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Massively parallel non-stationary EEG data processing on GPGPU platforms with Morlet continuous wavelet transform

Ze Deng, Dan Chen, Yangyang Hu, Xiaoming Wu, Weizhou Peng, Xiaoli Li
2012 Journal of Internet Services and Applications  
In this paper, we proposed a massively parallel MCWT approach based on GPGPU to address this research challenge.  ...  Morlet continuous wavelet transform (MCWT) has been widely used to process non-stationary electroencephalogram (EEG) data.  ...  Introduction Most data from either natural phenomena or artificial sources are non-linear and non-stationary in nature [30] .  ... 
doi:10.1007/s13174-012-0071-1 fatcat:prwsxt5lwva5rapbrpvpmsweoy

A Massively Parallel Approach for Nonlinear Interdependency Analysis of Multivariate Signals with GPGPU

Dan Chen, Lizhe Wang, Dong Cui, Dongchuan Lu, Xiaoli Li, Samee U. Khan, Joanna Kolodziej
2012 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum  
Nonlinear interdependency (NLI) analysis is an effective method for measurement of synchronization among brain regions, which is an important feature of normal and abnormal brain functions.  ...  We developed a massively parallel approach to address this problem. The approach has dramatically improved the runtime performance.  ...  Our group has developed a GPGPU-enabled approach (1) to decompose a complex non-linear and non-stationary signal into a number of components each carrying the true physical characteristics in a frequency  ... 
doi:10.1109/ipdpsw.2012.257 dblp:conf/ipps/ChenWCLLKK12 fatcat:v7dutqmdejckfa7winoykxcvky

Parallel Processing of Massive EEG Data with MapReduce

Lizhe Wang, Dan Chen, Rajiv Ranjan, Samee U. Khan, Joanna KolOdziej, Jun Wang
2012 2012 IEEE 18th International Conference on Parallel and Distributed Systems  
As neural signals are non-stationary and non-linear in nature, it is almost impossible to understand their true physical dynamics until the recent advent of the Ensemble Empirical Mode Decomposition (EEMD  ...  The MapReduce programming mode is a promising parallel computing paradigm for data intensive computing.  ...  Neural signals are naturally nonlinear and non-stationary.  ... 
doi:10.1109/icpads.2012.32 dblp:conf/icpads/WangCRKKW12 fatcat:jqvsyobfl5hflovrajwq64maye

GPGPU Acceleration of All-Electron Electronic Structure Theory Using Localized Numeric Atom-Centered Basis Functions [article]

William Huhn and Björn Lange and Victor Wen-zhe Yu and Mina Yoon and Volker Blum
2019 arXiv   pre-print
We present an implementation of all-electron density-functional theory for massively parallel GPGPU-based platforms, using localized atom-centered basis functions and real-space integration grids.  ...  Special attention is paid to domain decomposition of the problem on non-uniform grids, which enables compute- and memory-parallel execution across thousands of nodes for real-space operations, e.g. the  ...  Rainer Johanni, deceased in 2012, who pioneered the distributed-parallel CPU version of the locally-indexed real-space Hamiltonian scheme that is a critical foundation of this work.  ... 
arXiv:1912.06636v1 fatcat:4m7nyw56jffyngpwqpf5i3kzzm

Efficacy of a GPGPU-Acceleration to Inundation Flow Simulation in Tonle Sap Lake in Cambodia

Takashi Nakamura, Shun Murakami, Lun Sambo, Hideto Fujii
2019 Engineering Journal  
The developed model is applied to a solution of seasonal inundation process for the 154 days in 2002. Calculated result is compared with observational data and satellite remote sensing.  ...  In order to overcome a huge computational cost for a prolonged analysis over an extensive area, the General-Purpose computing on Graphics Processing Units (GPGPU) technology is applied to the model.  ...  Acknowledgement Authors thank the Mekong River Commission (MRC), the Tonle Sap Authority and Ministry of Water Resources and the Meteorology Cambodia (MOWRAM) for providing the dataset and kind supports  ... 
doi:10.4186/ej.2019.23.1.151 fatcat:jdol7yscindo7osngcbx3pabnm

GPGPU-based Gaussian Filtering for Surface Metrological Data Processing

Yang Su, Zhijie Xu, Xiangqian Jiang
2008 2008 12th International Conference Information Visualisation  
A great deal of consideration and thanks must go to my family. My parents, ChengXiang and Sufen Su, continue to be my role models for living life with passion, creativity, and hard work.  ...  The acceleration performance of these models are evaluated in terms of the speed-up factor and the data accuracy, which enabled the generation of quantifiable benchmarks for evaluating consumer-grade parallel  ...  analysis and performance evaluation with real application data.  ... 
doi:10.1109/iv.2008.14 dblp:conf/iv/SuXJ08 fatcat:lpagxjxstjbj5lcdumztlpgolu

Particle Filtering: The Need for Speed

Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson
2010 EURASIP Journal on Advances in Signal Processing  
To achieve this, GPUs are equipped with a parallel architecture which can be exploited for general-purpose computing on GPU (GPGPU) as a complement to the central processing unit (CPU).  ...  The modifications made to obtain a parallel particle filter, especially for the resampling step, are discussed and the performance of the resulting GPU implementation is compared to the one achieved with  ...  GPUs offer low-cost and easily accessible single instruction multiple data (SIMD) parallel hardware-almost every new computer comes with a decent graphics card.  ... 
doi:10.1155/2010/181403 fatcat:yjvuujqaizefbe6vnhmwlzb2qm

