Ordinary Personal Computer Research Articles

Numerical search for the effective thermal conductivity of cracked media

Spacecraft parts accumulate damage during operation and defects that are invariably present even in new designs may grow. This leads to changes in the behavior of individual parts of the space vehicle and, consequently, to the risk of fracture. A more accurate assessment of spacecraft safety requires internal defects to be included in the material models under consideration. One of the main hazardous effects on space objects is multiple temperature heating and cooling due to periodic action of solar rays. This paper presents a study of thermal conduction of media containing cracks. It is carried out with the help of a technique developed by the authors to determine the effective thermal conductivity of materials and based on approximate numerical solution of the steady-state thermal conduction problem for a three-dimensional medium with cracks by the boundary element method. This technique allows to obtain the distribution of the temperature field and heat flux density at any point of the body under consideration, as well as to calculate the effective parameters of materials with high accuracy at relatively low calculation time using ordinary personal computers of average power. The basis of the numerical method presented in this paper is the decomposition of the desired solution into a series of some pre-calculated analytical solutions of the heat conduction equations. The dependence of the effective thermal conductivity on the density of thermally insulated cracks was considered. The formula of this dependence is proposed. Verification of the proposed methodology was carried out by comparing the numerical results of a number of problems with the results of other authors.

Coordinated lane-changing scheduling of multilane CAV platoons in heterogeneous scenarios

With the development of sensing, communication and automated driving technology, connected and automated vehicles (CAVs) are becoming promising solutions for future transport requirements. It is widely believed that a vehicle platoon is a good form to organize urban traffic in the CAV era. Due to the multicommodity nature of urban traffic streams, vehicles will continuously leave and join a multilane platoon, which inevitably gives rise to the need of lane changing within a multilane platoon. This paper studies the coordinated lane-changing scheduling problem in a CAV platoon, with the goal of transferring the platoon from an initial state to a target state to minimize a certain cost measurement (e.g., number of steps), while heterogeneous scenarios are considered. Two approaches, i.e., an exact and an approximate approach, are proposed. For the exact approach, we formulate an integer linear programming (ILP) model to identify the global optimal solution. Multiple objective functions are defined to meet the different needs. To relieve the computational issue of the exact approach, we further propose a tree-based heuristic search (THS), an approximate algorithm framework. THS is able to obtain an acceptable solution with negligible computational effort, and has the potential to handle the scheduling problem with more precise modeling or larger platoons. Numerical experiments are conducted to demonstrate the performance of different algorithms on both small- and large-scale cases (with up to 60 vehicles in a platoon), and the parameter combinations in the THS are tested for the optimal trade-off between solution quality and computational load. The findings indicate that ILP is practical for small- or medium-scale cases, which can generate multiple optimal solutions for different objectives; THS can solve large-scale cases in milliseconds on an ordinary personal computer, while the acquired solution is verified to be only slightly worse than the global optimum.

Methods and performance of a GPU-based pinwise two-step nodal code VANGARD

The methods and performance of a GPU-based pinwise two-step nodal core calculation code VANGARD are presented which is targeted for use in the commercial nuclear design analyses. In order to realize high-speed core cycle depletion with a single consumer-grade GPU mounted on ordinary personal computers, various elaborated computational methods are introduced as follows. The computationally intense pinwise nodal calculation is optimized by adaptive employment of low-order expansion. The two-level surface current correction method is used for updating pinwise incoming partial currents within the assembly-level coarse mesh finite difference framework. A cross section data compression technique is introduced to fit the enormous pinwise group constant data into the limited GPU memory. A massively parallelized depletion scheme based on the Chebyshev Rational Approximation Method is implemented. The neighbor-informed burnup correction method is developed to ensure the accuracy of the pinwise depletion for gadolinia-bearing pins. Performance examinations are performed for the realistic APR1400 and AP1000 core problems to demonstrate that three-dimensional pinwise cycle depletion can be completed within 3 minutes with high accuracy and resolution.

