EM3DANI: A Julia package for fully anisotropic 3D forward modeling of electromagnetic data

Geophysics ◽  
2021 ◽  
pp. 1-45
Author(s):  
Ronghua Peng ◽  
Bo Han ◽  
Yajun Liu ◽  
Xiangyun Hu
Keyword(s):  
High Performance ◽  
Three Dimensional ◽  
Anisotropic Media ◽  
Forward Modeling ◽  
Hydrocarbon Exploration ◽  
Third Party ◽  
Low Level ◽  
Numerical Computing ◽  
Computationally Intensive ◽  
High Level

Forward modeling is vital for three-dimensional (3D) inversion and interpretation of electromagnetic (EM) data in anisotropic media, which is one of the major challenges in the field of EM geophysics. However, there are few freely available 3D codes that are capable of modeling EM responses in fully anisotropic media. Besides, most of the existing 3D EM codes are written in low-level languages such as C and Fortran, making them difficult to read, maintain and extend. Taking advantage of recent progress in computer technology and numerical methods, we have developed an open-source package for forward modeling of frequency-domain EM fields in a fully 3D anisotropic earth (EM3DANI) using the Julia language, a relatively young, high-level programming language with a focus on high performance. Based on a mimetic finite-volume (MFV) discretization of the governing equations, the modeling algorithm is expressed in an abstract form in terms of matrices/vectors and thus can be easily implemented by using any high-level language commonly-used for numerical computing. Existing libraries written in low-level languages can be easily integrated into a Julia code without the so-called two-language problem, thus we have exploited several mature third-party packages to deal with computationally intensive parts of the forward modeling, which guarantees high stability and efficiency. We have elaborated the structure of the package, paying special attention to code usability, readability and extendability, while striving to retain versatility and high performance. The effectiveness of the code is demonstrated through two 1D synthetic examples for magnetotellurics (MT) and controlled-source electromagnetics (CSEM) problems, respectively. High accuracy and efficiency can be achieved for both 1D examples. We further present a 3D example mimicking marine CSEM survey scenario for hydrocarbon exploration. The simulation results indicate that the effect of the anisotropy on forward responses is significant, and can be comparable to that of the target reservoir.

Urban network of China from the perspective of population mobility: Three-dimensional co-occurrence of nodes and links

2021 ◽  
pp. 0308518X2199781
Author(s):  
Xinyue Luo ◽  
Mingxing Chen
Keyword(s):  
Three Dimensional ◽  
Geographical Distance ◽  
Two Dimensional ◽  
Population Mobility ◽  
Urban Network ◽  
Urban Networks ◽  
Low Level ◽  
Medium Level ◽  
High Level ◽  
External Connections

The nodes and links in urban networks are usually presented in a two-dimensional(2D) view. The co-occurrence of nodes and links can also be realized from a three-dimensional(3D) perspective to make the characteristics of urban network more intuitively revealed. Our result shows that the external connections of high-level cities are mainly affected by the level of cities(nodes) and less affected by geographical distance, while medium-level cities are affected by the interaction of the level of cities(nodes) and geographical distance. The external connections of low-level cities are greatly restricted by geographical distance.

scholarly journals High-Level Parallel Ant Colony Optimization with Algorithmic Skeletons

2021 ◽  
Author(s):  
Breno A. de Melo Menezes ◽  
Nina Herrmann ◽  
Herbert Kuchen ◽  
Fernando Buarque de Lima Neto
Keyword(s):  
Ant Colony Optimization ◽  
High Performance ◽  
Optimization Problems ◽  
Programming Model ◽  
Parallel Implementation ◽  
Ant Colony ◽  
Algorithmic Skeletons ◽  
Low Level ◽  
Programming Patterns ◽  
High Level

