Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions Not only does this combination of a

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GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

IEEE Transactions on Pattern Analysis and Machine Intelligence

Background This paper investigates the use of a light stage to capture high-resolution, 3D facial surface textures and proposes novel methods to use the data for skin condition assessment. Materials and methods We introduce new methods for analysing 3D surface texture using high-resolution normal fields and apply these to the detection and assessment of skin conditions in human faces, specifically wrinkles, pores and acne. The use of high-resolution normal maps as input to our texture measures enables us to investigate the 3D nature of texture, while retaining aspects of some well-known 2D texture measures. The main contributions are as follows: the introduction of three novel methods for extracting texture descriptors from high-resolution surface orientation fields; a comparative study of 2D and 3D skin texture analysis techniques; and an extensive data set of high-resolution 3D facial scans presenting various skin conditions, with human ratings as "ground truth." Results Our results demonstrate an improvement on state-of-the-art methods for the analysis of pores and comparable results to the state of the art for wrinkles and acne using a considerably more compact model. Conclusions The use of high-resolution normal maps, captured by a light stage, and the methods described, represent an important new set of tools in the analysis of skin texture.

https://onlinelibrary.wiley.com/doi/epdf/10.1111/srt.12793

3D surface texture analysis of high-resolution normal fields for facial skin condition assessment.

A key problem in shape-from-shading is how to simultaneously satisfy data-closeness and regularisation (such as surface smoothness) constraints. This paper makes two contributions towards solving this problem. The first is to desc ribe a smoothness constraint which preserves surface structure by adaptively smoothing according to the intensity gradient magnitude. The second is to derive a framework which seeks to strictly satisfy this constraint while maintaining zero brightness error. Experimental results on both synthetic and real world imagery demonstrate that our method is both robust and accurate and outperforms a number of existing techniques.

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A shape-from-shading framework for satisfying data-closeness and structure-preserving smoothness constraints

In this paper we present methods for estimating shape from polarisation and shading information, i.e. photo-polarimetric shape estimation, under varying, but unknown, illumination, i.e. in an uncalibrated scenario. We propose several alternative photo-polarimetric constraints that depend upon the partial derivatives of the surface and show how to express them in a unified system of partial differential equations of which previous work is a special case. By careful combination and manipulation of the constraints, we show how to eliminate non-linearities such that a discrete version of the problem can be solved using linear least squares. We derive a minimal, combinatorial approach for two source illumination estimation which we use with RANSAC for robust light direction and intensity estimation. We also introduce a new method for estimating a polarisation image from multichannel data and provide methods for estimating albedo and refractive index. We evaluate lighting, shape, albedo and refractive index estimation methods on both synthetic and real-world data showing improvements over existing state-of-the-art.

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Uncalibrated, Two Source Photo-Polarimetric Stereo.

We present a new method for symmetry-factored statistical modelling of 3D shape. Our method comprises three novel components. First, a means to symmetrise a 3D mesh, regularised using the Laplace-Beltrami operator. Second, a symmetry-aware variant of Generalized Procrustes Analysis (GPA). Third, a means to compute a linear statistical shape model in which symmetry and asymmetric shape variation are modelled separately. We focus on human head data and build the first 3D morphable model of craniofacial asymmetry. The qualitative and quantitative evaluation demonstrates that the proposed model outperforms a linear model that does not decompose symmetric and asymmetric variation. It also validates that symmetry-aware GPA can improve the data generalisation and reconstruction ability of the standard PCA model. We will make our model and the implementation of our method publicly available1.

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Symmetry-Factored Statistical Modelling of Craniofacial Shape

We focus on the problem of developing a coupled statistical model that can be used to recover surface height from brightness images of faces The idea is to couple intensity and height by jointly modeling their combined variations The models are constructed by performing Principal Component Analysis (PCA) on the shape coefficients for both intensity and height training data By fitting the model to intensity data, the height information is implicitly recovered from the coupled shape parameters Experiments show that the methods generate accurate surfaces from out-of training intensity images

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William A. P. Smith

Papers

3D surface texture analysis of high-resolution normal fields for facial skin condition assessment.

A shape-from-shading framework for satisfying data-closeness and structure-preserving smoothness constraints

Uncalibrated, Two Source Photo-Polarimetric Stereo.

Symmetry-Factored Statistical Modelling of Craniofacial Shape

A coupled statistical model for face shape recovery