Image-based simulation of molecular diffusion on NMR Pulsed-Field Gradient experiments: Feasibility to estimate tortuosity and permeability of porous media

Nuclear Magnetic Resonance (NMR) is an important tool to assess physical quantities that characterize porous media such as reservoir rocks. Information about surface-to-volume ratio and micro-connectivity, for instance, are coded in the time-dependent diffusion coefficient of magnetized spins. In this work, we present an efficient computational implementation to perform image-based simulations of the NMR diffusion experiment in porous media by means of random walks. We enhance our decisions regarding computation that allow us to simulate hundreds of thousands of steps in a large volume of walkers in a matter of seconds on an ordinary personal computer. We validate the implementation against analytical solutions found in the literature and investigate the effects of varying some of the simulation parameters such as number of particles, step length, and image resolution, in the accuracy of results. We then simulate the diffusion in a dataset of digitally generated synthetic media to investigate the correlation of tortuosity, surface-to-volume ratio, and porosity with permeability, and fit exponential curves to explore these correlations. Finally, we perform simulations from microtomographic images of four rock samples and use the results in conjunction with the previously fitted curves to predict the permeability, and compare it to the gas permeability measured experimentally. Our results indicate that the diffusion experiment has the potential of helping in permeability prediction. In particular, they indicate that the tortuosity and the surface-to-volume ratio correlate better with permeability than the porosity. We hope that the present study may serve not only as a reference for those interested in simulating the NMR diffusion experiment but also to help in the design of new permeability prediction models.

FAST ALGORITHM FOR SOLVING A ONE-DIMENSIONAL UNCLOSED DESIRABLE NEIGHBORS PROBLEM

Contex. The paper formulates a general combinatorial problem for the desired neighbors. Possible areas of practical application of the results of its development are listed. Within the framework of this problem, an analysis of the scientific literature on the optimization of combinatorial problems of practical importance that are close in subject is carried out, on the basis of which the novelty of the formulated problem accepted for scientific and algorithmic development is established.
 Objective. For a particular case of the problem, the article formulates a one-dimensional unclosed integer combinatorial problem of practical importance about the desired neighbors on the example of the problem of distributing buyers on land plots, taking into account their recommendations on the desired neighborhood.
 Method. A method for solving the mentioned problem has been developed and an appropriate effective algorithm has been created, which for thousands of experimental sets of hundreds of distribution subjects allows to get the optimal result on an ordinary personal computer in less than a second of counting time. The idea of developing the optimization process is expressed, which doubles the practical effect of optimization by cutting off unwanted neighbors without worsening the maximum value of the desirability criterion.
 Results. The results of the work include the formulation of a one-dimensional unclosed combinatorial problem about the desired neighbors and an effective algorithm for its solution, which makes it possible to find one, several, and, if necessary, all the options for optimal distributions. The main results of the work can also include the concept and formulation of a general optimization combinatorial problem of desirable neighbors, which may have theoretical and practical prospects.
 Conclusions. The method underlying the algorithm for solving the problem allows, if necessary, to easily find all the best placement options, the number of which, as a rule, is very large. It is established that their number can be reduced with benefit up to one by reducing the number of undesirable neighborhoods, which contributes to improving the quality of filtered optimal distributions in accordance with this criterion. The considered problem can receive prospects for evolution and development in various subject areas of the economy, production, architecture, urban studies and other spheres.

Analysis and Improvement of Blockchain-Based Multilevel Privacy-Preserving Location Sharing Scheme for Telecare Medical Information Systems

Patient location sharing is an important part of modern smart healthcare and mobile medical services. Blockchain has many attractive properties and is suitable for managing patient locations in telecare medical information systems (TMIS). Recently, Ji et al. proposed a blockchain-based multilevel privacy-preserving location sharing (BMPLS) scheme for TMIS. In this paper, we show that Ji et al.’s BMPLS scheme does not achieve confidentiality and multilevel privacy-preserving. An adversary outside the system can use an ordinary personal computer to completely break the system within a dozen hours and obtain the location of any patient at any time. The adversary inside the system can use an ordinary personal computer to obtain the location of the designated patient within tens of seconds. Using salting technology, we propose an improved BMPLS scheme to fix our attacks. We also optimized the BMLS scheme to make it correct and executable. The security analysis shows that the improved BMPLS scheme achieves decentralization, untamperability, confidentiality, multilevel privacy-preserving, retrievability, and verifiability. The simulation shows that the improved BMPLS scheme is practical, the computational overhead of the location record phase is within 10 ms, and the computational overheads of the location sharing and location extraction phases are both within 30 ms.

