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Buwalda, F.J.L. (author), de Goede, Erik (author), Knepflé, Maxim (author), Vuik, Cornelis (author)The accuracy, stability and computational efficiency of numerical methods on central processing units (CPUs) for the depth-averaged shallow water equations were well covered in the literature. A large number of these methods were already developed and compared. However, on graphics processing units (GPUs), such comparisons are relatively scarce....journal article 2023
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Sun, W. (author), Katsifodimos, A (author), Hai, R. (author)Recent advances in Graphic Processing Units (GPUs) have facilitated a significant performance boost for database operators, in particular, joins. It has been intensively studied how conventional join implementations, such as hash joins, benefit from the massive parallelism of GPUs. With the proliferation of machine learning, more databases...conference paper 2023
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Hogervorst, T.A. (author), Nane, R. (author), Marchiori, Giacomo (author), Qiu, Tong Dong (author), Blatt, Markus (author), Rustad, Alf Birger (author)Scientific computing is at the core of many High-Performance Computing applications, including computational flow dynamics. Because of the utmost importance to simulate increasingly larger computational models, hardware acceleration is receiving increased attention due to its potential to maximize the performance of scientific computing....journal article 2022
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Bulavintsev, V. (author), Zhdanov, Dmitry D. (author)We propose a generalized method for adapting and optimizing algorithms for efficient execution on modern graphics processing units (GPU). The method consists of several steps. First, build a control flow graph (CFG) of the algorithm. Next, transform the CFG into a tree of loops and merge non-parallelizable loops into parallelizable ones....conference paper 2021
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Machidon, Alina L. (author), Machidon, Octavian M. (author), Ciobanu, C.B. (author), Ogrutan, Petre L. (author)Remote sensing data has known an explosive growth in the past decade. This has led to the need for efficient dimensionality reduction techniques, mathematical procedures that transform the high-dimensional data into a meaningful, reduced representation. Projection Pursuit (PP) based algorithms were shown to be efficient solutions for...journal article 2020
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Ahmed, N. (author), Bertels, K.L.M. (author), Al-Ars, Z. (author)The seeding heuristic is widely used in many DNA analysis applications to speed up the analysis time. In many applications, seeding takes a substantial amount of the total execution time. In this paper, we present an efficient GPU implementation for computing maximal exact matching (MEM) seeds in long DNA reads. We applied various...conference paper 2020
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van Kessel, L.C.P.M. (author), Hagen, C.W. (author)Monte Carlo simulations are frequently used to describe electron–matter interaction in the 0–50 keV energy range. It often takes hours to simulate electron microscope images using first-principle physical models. In an attempt to maintain a reasonable speed, empirical models are sometimes used. We present an open-source software package with...journal article 2020
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Khait, M. (author)Numerical simulation is based on space and time discretization providing a trade-off between accuracy and computational performance. The operator-based Linearization (OBL) approach introduces an additional discretization domain for the physical description of fluid and rock. Delft Advanced Research Terra Simulator (DARTS) is a general-purpose...doctoral thesis 2019
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Houtgast, E.J. (author)Developments in sequencing technology have drastically reduced the cost of DNA sequencing. The raw sequencing data being generated requires processing through computationally demanding suites of bioinformatics algorithms called genomics pipelines. The greatly decreased cost of sequencing has resulted in its widespread adoption, and the amount of...doctoral thesis 2019
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Liu, S. (author), Oosterlee, C.W. (author), Bohte, Sander M. (author)This paper proposes a data-driven approach, by means of an Artificial Neural Network (ANN), to value financial options and to calculate implied volatilities with the aim of accelerating the corresponding numerical methods. With ANNs being universal function approximators, this method trains an optimized ANN on a data set generated by a...journal article 2019
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Houtgast, E.J. (author), Sima, V.M. (author), Bertels, K.L.M. (author), Al-Ars, Z. (author)We present our work on hardware accelerated genomics pipelines, using either FPGAs or GPUs to accelerate execution of BWA-MEM, a widely-used algorithm for genomic short read mapping. The mapping stage can take up to 40% of overall processing time for genomics pipelines. Our implementation offloads the Seed Extension function, one of the main...journal article 2018
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Aissa, M.H. (author), Verstraete, Tom (author), Vuik, Cornelis (author)A computational Fluid Dynamics (CFD) code for steady simulations solves a set of non-linear partial differential equations using an iterative time stepping process, which could follow an explicit or an implicit scheme. On the CPU, the difference between both time stepping methods with respect to stability and performance has been well covered in...journal article 2017
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Smaragdos, Georgios (author), Chatzikonstantis, Georgios (author), Kukreja, Rahul (author), Sidiropoulos, Harry (author), Rodopoulos, Dimitrios (author), Sourdis, Ioannis (author), Al-Ars, Z. (author), Kachris, Christoforos (author), Soudris, Dimitrios (author), De Zeeuw, Chris I. (author), Strydis, C. (author)Objective. The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the...journal article 2017
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Houtgast, E.J. (author), Sima, V.M. (author), Marchiori, G. (author), Bertels, K.L.M. (author), Al-Ars, Z. (author)Next Generation Sequencing techniques have dramatically reduced the cost of sequencing genetic material, resulting in huge amounts of data being sequenced. The processing of this data poses huge challenges, both from a performance perspective, as well as from a power-efficiency perspective. Heterogeneous computing can help on both fronts, by...conference paper 2016
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Houtgast, E.J. (author), Sima, V.M. (author), Bertels, K.L.M. (author), Al-Ars, Z. (author)We are rapidly entering the era of genomics. The dramatic cost reduction of DNA sequencing due to the introduction of Next Generation Sequencing (NGS) techniques has resulted in an exponential growth of genetics data. The amount of data generated, and its associated processing into useful information, poses serious computational challenges. Here...abstract 2016
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Gupta, R. (author)In this work we study the implementations of deflation and preconditioning techniques for solving ill-conditioned linear systems using iterative methods. Solving such systems can be a time-consuming process because of the jumps in the coefficients due to large difference in material properties. We have developed implementations of the iterative...doctoral thesis 2015
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Schalkwijk, J. (author)De vorige eeuw was getuige van de opkomst van numerieke weer- en klimaatmodellen. Weersvoorspelling, voorheen een empirische procedure gebaseerd op de persoonlijke ervaring van de meteoroloog, ontwikkelde zich tot een wetenschappelijke methode om de toekomstige toestand van de atmosfeer te voorspellen op basis van de huidige toestand en tendens....doctoral thesis 2015
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Knibbe, H.P. (author)The oil and gas industry makes use of computational intensive algorithms to provide an image of the subsurface. The image is obtained by sending wave energy into the subsurface and recording the signal required for a seismic wave to reflect back to the surface from the Earth interfaces that may have different physical properties. A seismic wave...doctoral thesis 2015
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Performance modeling and optimization of sparse matrix-vector multiplication on NVIDIA CUDA platformXu, S. (author), Xue, W. (author), Lin, H.X. (author)In this article, we discuss the performance modeling and optimization of Sparse Matrix-Vector Multiplication (SpMV) on NVIDIA GPUs using CUDA. SpMV has a very low computation-data ratio and its performance is mainly bound by the memory bandwidth. We propose optimization of SpMV based on ELLPACK from two aspects: (1) enhanced performance for the...journal article 2011