AbstractParallel implementations of swarm intelligence algorithms such as the ant colony optimization (ACO) have been widely used to shorten the execution time when solving complex optimization problems. When aiming for a GPU environment, developing efficient parallel versions of such algorithms using CUDA can be a difficult and error-prone task even for experienced programmers. To overcome this issue, the parallel programming model of Algorithmic Skeletons simplifies parallel programs by abstracting from low-level features. This is realized by defining common programming patterns (e.g. map, fold and zip) that later on will be converted to efficient parallel code. In this paper, we show how algorithmic skeletons formulated in the domain specific language Musket can cope with the development of a parallel implementation of ACO and how that compares to a low-level implementation. Our experimental results show that Musket suits the development of ACO. Besides making it easier for the programmer to deal with the parallelization aspects, Musket generates high performance code with similar execution times when compared to low-level implementations.

scholarly journals A Uniform Architecture Design for Accelerating 2D and 3D CNNs on FPGAs

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 65 ◽  
Author(s):  
Zhiqiang Liu ◽  
Paul Chow ◽  
Jinwei Xu ◽  
Jingfei Jiang ◽  
Yong Dou ◽  
...  
Keyword(s):  
Design Space ◽  
State Of The Art ◽  
Three Dimensional ◽  
Architecture Design ◽  
Computer Vision Applications ◽  
Computationally Intensive ◽  
On Chip ◽  
3D Cnn ◽  
High Level ◽  
2D And 3D

Three-dimensional convolutional neural networks (3D CNNs) have gained popularity in many complicated computer vision applications. Many customized accelerators based on FPGAs are proposed for 2D CNNs, while very few are for 3D CNNs. Three-D CNNs are far more computationally intensive and the design space for 3D CNN acceleration has been further expanded since one more dimension is introduced, making it a big challenge to accelerate 3D CNNs on FPGAs. Motivated by the finding that the computation patterns of 2D and 3D CNNs are very similar, we propose a uniform architecture design for accelerating both 2D and 3D CNNs in this paper. The uniform architecture is based on the idea of mapping convolutions to matrix multiplications. A customized mapping module is developed to generate the feature matrix tilings with no need to store the entire enlarged feature matrix on-chip or off-chip, a splitting strategy is adopted to reconstruct a convolutional layer to adapt to the on-chip memory capacity, and a 2D multiply-and-accumulate (MAC) array is adopted to compute matrix multiplications efficiently. For demonstration, we implement an accelerator prototype with a high-level synthesis (HLS) methodology on a Xilinx VC709 board and test the accelerator on three typical CNN models: AlexNet, VGG16, and C3D. Experimental results show that the accelerator achieves state-of-the-art throughput performance on both 2D and 3D CNNs, with much better energy efficiency than the CPU and GPU.

scholarly journals Three-Dimensional Dirac Semimetal/Organic Thin Film Heterojunction Photodetector With Fast Response and High Detectivity

2021 ◽  
Vol 9 ◽  
Author(s):  
Qi Liu ◽  
Ming Yang ◽  
Jiangwei Zhang ◽  
Mingliang Yang ◽  
Jun Wang ◽  
...  
Keyword(s):  
Thin Film ◽  
High Performance ◽  
Three Dimensional ◽  
Fast Response ◽  
Current Response ◽  
Organic Thin Film ◽  
Small Current ◽  
Dirac Semimetal ◽  
High Level ◽  
P Type

As a typical three-dimensional Dirac semimetal (3D DSM), Cd3As2 possess ultrahigh carrier mobility, high level of full spectral absorption, fast electron transmission speed, and high photocurrent response, which enable wide applications in infrared photodetector. However, the large dark current of the detector based on Cd3As2 thin film limits the application of the small current response. Hence, we demonstrated heterojunction photodetectors based on n-type 3D DSM Cd3As2 (pristine and Zn doped) and p-type organic (PbPc) by depositing PbPc thin film on Cd3As2 (pristine and Zn doped) thin film using thermal deposition method. These photodetectors can detect the radiation wavelength from 405 to 1,550 nm at room temperature. It is remarkable that this thin film heterojunction photodetector exhibits high detectivity (3.95 × 1011 Jones) and fast response time (160 μs) under bias voltage, which is significantly improved vs. that of Cd3As2-based devices. The excellent performances are attributed to the strong built-in electric field at the interface of p-n junction, which is beneficial for efficient photocarriers collection and transportation. These results show that DSM/organic thin film heterojunction has excellent performance in the application of photodetectors. By combining 3D DSM with organic to form heterojunction, it provides a feasible solution for high-performance photodetectors.

