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https://www.readbyqxmd.com/read/28818036/ecccl-parallelized-gpu-implementation-of-ensemble-classifier-chains
#1
Mona Riemenschneider, Alexander Herbst, Ari Rasch, Sergei Gorlatch, Dominik Heider
BACKGROUND: Multi-label classification has recently gained great attention in diverse fields of research, e.g., in biomedical application such as protein function prediction or drug resistance testing in HIV. In this context, the concept of Classifier Chains has been shown to improve prediction accuracy, especially when applied as Ensemble Classifier Chains. However, these techniques lack computational efficiency when applied on large amounts of data, e.g., derived from next-generation sequencing experiments...
August 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28768689/accelerating-wright-fisher-forward-simulations-on-the-graphics-processing-unit
#2
David S Lawrie
Forward Wright-Fisher simulations are powerful in their ability to model complex demography and selection scenarios, but suffer from slow execution on the CPU, thus limiting their usefulness. The single-locus Wright-Fisher forward algorithm is, however, exceedingly parallelizable, with many steps which are so-called embarrassingly parallel, consisting of a vast number of individual computations that are all independent of each other and thus capable of being performed concurrently. The rise of modern Graphics Processing Units (GPUs) and programming languages designed to leverage the inherent parallel nature of these processors have allowed researchers to dramatically speed up many programs that have such high arithmetic intensity and intrinsic concurrency...
August 2, 2017: G3: Genes—Genomes—Genetics
https://www.readbyqxmd.com/read/28749354/real-time-cloth-rendering-with-fiber-level-detail
#3
Kui Wu, Cem Yuksel
Modeling cloth with fiber-level geometry can produce highly realistic details. However, rendering fiber-level cloth models not only has a high memory cost but it also has a high computation cost even for offline rendering applications. In this paper we present a real-time fiber-level cloth rendering method for current GPUs. Our method procedurally generates fiber-level geometric details on-the-fly using yarn-level control points for minimizing the data transfer to the GPU. We also reduce the rasterization operations by collectively representing the fibers near the center of each ply that form the yarn structure...
July 26, 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/28746339/openmm-7-rapid-development-of-high-performance-algorithms-for-molecular-dynamics
#4
Peter Eastman, Jason Swails, John D Chodera, Robert T McGibbon, Yutong Zhao, Kyle A Beauchamp, Lee-Ping Wang, Andrew C Simmonett, Matthew P Harrigan, Chaya D Stern, Rafal P Wiewiora, Bernard R Brooks, Vijay S Pande
OpenMM is a molecular dynamics simulation toolkit with a unique focus on extensibility. It allows users to easily add new features, including forces with novel functional forms, new integration algorithms, and new simulation protocols. Those features automatically work on all supported hardware types (including both CPUs and GPUs) and perform well on all of them. In many cases they require minimal coding, just a mathematical description of the desired function. They also require no modification to OpenMM itself and can be distributed independently of OpenMM...
July 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28692677/fux-sim-implementation-of-a-fast-universal-simulation-reconstruction-framework-for-x-ray-systems
#5
Monica Abella, Estefania Serrano, Javier Garcia-Blas, Ines García, Claudia de Molina, Jesus Carretero, Manuel Desco
The availability of digital X-ray detectors, together with advances in reconstruction algorithms, creates an opportunity for bringing 3D capabilities to conventional radiology systems. The downside is that reconstruction algorithms for non-standard acquisition protocols are generally based on iterative approaches that involve a high computational burden. The development of new flexible X-ray systems could benefit from computer simulations, which may enable performance to be checked before expensive real systems are implemented...
2017: PloS One
https://www.readbyqxmd.com/read/28685445/a-new-method-based-on-graphics-processing-units-for-fast-near-infrared-optical-tomography
#6
Jingjing Jiang, Linda Ahnen, Alexander Kalyanov, Scott Lindner, Martin Wolf, Salvador Sanchez Majos
The accuracy of images obtained by Diffuse Optical Tomography (DOT) could be substantially increased by the newly developed time resolved (TR) cameras. These devices result in unprecedented data volumes, which present a challenge to conventional image reconstruction techniques. In addition, many clinical applications require taking photons in air regions like the trachea into account, where the diffusion model fails. Image reconstruction techniques based on photon tracking are mandatory in those cases but have not been implemented so far due to computing demands...
2017: Advances in Experimental Medicine and Biology
https://www.readbyqxmd.com/read/28680387/event-driven-random-back-propagation-enabling-neuromorphic-deep-learning-machines
#7
Emre O Neftci, Charles Augustine, Somnath Paul, Georgios Detorakis
An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28666314/gpu-powered-model-analysis-with-pysb-cupsoda
#8
Leonard A Harris, Marco S Nobile, James C Pino, Alexander L R Lubbock, Daniela Besozzi, Giancarlo Mauri, Paolo Cazzaniga, Carlos F Lopez
Summary: A major barrier to the practical utilization of large, complex models of biochemical systems is the lack of open-source computational tools to evaluate model behaviors over high-dimensional parameter spaces. This is due to the high computational expense of performing thousands to millions of model simulations required for statistical analysis. To address this need, we have implemented a user-friendly interface between cupSODA, a GPU-powered kinetic simulator, and PySB, a Python-based modeling and simulation framework...
