Search results for: computation offloading
542 Cloud-Based Mobile-to-Mobile Computation Offloading
Authors: Ebrahim Alrashed, Yousef Rafique
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Mobile devices have drastically changed the way we do things on the move. They are being extremely relied on to perform tasks that are analogous to desktop computer capability. There has been a rapid increase of computational power on these devices; however, battery technology is still the bottleneck of evolution. The primary modern approach day approach to tackle this issue is offloading computation to the cloud, proving to be latency expensive and requiring high network bandwidth. In this paper, we explore efforts to perform barter-based mobile-to-mobile offloading. We present define a protocol and present an architecture to facilitate the development of such a system. We further highlight the deployment and security challenges.Keywords: computational offloading, power conservation, cloud, sandboxing
Procedia PDF Downloads 382541 Crow Search Algorithm-Based Task Offloading Strategies for Fog Computing Architectures
Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara
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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.Keywords: IoT, fog computing, task offloading, efficient crow search algorithm
Procedia PDF Downloads 46540 Deep Reinforcement Learning-Based Computation Offloading for 5G Vehicle-Aware Multi-Access Edge Computing Network
Authors: Ziying Wu, Danfeng Yan
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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network
Procedia PDF Downloads 106539 WiFi Data Offloading: Bundling Method in a Canvas Business Model
Authors: Majid Mokhtarnia, Alireza Amini
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Mobile operators deal with increasing in the data traffic as a critical issue. As a result, a vital responsibility of the operators is to deal with such a trend in order to create added values. This paper addresses a bundling method in a Canvas business model in a WiFi Data Offloading (WDO) strategy by which some elements of the model may be affected. In the proposed method, it is supposed to sell a number of data packages for subscribers in which there are some packages with a free given volume of data-offloaded WiFi complimentary. The paper on hands analyses this method in the views of attractiveness and profitability. The results demonstrate that the quality of implementation of the WDO strongly affects the final result and helps the decision maker to make the best one.Keywords: bundling, canvas business model, telecommunication, WiFi data offloading
Procedia PDF Downloads 193538 Influence of Mooring Conditions on Side-By-Side Offloading System Safety Performance
Authors: Liu Shengnan, Sun Liping, Zhu Jianxun
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Based on three dimensional potential flow theory, hydrodynamic response analysis is carried on the multi floating bodies system composed of FPSO moored with yoke and shuttle tanker. It considered hydrodynamic interaction between FPSO and shuttle tanker, interaction between the hull and yoke mooring systems, hawsers, fenders, and then focuses on hawsers of the side-by-side offloading system. The influence of hawsers parameters on system safety is studied in respects of hawser stiffness, length and arrangement. Through analysis in different environment conditions and two typical loading conditions, it can be found that a better safety performance can be achieved through these three ways including enlarging the number of hawsers as well as the stiffness of hawsers, changing the length and arrangement of hawsers.Keywords: yoke mooring, side-by-side offloading, multi floating body, hawser, safety
Procedia PDF Downloads 421537 Artificial Intelligent-Based Approaches for Task Offloading, Resource Allocation and Service Placement of Internet of Things Applications: State of the Art
Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib
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In order to support the continued growth, critical latency of IoT applications, and various obstacles of traditional data centers, mobile edge computing (MEC) has emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. By adopting a MEC structure, IoT applications could be executed locally, on an edge server, different fog nodes, or distant cloud data centers. However, we are often faced with wanting to optimize conflicting criteria such as minimizing energy consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge devices and trying to keep high performance (reducing response time, increasing throughput and service availability) at the same time. Achieving one goal may affect the other, making task offloading (TO), resource allocation (RA), and service placement (SP) complex processes. It is a nontrivial multi-objective optimization problem to study the trade-off between conflicting criteria. The paper provides a survey on different TO, SP, and RA recent multi-objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications.Keywords: mobile edge computing, multi-objective optimization, artificial intelligence approaches, task offloading, resource allocation, service placement
Procedia PDF Downloads 107536 Indexing and Incremental Approach Using Map Reduce Bipartite Graph (MRBG) for Mining Evolving Big Data
Authors: Adarsh Shroff
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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.Keywords: big data, map reduce, incremental processing, iterative computation
Procedia PDF Downloads 342535 Verifiable Secure Computation of Large Scale Two-Point Boundary Value Problems Using Certificate Validation
Authors: Yogita M. Ahire, Nedal M. Mohammed, Ahmed A. Hamoud