Голографічні 3D-технології в освіті

The article considers the aspects of using modern information technologies in the educational process. The results of the use of computer technologies in conveying information to students, the role of the development of information technologies for the educational sphere, as well as the feasibility of using innovative methods in education are analyzed. Holographic 3D showcases and holographic technologies are one of the most innovative devices and technologies for educators. The use of holographic 3D showcases for the reproduction of multimedia presentations and demonstration of objects is a modern and progressive method of presenting educational material. The relevance of the article lies in the argumentation of the use of modern information technologies which facilitate the work of the teacher and increase the capabilities of the devices available in educational institutions. Portability, mobility, and easiness of use are the keys to the successful use of gadgets in educational institutions. The educational process is an integral part of human development. The further interest of the students and the results they will get depend on the method of presenting the information. A review of approaches to conveying information provides an algorithm for the successful presentation of material so that listeners could easily learn it and were interested in it. An important aspect of the educational process is the practical use of skills and the comparison of real objects and tasks with those that were covered in the educational process. The use of holographic models will give an opportunity to create a simulated model of anything, allowing students to understand the material better. The information technologies for the operation of holographic 3D showcases used for modeling tasks and examples are intuitive and optimized for the level of knowledge in IT of the average teacher and lecturer. It allows every teacher to create educational material, lessons, lectures, and practical or laboratory tasks on an ordinary personal computer without any problems. The article also describes the methodology of creating educational materials for a holographic 3D showcase which will optimize the process of developing bulk materials and help to understand better the specific features of the holographic 3D showcase functioning.

Rhythmic Control of Automated Traffic—Part II: Grid Network Rhythm and Online Routing

Connected and automated vehicle (CAV) technology is providing urban transportation managers tremendous opportunities for better operation of urban mobility systems. However, there are significant challenges in real-time implementation as the computational time of the corresponding operations optimization model increases exponentially with increasing vehicle numbers. Following the companion paper (Chen et al. 2021), which proposes a novel automated traffic control scheme for isolated intersections, this study proposes a network-level, real-time traffic control framework for CAVs on grid networks. The proposed framework integrates a rhythmic control method with an online routing algorithm to realize collision-free control of all CAVs on a network and achieve superior performance in average vehicle delay, network traffic throughput, and computational scalability. Specifically, we construct a preset network rhythm that all CAVs can follow to move on the network and avoid collisions at all intersections. Based on the network rhythm, we then formulate online routing for the CAVs as a mixed integer linear program, which optimizes the entry times of CAVs at all entrances of the network and their time–space routings in real time. We provide a sufficient condition that the linear programming relaxation of the online routing model yields an optimal integer solution. Extensive numerical tests are conducted to show the performance of the proposed operations management framework under various scenarios. It is illustrated that the framework is capable of achieving negligible delays and increased network throughput. Furthermore, the computational time results are also promising. The CPU time for solving a collision-free control optimization problem with 2,000 vehicles is only 0.3 second on an ordinary personal computer.

A New Challenge: Detection of Small-Scale Falling Rocks on Transportation Roads in Open-Pit Mines

In transportation at open-pit mines, rocks dropped as a mining truck is driven will wear out the tires of the vehicle, thus increasing the mining cost. In the case of autonomous vehicles, the vehicle must automatically detect rocks on the transportation roads during the driving process. This will be a new challenge: rough road, rocks of small size and irregular shape, long detection distance, etc. This paper presents a detection method based on light detection and ranging (lidar). It includes two stages: (1) using the modified cloth simulation method to filter out the ground points; (2) using the regional growth method based on grid division to cluster non-ground points. Experimental results show that the method can detect rocks with a size of 20–30 cm at a distance of 40 m in front of the vehicle, and it takes only 0.3 s on an ordinary personal computer (PC). This method is easy to understand, and it has fewer parameters to be adjusted. Therefore, it is a better method for detecting small, irregular obstacles on a low-speed, unstructured and rough road.