scholarly journals High-performance Python for crystallographic computing

2019 ◽  
Vol 52 (4) ◽  
pp. 882-897 ◽  
Author(s):  
A. Boulle ◽  
J. Kieffer
Keyword(s):  
Programming Language ◽  
High Performance ◽  
Scientific Computing ◽  
State Of The Art ◽  
Third Party ◽  
Improve Performance ◽  
Python Language ◽  
Python Programming Language ◽  
Numerical Computing ◽  
Python Programming

The Python programming language, combined with the numerical computing library NumPy and the scientific computing library SciPy, has become the de facto standard for scientific computing in a variety of fields. This popularity is mainly due to the ease with which a Python program can be written and executed (easy syntax, dynamical typing, no compilation etc.), coupled with the existence of a large number of specialized third-party libraries that aim to lift all the limitations of the raw Python language. NumPy introduces vector programming, improving execution speeds, whereas SciPy brings a wealth of highly optimized and reliable scientific functions. There are cases, however, where vector programming alone is not sufficient to reach optimal performance. This issue is addressed with dedicated compilers that aim to translate Python code into native and statically typed code with support for the multi-core architectures of modern processors. In the present article it is shown how these approaches can be efficiently used to tackle different problems, with increasing complexity, that are relevant to crystallography: the 2D Laue function, scattering from a strained 2D crystal, scattering from 3D nanocrystals and, finally, diffraction from films and multilayers. For each case, detailed implementations and explanations of the functioning of the algorithms are provided. Different Python compilers (namely NumExpr, Numba, Pythran and Cython) are used to improve performance and are benchmarked against state-of-the-art NumPy implementations. All examples are also provided as commented and didactic Python (Jupyter) notebooks that can be used as starting points for crystallographers curious to enter the Python ecosystem or wishing to accelerate their existing codes.

A review on manufacture of polymeric foam cores for sandwich structures of complex shape in automotive applications

2021 ◽  
pp. 109963622110305
Author(s):  
Youming Chen ◽  
Raj Das
Keyword(s):  
Mechanical Properties ◽  
High Performance ◽  
Complex Shape ◽  
Complex Geometry ◽  
Sandwich Structures ◽  
Three Dimensional ◽  
High Density ◽  
Automotive Applications ◽  
Polymeric Foam ◽  
High Level

In this work, polymeric foam thermoforming, foam injection moulding, bead foaming and film foaming were reviewed in an effort to explore feasible processes to manufacture sandwich structures of complex geometry for automotive applications. Injection moulded foams generally suffer from high density, poor cell morphologies and unnecessary skin layers. Foamable films currently available are pressure-induced. In order for foamable films to produce foam, high uniformly-distributed pressure needs to be applied, which makes it difficult to manufacture foam parts of three-dimensional complex geometry with foamable films. The majority of commercial high-performance foam cores can be thermoformed. Ideally, thermoformed foam cores would have good mechanical properties if high-performance foam sheets are used. However, the mechanical properties of foams might be reduced during the process of thermoforming, especially around corners. Bead foaming offers a high level of freedom in foam geometry to be moulded, and inserts can be integrated into foam cores during the process of moulding. Moreover, foam cores with high density in high stressed areas and low density in low stressed areas can be manufactured with foam beads of different densities. However, due to nonhomogeneous degree of fusion and weak bonds and voids between beads, bead foams generally show mechanical properties lower than their block counterpart. Relatively speaking, thermoforming with high-performance foam sheets and moulding with high-performance foam beads hold great potentials for mass production of sandwich cores of complex geometry for automotive applications. However, further investigation on the mechanical properties of thermoformed foams and high-performance bead foams is still in need to confirm their suitability.