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Scientific computation outsourcing is gaining popularity because it allows customers with limited computing resources and storage devices to outsource complex computation workloads to more powerful service providers. However, it raises some security and privacy concerns and challenges, such as customer input and output privacy, as well as cloud cheating behaviors. This study was motivated by these concerns and focused on privacy-preserving Two-Point Boundary Value Problems (BVP) as a common and realistic instance for verifiable safe multiparty computing. We'll look at the safe and verifiable schema with correctness guarantees by utilizing standard multiparty approaches to compute the result of a computation and then solely using verifiable ways to check that the result was right.Keywords: verifiable computing, cloud computing, secure and privacy BVP, secure computation outsourcing
Procedia PDF Downloads 91534 Dissociation of CDS from CVA Valuation Under Notation Changes
Authors: R. Henry, J-B. Paulin, St. Fauchille, Ph. Delord, K. Benkirane, A. Brunel
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In this paper, the CVA computation of interest rate swap is presented based on its rating. Rating and probability default given by Moody’s Investors Service are used to calculate our CVA for a specific swap with different maturities. With this computation, the influence of rating variation can be shown on CVA. The application is made to the analysis of Greek CDS variation during the period of Greek crisis between 2008 and 2011. The main point is the determination of correlation between the fluctuation of Greek CDS cumulative value and the variation of swap CVA due to change of ratingKeywords: CDS, computation, CVA, Greek crisis, interest rate swap, maturity, rating, swap
Procedia PDF Downloads 303533 Aperiodic and Asymmetric Fibonacci Quasicrystals: Next Big Future in Quantum Computation
Authors: Jatindranath Gain, Madhumita DasSarkar, Sudakshina Kundu
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Quantum information is stored in states with multiple quasiparticles, which have a topological degeneracy. Topological quantum computation is concerned with two-dimensional many body systems that support excitations. Anyons are elementary building block of quantum computations. When anyons tunneling in a double-layer system can transition to an exotic non-Abelian state and produce Fibonacci anyons, which are powerful enough for universal topological quantum computation (TQC).Here the exotic behavior of Fibonacci Superlattice is studied by using analytical transfer matrix methods and hence Fibonacci anyons. This Fibonacci anyons can build a quantum computer which is very emerging and exciting field today’s in Nanophotonics and quantum computation.Keywords: quantum computing, quasicrystals, Multiple Quantum wells (MQWs), transfer matrix method, fibonacci anyons, quantum hall effect, nanophotonics
Procedia PDF Downloads 378532 Symbolic Computation and Abundant Travelling Wave Solutions to Modified Burgers' Equation
Authors: Muhammad Younis
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In this article, the novel (G′/G)-expansion method is successfully applied to construct the abundant travelling wave solutions to the modified Burgers’ equation with the aid of computation. The method is reliable and useful, which gives more general exact travelling wave solutions than the existing methods. These obtained solutions are in the form of hyperbolic, trigonometric and rational functions including solitary, singular and periodic solutions which have many potential applications in physical science and engineering. Some of these solutions are new and some have already been constructed. Additionally, the constraint conditions, for the existence of the solutions are also listed.Keywords: traveling wave solutions, NLPDE, computation, integrability
Procedia PDF Downloads 426531 Offloading Knowledge-Keeping to Digital Technology and the Attrition of Socio-Cultural Life
Authors: Sophia Melanson Ricciardone
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Common vexations concerning the impact of contemporary media technology on our daily lives tend to conjure mental representations of digital specters that surreptitiously invade the privacy of our most intimate spaces. While legitimacy assuredly sustains these concerns, examining them in isolation from other attributable phenomena to the problems created by our hyper-mediated conditions does not supply a complete account of the deleterious cost of integrating digital affordances into the banal cadence of our shared socio-cultural realities. As we continue to subconsciously delegate facets of our social and cognitive lives to digital technology, the very faculties that have enabled our species to thrive and invent technology in the first place are at risk of attrition – namely our capacity to sustain attention while synthesizing information in working memory to produce creative and inventive constructions for our shared social existence. Though the offloading of knowledge-keeping to fellow social agents belonging to our family and community circles is an enduring intuitive phenomenon across human societies – what social psychologists refer to as transactive memory – in offloading our various socio-cognitive faculties to digital technology, we may plausibly be supplanting the visceral social connections forged by transactive memory. This paper will present related research and literature produced across the disciplines of sociobiology, socio-cultural anthropology, social psychology, cognitive semiotics and communication and media studies that directly and indirectly address the social precarity cultivated by digital technologies. This body of scholarly work will then be situated within common areas of interest belonging to digital anthropology, including the groundbreaking work of Pavel Curtis, Christopher Kelty, Lynn Cherny, Vincent Duclos, Nick Seaver, and Sherry Turkle. It is anticipated that in harmonizing these overlapping areas of intradisciplinary interest, this paper can weave together the disparate connections across spheres of knowledge that help delineate the conditions of our contemporary digital existence.Keywords: cognition, digital media, knowledge keeping, transactive memory
Procedia PDF Downloads 129530 Symbolic Computation on Variable-Coefficient Non-Linear Dispersive Wave Equations
Authors: Edris Rawashdeh, I. Abu-Falahah, H. M. Jaradat