Intelligent design of large angle deflection beam splitter based on method of moving asymptotes

Photonic chip is a kind of integrated device that uses light as a carrier for information transportation and processing. Owing to its advantages of small size, lightweight, and low power consumption, photonic chip has become the most popular research topic nowadays. The beam splitter is a vital part of on-chip integration. For conventional beam splitting elements, Y-type and tree-branch output are the main elements, which are usually realized by interference principles. However, it is appropriate only for simple conventional beam splitter because the propagation direction of light cannot achieve large angle deflection. In the case of relay loading, optical amplification, pumping, and frequency upconversion, the vertical loading is often required without affecting the main optical path. To complete the large-angle deflection beam splitting, one needs to add a mirror to realize it or use a right-angle mirror structure for geometric double-sided reflection and splitting in traditional ways, but these structures are relatively complicated and difficult to complete on-chip integration. Based on previous work on inversely designed multi-channel wavelength routers and wide spectrum efficient focusing devices by using the intelligent algorithm, and combining the years of research on the coherent superposition theory of multi-scattering of the disordered medium, a large angle beam splitter that can realize from the near-infrared band is designed through using the intelligent algorithm. The beam splitter structure is based on AMTIR-1 glass, the part to be etched is air. The composition of AMTIR-1 is Ge<sub>33</sub>As<sub>12</sub>Se<sub>55</sub>. And the size of the structure is only 1 μm × 2 μm. The beam splitter can achieve 180° linear separation of beams in a range from 800 nm to 1100 nm, the beam splitting ratio of the entire waveband is approximately 1∶1, and the gross beam splitting efficiency is stable between 85% and 92%. Compared with several conventional structures with the same size, the efficiency of the beam splitter designed by this algorithm is higher. At the same time, the algorithm has the advantages of fast computation speed and small computation amount, and it can be completed only by ordinary personal computers without the support of hardware such as workstations. This intelligent algorithm can also be applied to the design of various passive photonic devices such as optical polarization splitters, routers, optical isolators, etc., providing an idea and reference for the design of integrated micro-nano photonic devices on high-density sheets.

Web-Based Technology for Remote Viewing of Radiological Images: App Validation.

BackgroundInternet technologies can create advanced and rich web-based apps that allow radiologists to easily access teleradiology systems and remotely view medical images. However, each technology has its own drawbacks. It is difficult to balance the advantages and disadvantages of these internet technologies and identify an optimal solution for the development of medical imaging apps.ObjectiveThis study aimed to compare different internet platform technologies for remotely viewing radiological images and analyze their advantages and disadvantages.MethodsOracle Java, Adobe Flash, and HTML5 were each used to develop a comprehensive web-based medical imaging app that connected to a medical image server and provided several required functions for radiological interpretation (eg, navigation, magnification, windowing, and fly-through). Java-, Flash-, and HTML5-based medical imaging apps were tested on different operating systems over a local area network and a wide area network. Three computed tomography colonography data sets and 2 ordinary personal computers were used in the experiment.ResultsThe experimental results demonstrated that Java-, Flash-, and HTML5-based apps had the ability to provide real-time 2D functions. However, for 3D, performances differed between the 3 apps. The Java-based app had the highest frame rate of volume rendering. However, it required the longest time for surface rendering and failed to run surface rendering in macOS. The HTML5-based app had the fastest surface rendering and the highest speed for fly-through without platform dependence. Volume rendering, surface rendering, and fly-through performances of the Flash-based app were significantly worse than those of the other 2 apps.ConclusionsOracle Java, Adobe Flash, and HTML5 have individual strengths in the development of remote access medical imaging apps. However, HTML5 is a promising technology for remote viewing of radiological images and can provide excellent performance without requiring any plug-ins.