Joint upsampling and noise reduction for real-time depth map enhancement

Kazuki Matsumoto, Chiyoung Song, Francois de Sorbier, Hideo Saito, Andrew J. Woods, Nicolas S. Holliman, Gregg E. Favalora
2014 Stereoscopic Displays and Applications XXV  
By benefiting from massively parallel computing capability of modern commodity GPUs, the system is able to maintain high frame rate.  ...  The amount of noise is reduced by accumulating the downsampled data simultaneously.  ...  Instead, our buffer is more suited for stationary camera with moving objects.  ... 
doi:10.1117/12.2039190 fatcat:oyfsvnxlcrfmthcpcmjzz2opdy

Hyper-Real-Time Ice Simulation and Modeling Using GPGPU

Shadi Alawneh, Roelof Dragt, Dennis Peters, Claude Daley, Stephen Bruneau
2015 IEEE transactions on computers  
GPGPU is the use of a GPU (graphics processing unit) to do general purpose scientific and engineering computing.  ...  The model for GPU computing is to use a CPU and GPU together in a heterogeneous co-processing computing platform.  ...  Massively parallel computation coupled with discrete event solutions for ice-ice and ice-structure interactions are combined to create a method to permit the rapid practical simulation of realistic ice  ... 
doi:10.1109/tc.2015.2409861 fatcat:upzn4lnpnvevzmi7xrxrl3x62q

Modular FEM framework "ModFem" for generic scientific parallel simulations

Michalik Kazimierz, Banas Krzysztof, Plaszewski Przemyslaw, Cybulka Pawel
2013 Computer Science  
The structure allows for reusing the sequential code for parallel environments, and also supports solving multi-physics and multi-scale problems.  ...  We present the design for, and implementation of, a flexible and robust parallel modular finite element (FEM) framework called ModFEM.  ...  Most real problems contain different non-linearities, and general error analysis becomes difficult or even impossible for them.  ... 
doi:10.7494/csci.2013.14.3.513 fatcat:632rfec2tjg7fgsnssk4jfeyli

Bringing Together Dynamic Geometry Software and the Graphics Processing Unit [article]

Aaron Montag, Jürgen Richter-Gebert
2018 arXiv   pre-print
We equip dynamic geometry software (DGS) with a user-friendly method that enables massively parallel calculations on the graphics processing unit (GPU).  ...  We ease the development of complex (mathematical) visualizations and provide a rapid-prototyping scheme for general-purpose computations (GPGPU).  ...  This scheme is suitable for massively parallel computations on the GPU. Example 7. A simple example is the function F (x, y, z) = x 2 +y 2 +z 2 −1 with V (F ) = S 2 .  ... 
arXiv:1808.04579v1 fatcat:tutap5rwuzcqxfk4rkpelbke2y

Using efficient parallelization in Graphic Processing Units to parameterize stochastic fire propagation models [article]

Mónica Denham, Karina Laneri
2017 arXiv   pre-print
Stochastic propagation was performed with a probability model that depends on aspect, slope, wind direction and vegetation type.  ...  The efficiency of the fire simulation procedure allowed us to also estimate the fire ignition point when it is unknown as well as its associated uncertainty, making this approach suitable for the analysis  ...  Even though application maps are squared data structures, and data increases in a quadratic form too, runtimes have a linear growth.  ... 
arXiv:1701.03549v2 fatcat:ucoah5szvncw5c42sfn3mhapki

GPU acceleration of an unmodified parallel finite element Navier-Stokes solver

Dominik Goddeke, Sven H.M. Buijssen, Hilmar Wobker, Stefan Turek
2009 2009 International Conference on High Performance Computing & Simulation  
linear solver.  ...  We have previously suggested a minimally invasive approach to include hardware accelerators into an existing large-scale parallel finite element PDE solver toolkit, and implemented it into our software  ...  The 'minimally invasive' concept of co-processor acceleration has been developed in close collaboration with Robert Strzodka, Jamaludin Mohd-Yusof and Patrick McCormick.  ... 
doi:10.1109/hpcsim.2009.5191718 dblp:conf/ieeehpcs/GoddekeBWT09 fatcat:mm4tch3fjnc3vgmh7hxkdnrq6u

Aggregate gaze visualization with real-time heatmaps

Andrew T. Duchowski, Margaux M. Price, Miriah Meyer, Pilar Orero
2012 Proceedings of the Symposium on Eye Tracking Research and Applications - ETRA '12  
Parallelization of the algorithm leads to substantial speedup over its CPU-based implementation and, for the first time, allows real-time rendering of heatmaps atop video.  ...  Abstract A GPU implementation is given for real-time visualization of aggregate eye movements (gaze) via heatmaps.  ...  Two parallel programming languages have emerged for massively parallel GPGPU tasks: CUDA and OpenCL [Kirk and Hwu 2010] .  ... 
doi:10.1145/2168556.2168558 dblp:conf/etra/DuchowskiPMO12 fatcat:orilo4mcqbgwlegg4bt2epiirq

GPGPU-based parallel computing applied in the FEM using the conjugate gradient algorithm: a review

Nileshchandra K Pikle, Shailesh R Sathe, Arvind Y Vyavhare
2018 Sadhana (Bangalore)  
General-purpose graphics processing units (GPGPUs) have been effectively utilized for the parallelization of FEM computations ever since 2007.  ...  These operations have the single-instruction multiple-data (SIMD) computation pattern, which is beneficial for shared-memory parallel architectures.  ...  The convergence rate of stationary iterative methods [11] such as the Gauss-Seidel, Jacobi, and successive overrelaxation (SOR) iterative methods is slower compared with that of non-stationary methods  ... 
doi:10.1007/s12046-018-0892-0 fatcat:igpuqhu6qfcjdo2zm6apnmpzhy
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