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Scaling-up spatially-explicit ecological models using graphics processors
2011
Ecological Modelling
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Here, we describe the use of graphics processors to efficiently solve spatially explicit ecological models at large spatial scale using the CUDA language extension. ...
Using these models, we show that the solutions of models on large spatial grids can be obtained on graphics processors with up to two orders of magnitude reduction in simulation time relative to normal ...
Acknowledgement We would like to thank Fred Guichard for comments on a draft of the manuscript. ...
doi:10.1016/j.ecolmodel.2011.06.004
fatcat:fq64assiq5aw5e66iuxksrroqq
Mathematical modeling of nonlinear effects in dynamic of interacting plankton and fish populations of Azov Sea
2019
COMPUTATIONAL MATHEMATICS AND INFORMATION TECHNOLOGIES
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Paper covers the research of nonlinear effects in population dynamics of the pelengas commercial fish of the Azov Sea at low and high size taking into account the Allee effect, competition for resources ...
The system of grid equations of large dimension, arising at discretization, has been solved on the basis of a two-layer variational type methodthe minimum corrections method having the maximum convergence ...
𝑃 3 ) in CSR format on GPUs using CUDA technology. ...
doi:10.23947/2587-8999-2019-2-2-83-103
fatcat:krkqmlhmbfatxjnhr4qtninoge
An optimized D2Q37 Lattice Boltzmann code on GP-GPUs
2013
Computers & Fluids
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We describe the implementation of a thermal compressible Lattice Boltzmann algorithm on an NVIDIA Tesla C2050 system based on the Fermi GP-GPU. ...
We describe the overall organization of the algorithm and give details on its implementations. Efficiency ranges from 25% to 31% of the double precision peak performance of the GP-GPU. ...
Acknowledgments We would like to thank the Jülich Supercomputing Center (JSC) for providing access to the Judge system [14]. ...
doi:10.1016/j.compfluid.2012.06.003
fatcat:xpsp3l5nunc57b6ue727q2qm7m
A successful parallel implementation of NSGA-II on GPU for the energy dispatch problem on hydroelectric power plants
2016
2016 IEEE Congress on Evolutionary Computation (CEC)
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The energy dispatch optimization problem consists in determining which generation units need to be on or off and what is their respective power-set, so that both the overall HPP costs is minimized and ...
This paper presents a parallel implementation of NSGA-II on GPU, to solve the energy dispatch problem of a HPP complaying with the real time restrictions posed by the operation of a real HPP from the reception ...
The CUDA toolkit version is the 7.0, Matlab version is the 2014a and the operational system is CentOS 7. ...
doi:10.1109/cec.2016.7744337
dblp:conf/cec/OliveiraMMAC16
fatcat:ka4hhm2ek5b6zgcptzp7s4dxx4
CUDA Based Enhanced Differential Evolution: A Computational Analysis
2012
ECMS 2012 Proceedings edited by: K. G. Troitzsch, M. Moehring, U. Lotzmann
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This research explores the advantages of applying a evolutionary algorithm (EA) on the GPU in terms of computational speedups. ...
This research utilizes the Nvidia CUDA framework for GPU computation. ...
Section 4 describes the code design on the GPU, whereas the experimentation and analysis (Section 5) compares the obtained results. The paper is concluded in Section 6. ...
doi:10.7148/2012-0399-0404
dblp:conf/ecms/DavendraGBS12
fatcat:kduyh5q2xrcv3pbfuq2czspicy
Accelerating viability kernel computation with CUDA architecture: application to bycatch fishery management
2016
Computational Management Science
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Dierent parts of the algorithm are parallelized on the GPU device and we 14 test the algorithm on a dynamical system of theoretical population growth. 15 We study computing time gains as a function of ...
Brias Irstea, UR LISC Laboratoire d'ingénierie des systèmes complexes, 2 Antoine Brias et al. sions. ...
This model is a simple dynamical system of population growth on a 256 bounded space without any predator. ...
doi:10.1007/s10287-015-0246-x
fatcat:5a2ef3i3szarfn2wjeerzwdzyu
GPUs Outperform Current HPC and Neuromorphic Solutions in Terms of Speed and Energy When Simulating a Highly-Connected Cortical Model
2018
Frontiers in Neuroscience
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In addition, we find that, across a range of GPU systems, the energy to solution as well as the energy per synaptic event of the microcircuit simulation is as much as 14× lower than either on SpiNNaker ...
Instead, SNN models tend to be developed and simulated on computers or clusters of computers with standard von Neumann CPU architectures. ...
FUNDING This work was funded by the EPSRC (Brains on Board project, grant number EP/P006094/1). ...
doi:10.3389/fnins.2018.00941
pmid:30618570
pmcid:PMC6299048
fatcat:xtzqfak7m5avhli42wcpwkqteq
Parallel Programming Approaches for an Agent-based Simulation of Concurrent Pandemic and Seasonal Influenza Outbreaks
2013
Procedia Computer Science
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In addition to the OpenMP parallelization, a proposed CUDA implementation is also presented. ...