A hardware intelligent processing accelerator for domestic service robots

ABSTRACT We present a method for implementing hardware intelligent processing accelerator on domestic service robots. These domestic service robots support human life; therefore, they are required to recognize environments using intelligent processing. Moreover, the intelligent processing requires large computational resources. Therefore, standard personal computers (PCs) with robot middleware on the robots do not have enough resources for this intelligent processing. We propose a ‘connective object for middleware to an accelerator (COMTA),’ which is a system that integrates hardware intelligent processing accelerators and robot middleware. Herein, by constructing dedicated architecture digital circuits, field-programmable gate arrays (FPGAs) accelerate intelligent processing. In addition, the system can configure and access applications on hardware accelerators via a robot middleware space; consequently, robotic engineers do not require the knowledge of FPGAs. We conducted an experiment on the proposed system by utilizing a human-following application with image processing, which is commonly applied in the robots. Experimental results demonstrated that the proposed system can be automatically constructed from a single-configuration file on the robot middleware and can execute the application 5.2 times more efficiently than an ordinary PC.

Numerical simulation of 3D Fox–Li integral equation described by Rayleigh–Sommerfeld diffraction for MEMS-VCSEL

The Fox–Li integral equation is famous as a simulation method for Fabry–Perot cavities. Three-dimensional and higher-order modes can be easily and precisely calculated using the equation and an ordinary personal computer. Fresnel diffraction is generally used as an optical propagation equation in such approaches. However, when considering an optical microcavity, Fresnel diffraction may not be appropriate because it includes the approximation that the propagation distance is larger than the wavelength. In this study, we applied Rayleigh–Sommerfeld diffraction because it is known to be the exact solution while considering optical diffraction for optical cavities comprising plane mirrors. We calculated the 3D Fox–Li integral equation using the Rayleigh–Sommerfeld diffraction, when the cavity condition differs from the approximation. We obtained the diffraction loss and mode profile and compared them with the numerical solution obtained using the Fresnel diffraction formula. Consequently, the diffraction loss was found to be different when the condition did not match the approximation. However, it was similar in the range with the approximation. We also confirmed that the diffraction loss can be determined by the Fresnel number under all conditions when using Rayleigh–Sommerfeld diffraction. In addition, we investigated the applicability of this method to an actual device such as MEMS-VCSEL. We demonstrate that the Fox–Li method described by the Rayleigh–Sommerfeld diffraction can be applied to various applications for micro-optical devices.

LtrDetector: A tool-suite for detecting long terminal repeat retrotransposons de-novo

BackgroundLong terminal repeat retrotransposons are the most abundant transposons in plants. They play important roles in alternative splicing, recombination, gene regulation, and defense mechanisms. Large-scale sequencing projects for plant genomes are currently underway. Software tools are important for annotating long terminal repeat retrotransposons in these newly available genomes. However, the available tools are not very sensitive to known elements and perform inconsistently on different genomes. Some are hard to install or obsolete. They may struggle to process large plant genomes. None can be executed in parallel out of the box and very few have features to support visual review of new elements. To overcome these limitations, we developed LtrDetector, which uses techniques inspired by signal-processing.ResultsWe compared LtrDetector to LTR_Finder and LTRharvest, the two most successful predecessor tools, on six plant genomes. For each organism, we constructed a ground truth data set based on queries from a consensus sequence database. According to this evaluation, LtrDetector was the most sensitive tool, achieving 16–23% improvement in sensitivity over LTRharvest and 21% improvement over LTR_Finder. All three tools had low false positive rates, with LtrDetector achieving 98.2% precision, in between its two competitors. Overall, LtrDetector provides the best compromise between high sensitivity and low false positive rate while requiring moderate time and utilizing memory available on personal computers.ConclusionsLtrDetector uses a novel methodology revolving around k-mer distributions, which allows it to produce high-quality results using relatively lightweight procedures. It is easy to install and use. It is not species specific, performing well using its default parameters on genomes of varying size and repeat content. It is automatically configured for parallel execution and runs efficiently on an ordinary personal computer. It includes a k-mer scores visualization tool to facilitate manual review of the identified elements. These features make LtrDetector an attractive tool for future annotation projects involving long terminal repeat retrotransposons.