June 28, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28663861/autofocus-method-for-automated-microscopy-using-embedded-gpus
#9
J M Castillo-Secilla, M Saval-Calvo, L Medina-Valdès, S Cuenca-Asensi, A Martínez-Álvarez, C Sánchez, G Cristóbal
In this paper we present a method for autofocusing images of sputum smears taken from a microscope which combines the finding of the optimal focus distance with an algorithm for extending the depth of field (EDoF). Our multifocus fusion method produces an unique image where all the relevant objects of the analyzed scene are well focused, independently to their distance to the sensor. This process is computationally expensive which makes unfeasible its automation using traditional embedded processors. For this purpose a low-cost optimized implementation is proposed using limited resources embedded GPU integrated on cutting-edge NVIDIA system on chip...
March 1, 2017: Biomedical Optics Express
https://www.readbyqxmd.com/read/28659654/real-time-implementation-of-anti-scatter-grid-artifact-elimination-method-for-high-resolution-x-ray-imaging-cmos-detectors-using-graphics-processing-units-gpus
#10
R Rana, S V Setlur Nagesh, D R Bednarek, S Rudin
Scatter is one of the most important factors effecting image quality in radiography. One of the best scatter reduction methods in dynamic imaging is an anti-scatter grid. However, when used with high resolution imaging detectors these grids may leave grid-line artifacts with increasing severity as detector resolution improves. The presence of such artifacts can mask important details in the image and degrade image quality. We have previously demonstrated that, in order to remove these artifacts, one must first subtract the residual scatter that penetrates through the grid followed by dividing out a reference grid image; however, this correction must be done fast so that corrected images can be provided in real-time to clinicians...
February 11, 2017: Proceedings of SPIE
https://www.readbyqxmd.com/read/28658298/bayesian-lasso-and-multinomial-logistic-regression-on-gpu
#11
Rok Češnovar, Erik Štrumbelj
We describe an efficient Bayesian parallel GPU implementation of two classic statistical models-the Lasso and multinomial logistic regression. We focus on parallelizing the key components: matrix multiplication, matrix inversion, and sampling from the full conditionals. Our GPU implementations of Bayesian Lasso and multinomial logistic regression achieve 100-fold speedups on mid-level and high-end GPUs. Substantial speedups of 25 fold can also be achieved on older and lower end GPUs. Samplers are implemented in OpenCL and can be used on any type of GPU and other types of computational units, thereby being convenient and advantageous in practice compared to related work...
2017: PloS One
https://www.readbyqxmd.com/read/28644816/fast-and-accurate-poisson-denoising-with-trainable-nonlinear-diffusion
#12
Wensen Feng, Peng Qiao, Yunjin Chen
The degradation of the acquired signal by Poisson noise is a common problem for various imaging applications, such as medical imaging, night vision, and microscopy. Up to now, many state-of-the-art Poisson denoising techniques mainly concentrate on achieving utmost performance, with little consideration for the computation efficiency. Therefore, in this paper we aim to propose an efficient Poisson denoising model with both high computational efficiency and recovery quality. To this end, we exploit the newly developed trainable nonlinear reaction diffusion (TNRD) model which has proven an extremely fast image restoration approach with performance surpassing recent state-of-the-arts...
June 20, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28636811/performance-evaluation-of-gpu-parallelization-space-time-adaptive-algorithms-and-their-combination-for-simulating-cardiac-electrophysiology
#13
Rafael S Oliveira, Bernardo M Rocha, Denise Burgarelli, Wagner Meira, Christakis Constantinides, Rodrigo Weber Dos Santos
The use of computer models as a tool for the study and understanding of the complex phenomena of cardiac electrophysiology has attained increased importance nowadays. At the same time, the increased complexity of the biophysical processes translates into complex computational and mathematical models. In order to speed up cardiac simulations and to allow more precise and realistic uses, two different techniques have been traditionally exploited: parallel computing and sophisticated numerical methods. In this work, we combine a modern parallel computing technique based on multicore and graphics processing units (GPUs), and a sophisticated numerical method based on a new space-time adaptive algorithm...
June 21, 2017: International Journal for Numerical Methods in Biomedical Engineering
https://www.readbyqxmd.com/read/28636392/hybrid-cpu-gpu-integral-engine-for-strong-scaling-ab-initio-methods
#14
Jörg Kussmann, Christian Ochsenfeld
We present a parallel integral algorithm for two-electron contributions occurring in Hartree-Fock and hybrid density functional theory that allows for a strong scaling parallelization on inhomogeneous compute clusters. With a particular focus on graphic processing units, we show that our approach allows an efficient use of CPUs and graphics processing units (GPUs) simultaneously, although the different architectures demand conflictive strategies in order to ensure efficient program execution. Furthermore, we present a general strategy to use large basis sets like quadruple-ζ split valence on GPUs and investigate the balance between CPUs and GPUs depending on l-quantum numbers of the corresponding basis functions...