We simulated the outbreak in a population of 1,000,000 individuals to evaluate algorithm performance and results. ...
Introduction It is currently impossible to predict the upcoming of a Pandemic Influenza (PI) virus, and its impact on the population and the public health systems. ...
doi:10.1016/j.procs.2013.05.389
fatcat:z47milj2ejhrjkxbr4vzcis2jy
Multi-core and many-core SPMD parallel algorithms for construction of basins of attraction
2019
Journal of Theoretical and Applied Mechanics
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The algorithm is tested on three systems, the classic nonlinear Duffing system, a non-ideal system exhibiting the Sommerfeld effect and an immunodynamic system. ...
Construction of basins of attraction, used for the analysis of nonlinear dynamical systems which present multistability, are computationaly very expensive. ...
Other examples are single step implicit algorithms (Modak and Sotelino, 2002) , population dynamics problems (Ramachandramurthi et al., 1997; Michaels and Zubik-Kowal, 2012 ) and molecular dynamics ...
doi:10.15632/jtam-pl/112463
fatcat:6fnlwazs45hnxbtuf3sal5g3tu
A GPU-Based Enhanced Genetic Algorithm for Power-Aware Task Scheduling Problem in HPC Cloud
[chapter]
2014
Lecture Notes in Computer Science
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The GA is developed with two versions: (1) BKGPUGA, which is an adaptively implemented using NVIDIA's Compute Unified Device Architecture (CUDA) framework; and (2) SGA, which is a serial GA version on ...
TM E5-2630 (2.3 GHz) on same input problem size. ...
Call n is the total number of cell populations, p is the probability change of each cell, q=(1 -p). ...
doi:10.1007/978-3-642-55032-4_16
fatcat:2kzrksnhbnarvcaqg3mfpo7ema
GPU based parallel genetic algorithm for solving an energy efficient dynamic flexible flow shop scheduling problem
2018
Journal of Parallel and Distributed Computing
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In order to achieve a speedup to meet the short response in the dynamic environment, the proposed method is designed to be highly consistent with NVIDIA CUDA software model. ...
Most efforts considering energy issues in scheduling problems have focused on static scheduling. ...
Few works take [8, 9] reactive approaches into consideration for supporting energy efficient dynamic systems. ...
doi:10.1016/j.jpdc.2018.07.022
fatcat:o647d7fomzbw5i2vq2esxqqspe
Enhancing Metaheuristic-based Virtual Screening Methods on Massively Parallel and Heterogeneous Systems
2016
Proceedings of the 7th International Workshop on Programming Models and Applications for Multicores and Manycores - PMAM'16
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Our solution finds a good workload balance via dynamic assignment of jobs to heterogeneous resources which perform independent metaheuristic executions under different molecular interactions. ...
In this paper, we analyze the current landscape of computation, where massive parallelism and heterogeneity are today the main ingredients in large-scale computing systems, to enhance metaheuristic-based ...
P ercent = 0.5, and so on. ...
doi:10.1145/2883404.2883413
dblp:conf/ppopp/ImbernonCG16
fatcat:ihoiqcbvjvcu7pkqfq2awxqbx4
Fast simulations of highly-connected spiking cortical models using GPUs
[article]
2020
arXiv
pre-print
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The numerical solution of the differential equations of the dynamics of the AdEx models is performed through a parallel implementation, written in CUDA-C++, of the fifth-order Runge-Kutta method with adaptive ...
Compared to other highly-parallel systems, GPU-accelerated solutions have the advantage of a relatively low cost and a great versatility, thanks also to the possibility of using the CUDA-C/C++ programming ...
1 , p 2 ) = − i p 1,i log(p 1,i /p 2,i ), where p 1 and p 2 are two distributions, and the index i runs on the sampling points of the two distributions. ...
arXiv:2007.14236v3
fatcat:6jwlx5bchranjn2hyvolphjwu4
Accelerating QDP++/Chroma on GPUs
[article]
2011
arXiv
pre-print
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Interoperability with existing Krylov space solvers is demonstrated and special attention is paid on 'Chroma readiness'. ...
Extensions to the C++ implementation of the QCD Data Parallel Interface are provided enabling acceleration of expression evaluation on NVIDIA GPUs. ...
In case all objects are cached, i.e. available on the device, the availability of the CUDA kernel is queried via the dynamic linking loader. ...
arXiv:1111.5596v1
fatcat:yv3gwkessfbpbjxcrpx2f6ytxq
Adapting Particle Filter Algorithms to Many-Core Architectures
2013
2013 IEEE 27th International Symposium on Parallel and Distributed Processing
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It is ideal for non-linear, non-Gaussian dynamical systems with applications in many areas, such as computer vision, robotics, and econometrics. ...
The particle filter is a Bayesian estimation technique based on Monte Carlo simulation. ...
This system of dynamical equations represents our a priori p(x k |x k−1 ). The camera detects the object in its own frame of reference. ...
doi:10.1109/ipdps.2013.88
dblp:conf/ipps/ChitchianASKS13
fatcat:lvjezokuxbdq5ndtqlokhoarze
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