removing explicit angles and dihedral angles from energy expressions and recoding the most time-consuming energy/force terms...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublikacjaAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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A Regular Expression Matching Application with Configurable Data Intensity for Testing Heterogeneous HPC Systems
PublikacjaModern High Performance Computing (HPC) systems are becoming increasingly heterogeneous in terms of utilized hardware, as well as software solutions. The problems, that we wish to efficiently solve using those systems have different complexity, not only considering magnitude, but also the type of complexity: computation, data or communication intensity. Developing new mechanisms for dealing with those complexities or choosing an...
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Distributed NVRAM Cache – Optimization and Evaluation with Power of Adjacency Matrix
PublikacjaIn this paper we build on our previously proposed MPI I/O NVRAM distributed cache for high performance computing. In each cluster node it incorporates NVRAMs which are used as an intermediate cache layer between an application and a file for fast read/write operations supported through wrappers of MPI I/O functions. In this paper we propose optimizations of the solution including handling of write requests with a synchronous mode,...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Model of Volunteer Based Systems.
PublikacjaThere are two main approaches to processing tasks requiring high amounts of computational power. One approach is using clusters of mostly identical hardware, placed in dedicated locations. The other approach is outsourcing computing resources from large numbers of volunteers connected to the Internet. This chapter attempts to formulate a mathematical model of the volunteer based approach to distributed computations and apply it...
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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems
PublikacjaThis paper introduces approximate analytic quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO) procedures. We present a summary of extensive research into computing. In the performed comparative study we take into account the various approaches of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces; where some executive criteria,...
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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems
PublikacjaThis paper introduces approximate analytic quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO) procedures. We present a summary of extensive research into computing. In the performed comparative study we take into account the various approaches of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces; where some executive criteria,...
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Tuning matrix-vector multiplication on GPU
PublikacjaA matrix times vector multiplication (matvec) is a cornerstone operation in iterative methods of solving large sparse systems of equations such as the conjugate gradients method (cg), the minimal residual method (minres), the generalized residual method (gmres) and exerts an influence on overall performance of those methods. An implementation of matvec is particularly demanding when one executes computations on a GPU (Graphics...
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Auto-tuning methodology for configuration and application parameters of hybrid CPU + GPU parallel systems based on expert knowledge
PublikacjaAuto-tuning of configuration and application param- eters allows to achieve significant performance gains in many contemporary compute-intensive applications. Feasible search spaces of parameters tend to become too big to allow for exhaustive search in the auto-tuning process. Expert knowledge about the utilized computing systems becomes useful to prune the search space and new methodologies are needed in the face of emerging heterogeneous...