A Comparative Land-Cover Classification Feature Study of Learning Algorithms: DBM, PCA, and RF Using Multispectral LiDAR Data

Multispectral LiDAR, characterization of completeness, and consistency of spectrum and spatial geometric data provide a new data source for land cover classification. However, how to choose the optimal features for a given set of land covers is an open problem for effective land cover classification. To address this problem, we propose a comparative scheme, which investigates a popular deep learning (deep Boltzmann machine, DBM) model for high-level feature representation and widely used machine learning methods for low-level feature extraction and selection [principal component analysis (PCA) and random forest (RF)] in land cover classification. The comparative study was conducted on the multispectral LiDAR point clouds, acquired by a Teledyne Optech's Titan airborne system. The deep learning-based high-level feature representation experimental results showed that, on an ordinary personal computer or workstation, this method required larger training samples and more computational complexity than the machine learning-based low-level feature extraction and selection methods. However, our comparative experiments demonstrated that the classification accuracies of the DBM-based method were higher than those of the RF-based and PCA-based methods using multispectral LiDAR data.

New speedup algorithms for nonlinear dynamic time history analysis of supertall building structures under strong earthquakes

SummarySome speedup algorithms oriented to improving computational efficiency of nonlinear dynamic time history analysis of supertall buildings structures excited by strong earthquakes are proposed. In order to minimize Jacobian factorizations, the inexact Newton algorithm combined with the sparse Cholesky matrix factorization (INC) is suggested with an unbalance‐independent relation for the determination of a forcing term in the INC. Further, some shared memory parallel computing techniques are incorporated into the state transformation procedures developed previously (parallel state transformation procedure) and the matrix factorization (parallelized factorization) for full utilization of the resources of an ordinary personal computer. All the algorithms are integrated in a finite element program specialized in time history analysis of aseismic supertall building structures, with some features from OpenSees. Computational efficiency, as well as accuracy, of the proposed speedup algorithms is demonstrated on one 12‐story reinforced concrete frame (K1) and 4 frame‐core‐tube supertall buildings (S1–S4). The results from the demonstration indicate that, as the number of degrees of freedom increases, the proportion of time consumed in Jacobian factorization becomes relatively more dominant. The combination of the INC and the parallelized factorization can achieve better acceleration performance in this case. Factors associated with the forcing term of the INC have much influence on computational efficiency and should be selected based on building scale. Combination of all the algorithms in the biggest model (S4) yields an average of 28.72 of acceleration ratio even with peak ground acceleration equal to 3.2 g. In all cases considered, a desirable agreement in structural response is always reached between conventional time history analysis method and the method using the proposed speedup algorithms.

An efficient traffic sign recognition based on graph embedding features

Traffic sign recognition (TSR) is one of the significant modules of an intelligent transportation system. It instantly assists the drivers to efficiently recognize the traffic sign. Recognition of traffic sign is a large-scale feature learning problem with different real-world appearances. The main goal of this paper is to develop an efficient TSR method, which can run on an ordinary personal computer (PC). In the proposed method, GIST descriptors of the traffic sign images are extracted and subjected to graph-based linear discriminant analysis to reduce the dimension. Moreover, it effectively learns the discriminative subspace through the graph structure with increased computational efficiency. An efficient TSR module is built by conducting series of experiments using support vector machine, extreme learning machine, and k-nearest neighbor (k-NN) classifiers on available public datasets. Our approach achieved the highest recognition accuracy of 96.33 and 97.79% using k-NN classifier for German Traffic Sign Recognition Benchmark (GTSRB) and Belgium Traffic Sign Classification Benchmark (BelgiumTSC), respectively. Also it achieved 99.1% accuracy for a subcategory of GTSRB traffic signs and able to predict the class of unknown traffic sign within 0.0019 s on an ordinary PC. Hence, it can be used in real-world driver assistance system.

Numerical Method for the Design of Healing Chamber in Additive-Manufactured Dental Implants.