June 21, 2017: Journal of Chemical Theory and Computation
https://www.readbyqxmd.com/read/28618232/toward-fast-and-accurate-binding-affinity-prediction-with-pmemdgti-an-efficient-implementation-of-gpu-accelerated-thermodynamic-integration
#15
Tai-Sung Lee, Yuan Hu, Brad Sherborne, Zhuyan Guo, Darrin M York
We report the implementation of the thermodynamic integration method on the pmemd module of the AMBER 16 package on GPUs (pmemdGTI). The pmemdGTI code typically delivers over 2 orders of magnitude of speed-up relative to a single CPU core for the calculation of ligand-protein binding affinities with no statistically significant numerical differences and thus provides a powerful new tool for drug discovery applications.
June 23, 2017: Journal of Chemical Theory and Computation
https://www.readbyqxmd.com/read/28600826/tinker-openmm-absolute-and-relative-alchemical-free-energies-using-amoeba-on-gpus
#16
Matthew Harger, Daniel Li, Zhi Wang, Kevin Dalby, Louis Lagardère, Jean-Philip Piquemal, Jay Ponder, Pengyu Ren
The capabilities of the polarizable force fields for alchemical free energy calculations have been limited by the high computational cost and complexity of the underlying potential energy functions. In this work, we present a GPU-based general alchemical free energy simulation platform for polarizable potential AMOEBA. Tinker-OpenMM, the OpenMM implementation of the AMOEBA simulation engine has been modified to enable both absolute and relative alchemical simulations on GPUs, which leads to a ∼200-fold improvement in simulation speed over a single CPU core...
September 5, 2017: Journal of Computational Chemistry
https://www.readbyqxmd.com/read/28580909/the-dynamo-package-for-tomography-and-subtomogram-averaging-components-for-matlab-gpu-computing-and-ec2-amazon-web-services
#17
Daniel Castaño-Díez
Dynamo is a package for the processing of tomographic data. As a tool for subtomogram averaging, it includes different alignment and classification strategies. Furthermore, its data-management module allows experiments to be organized in groups of tomograms, while offering specialized three-dimensional tomographic browsers that facilitate visualization, location of regions of interest, modelling and particle extraction in complex geometries. Here, a technical description of the package is presented, focusing on its diverse strategies for optimizing computing performance...
June 1, 2017: Acta Crystallographica. Section D, Structural Biology
https://www.readbyqxmd.com/read/28572719/multi-gpu-acceleration-of-branchless-distance-driven-projection-and-backprojection-for-clinical-helical-ct
#18
Ayan Mitra, David G Politte, Bruce R Whiting, Jeffrey F Williamson, Joseph A O'Sullivan
Model-based image reconstruction (MBIR) techniques have the potential to generate high quality images from noisy measurements and a small number of projections which can reduce the x-ray dose in patients. These MBIR techniques rely on projection and backprojection to refine an image estimate. One of the widely used projectors for these modern MBIR based technique is called branchless distance driven (DD) projection and backprojection. While this method produces superior quality images, the computational cost of iterative updates keeps it from being ubiquitous in clinical applications...
January 2017: Journal of Imaging Science and Technology
https://www.readbyqxmd.com/read/28561575/employing-opencl-to-accelerate-ab-initio-calculations-on-graphics-processing-units
#19
Jörg Kussmann, Christian Ochsenfeld
We present an extension of our graphics processing units (GPU)-accelerated quantum chemistry package to employ OpenCL compute kernels, which can be executed on a wide range of computing devices like CPUs, Intel Xeon Phi, and AMD GPUs. Here, we focus on the use of AMD GPUs and discuss differences as compared to CUDA-based calculations on NVIDIA GPUs. First illustrative timings are presented for hybrid density functional theory calculations using serial as well as parallel compute environments. The results show that AMD GPUs are as fast or faster than comparable NVIDIA GPUs and provide a viable alternative for quantum chemical applications...
May 31, 2017: Journal of Chemical Theory and Computation
https://www.readbyqxmd.com/read/28508345/deep-monocular-3d-reconstruction-for-assisted-navigation-in-bronchoscopy
#20
Marco Visentini-Scarzanella, Takamasa Sugiura, Toshimitsu Kaneko, Shinichiro Koto
PURPOSE: In bronchoschopy, computer vision systems for navigation assistance are an attractive low-cost solution to guide the endoscopist to target peripheral lesions for biopsy and histological analysis. We propose a decoupled deep learning architecture that projects input frames onto the domain of CT renderings, thus allowing offline training from patient-specific CT data. METHODS: A fully convolutional network architecture is implemented on GPU and tested on a phantom dataset involving 32 video sequences and [Formula: see text]60k frames with aligned ground truth and renderings, which is made available as the first public dataset for bronchoscopy navigation...
July 2017: International Journal of Computer Assisted Radiology and Surgery
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