scholarly journals Scientific Computing on the Itanium® Processor

2002 ◽  
Vol 10 (4) ◽  
pp. 329-337 ◽  
Author(s):  
Bruce Greer ◽  
John Harrison ◽  
Greg Henry ◽  
Wei Li ◽  
Peter Tang
Keyword(s):  
Linear Algebra ◽  
High Performance ◽  
Scientific Computing ◽  
Peak Performance ◽  
Low Level ◽  
Architectural Features ◽  
Transcendental Functions ◽  
High Performance Computer ◽  
High Level ◽  
Engineering Computing

The 64-bit Intel® Itanium® architecture is designed for high-performance scientific and enterprise computing, and the Itanium processor is its first silicon implementation. Features such as extensive arithmetic support, predication, speculation, and explicit parallelism can be used to provide a sound infrastructure for supercomputing. A large number of high-performance computer companies are offering Itanium® -based systems, some capable of peak performance exceeding 50 GFLOPS. In this paper we give an overview of the most relevant architectural features and provide illustrations of how these features are used in both low-level and high-level support for scientific and engineering computing, including transcendental functions and linear algebra kernels.

scholarly journals Three-Dimensional Computer Model of Brainstem Respiratory Neuronal Circuits - Application for Research in Respirology

2013 ◽  
Vol 13 (Supplement-1) ◽  
pp. 7-14
Author(s):  
S. Gavliakova ◽  
J. Plevkova ◽  
J. Jakus ◽  
I. Poliacek
Keyword(s):  
Programming Languages ◽  
Computer Model ◽  
Ex Vivo ◽  
Three Dimensional ◽  
Neuronal Circuits ◽  
Spatial Image ◽  
The Matrix ◽  
Computationally Intensive ◽  
High Level

Abstract Methods that had been applied to study central neuronal circuits regulating cough and respiratory reflexes so far rely on recording performed in vivo, ex vivo, micro injecting and lesion methods. Based on the available data it is clear that this network is complicated, multilevel, holarchical, undergoing reconfiguration under afferent inputs. For many students and researchers it is complicated to get a virtual spatial image of these cooperating neuronal populations. The project was aimed to create graphical three-dimensional computer model of the brainstem using environment MATLAB and the matrix algebra to visualize neuron localization within the brainstem. Relevant data for the model had been taken from recent and also former research papers published in particular areas. This model may help scientists to visualize groups of neurons, help them to find targets for microinjecting or lesion studies together with stereotaxic positioning. The model is upgradeable and highly flexible for future use, research and teaching applications in MATLAB environment. MATLAB is a high-level language and interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming languages

Experience of using three-dimensional inversion for the large volume of magnetotelluric data

2019 ◽  
pp. 84-87
Author(s):  
S. V. Zaytsev
Keyword(s):  
Computer Technology ◽  
Large Volume ◽  
High Performance ◽  
Three Dimensional ◽  
Hydrocarbon Exploration ◽  
Huge Amount ◽  
3D Inversion ◽  
Magnetotelluric Data ◽  
Geophysical Field ◽  
Wide Range

When switching to 3D inversion of MT data, the requirement for computer technology is significantly increased. In this paper we will discuss a few examples of 3D inversion of electromagnetic geophysical field data with the usage of “Lomonosov” supercomputer and show its effectiveness on several geological objects. Each object is associated with a variety of problems: from search for shallow ore to regional hydrocarbon exploration. But all these objects contain a large volume of measurements obtaining qualitative results for which requires a huge amount of time. So that the use of 3D inversion with a high-performance computational complex makes it possible to obtain a qualitative result of solving a wide range of problems.

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