The inclusion of a healing chamber in dental implants has been shown to promote biological healing. In this paper, a novel numerical approach to the design of the healing chamber for additive-manufactured dental implants is proposed. This study developed an algorithm for the modeling of bone growth and employed finite element method in ANSYS to facilitate the design of healing chambers with a highly complex configuration. The model was then applied to the design of dental implants for insertion into the posterior maxillary bones. Two types of ITI® solid cylindrical screwed implant with extra rectangular-shaped healing chamber as an initial design are adopted, with which to evaluate the proposed system. This resulted in several configurations for the healing chamber, which were then evaluated based on the corresponding volume fraction of healthy surrounding bone. The best of these implants resulted in a healing chamber surrounded by around 9.2% more healthy bone than that obtained from the original design. The optimal design increased the contact area between the bone and implant by around 52.9%, which is expected to have a significant effect on osseointegration. The proposed approach is highly efficient which typically completes the optimization of each implant within 3–5 days on an ordinary personal computer. It is also sufficiently general to permit extension to various loading conditions.

High-performance GPU parallel solver for 3D modeling of electron transfer during ion–surface interaction

This study presents parallelized time-dependent Schrödinger equation solver (GPU TDSE Solver) for 3D modeling of resonant electron transfer (RCT) during ion–surface interactions and atomic collisions. The computer modeling of RCT process is based on the numerical one-electron TDSE solution in relatively large spatial domain (about 103–104 nm3). Due to the numerical complexity of direct 3D TDSE solution in such domains, most of RCT calculations use approximations that reduce problem to 2D calculations (e.g. cylindrical symmetry). Last years the TDSE Solver was developed for 3D RCT modeling in large-scale nanosystems (Gainullin and Sonkin, 2015). It was shown to have rather good performance due to the effective parallel implementation of simple numerical scheme on GPUs (explicit finite-difference method in Cartesian coordinates). Note, that usage of FDM in Cartesian coordinates requires ∼100 times greater numerical grid, comparing to the finite-element or finite-volume methods. For the majority of RCT problems the calculations transfer to the cylindrical coordinates decreases the size of numerical grid by an order of magnitude without loss of the calculations precision. The main problem in the transfer to the cylindrical coordinates is that explicit numerical schemes for parabolic equations, including TDSE, are unstable near the axis ρ=0. This study presents hybrid numerical scheme, which eliminates this instability and preserves the effective parallelization on GPUs. The performance of new version of the GPU TDSE Solver, based on the hybrid numerical scheme, was found to be 6 times greater comparing to the previous version. Such performance gain is stipulated by less discrete points, required for the FDM implementation in cylindrical coordinates. Due to reduction of required GPU memory, new version of GPU TDSE Solver can handle spatial domains about 103 nm3 using an ordinary personal computer (equipped with modern GPU, e.g. Tesla k20 or better) or up to 105 nm3 using supercomputers. GPU TDSE Solver was applied to the calculation of the resonant charge transfer in nanosystems. The calculated neutralization probability for Li+ ions impinging on the Ag(100) surface shows a good quantitative agreement with the experimental data.

A modified two-stage Markov clustering algorithm for large and sparse networks

BackgroundGraph-based hierarchical clustering algorithms become prohibitively costly in both execution time and storage space, as the number of nodes approaches the order of millions. ObjectiveA fast and highly memory efficient Markov clustering algorithm is proposed to perform the classification of huge sparse networks using an ordinary personal computer. MethodsImprovements compared to previous versions are achieved through adequately chosen data structures that facilitate the efficient handling of symmetric sparse matrices. Clustering is performed in two stages: the initial connected network is processed in a sparse matrix until it breaks into isolated, small, and relatively dense subgraphs, which are then processed separately until convergence is obtained. An intelligent stopping criterion is also proposed to quit further processing of a subgraph that tends toward completeness with equal edge weights. The main advantage of this algorithm is that the necessary number of iterations is separately decided for each graph node. ResultsThe proposed algorithm was tested using the SCOP95 and large synthetic protein sequence data sets. The validation process revealed that the proposed method can reduce 3–6 times the processing time of huge sequence networks compared to previous Markov clustering solutions, without losing anything from the partition quality. ConclusionsA one-million-node and one-billion-edge protein sequence network defined by a BLAST similarity matrix can be processed with an upper-class personal computer in 100 minutes. Further improvement in speed is possible via parallel data processing, while the extension toward several million nodes needs intermediary data storage, for example on solid state drives.