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The variable-coefficient non-linear dispersive wave equation is investigated with the aid of symbolic computation. By virtue of a newly developed simplified bilinear method, multi-soliton solutions for such an equation have been derived. Effects of the inhomogeneities of media and nonuniformities of boundaries, depicted by the variable coefficients, on the soliton behavior are discussed with the aid of the characteristic curve method and graphical analysis.Keywords: dispersive wave equations, multiple soliton solution, Hirota Bilinear Method, symbolic computation
Procedia PDF Downloads 447529 Predicting of Hydrate Deposition in Loading and Offloading Flowlines of Marine CNG Systems
Authors: Esam I. Jassim
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The main aim of this paper is to demonstrate the prediction of the model capability of predicting the nucleation process, the growth rate, and the deposition potential of second phase particles in gas flowlines. The primary objective of the research is to predict the risk hazards involved in the marine transportation of compressed natural gas. However, the proposed model can be equally used for other applications including production and transportation of natural gas in any high-pressure flow-line. The proposed model employs the following three main components to approach the problem: computational fluid dynamics (CFD) technique is used to configure the flow field; the nucleation model is developed and incorporated in the simulation to predict the incipient hydrate particles size and growth rate; and the deposition of the gas/particle flow is proposed using the concept of the particle deposition velocity. These components are integrated in a comprehended model to locate the hydrate deposition in natural gas flowlines. The present research is prepared to foresee the deposition location of solid particles that could occur in a real application in Compressed Natural Gas loading and offloading. A pipeline with 120 m length and different sizes carried a natural gas is taken in the study. The location of particle deposition formed as a result of restriction is determined based on the procedure mentioned earlier and the effect of water content and downstream pressure is studied. The critical flow speed that prevents such particle to accumulate in the certain pipe length is also addressed.Keywords: hydrate deposition, compressed natural gas, marine transportation, oceanography
Procedia PDF Downloads 480528 Study of Suezmax Shuttle Tanker Energy Efficiency for Operations at the Brazilian Pre-Salt Region
Authors: Rodrigo A. Schiller, Rubens C. Da Silva, Kazuo Nishimoto, Claudio M. P. Sampaio
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The need to reduce fossil fuels consumption due to the current scenario of trying to restrain global warming effects and reduce air pollution is dictating a series of transformations in shipping. This study introduces, at first, the changes of the regulatory framework concerning gas emissions control and fuel consumption efficiency on merchant ships. Secondly, the main operational procedures with high potential reduction of fuel consumption are discussed, with focus on existing vessels, using ship speed reduction procedure. This procedure shows the positive impacts on both operating costs reduction and also on energy efficiency increase if correctly applied. Finally, a numerical analysis of the fuel consumption variation with the speed was carried out for a Suezmax class oil tanker, which has been adapted to oil offloading operations for FPSOs in Brazilian offshore oil production systems. In this analysis, the discussions about the variations of vessel energy efficiency from small speed rate reductions and the possible applications of this improvement, taking into account the typical operating profile of the vessel in such a way to have significant economic impacts on the operation. This analysis also evaluated the application of two different numerical methods: one based only on regression equations produced by existing data, semi-empirical method, and another using a CFD simulations for estimating the hull shape parameters that are most relevant for determining fuel consumption, analyzing inaccuracies and impact on the final results.Keywords: energy efficiency, offloading operations, speed reduction, Suezmax oil tanker
Procedia PDF Downloads 522527 Parallel Computation of the Covariance-Matrix
Authors: Claude Tadonki
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We address the issues related to the computation of the covariance matrix. This matrix is likely to be ill conditioned following its canonical expression, thus consequently raises serious numerical issues. The underlying linear system, which therefore should be solved by means of iterative approaches, becomes computationally challenging. A huge number of iterations is expected in order to reach an acceptable level of convergence, necessary to meet the required accuracy of the computation. In addition, this linear system needs to be solved at each iteration following the general form of the covariance matrix. Putting all together, its comes that we need to compute as fast as possible the associated matrix-vector product. This is our purpose in the work, where we consider and discuss skillful formulations of the problem, then propose a parallel implementation of the matrix-vector product involved. Numerical and performance oriented discussions are provided based on experimental evaluations.Keywords: covariance-matrix, multicore, numerical computing, parallel computing
Procedia PDF Downloads 307526 The Intersection/Union Region Computation for Drosophila Brain Images Using Encoding Schemes Based on Multi-Core CPUs
Authors: Ming-Yang Guo, Cheng-Xian Wu, Wei-Xiang Chen, Chun-Yuan Lin, Yen-Jen Lin, Ann-Shyn Chiang
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With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosophila Driver image, which can cover a set of Drosophila Driver/Neuron images. In order to solve this problem, the intersection/union region for a set of images should be computed at first, then a comparison work is used to calculate the similarities between the region and other images. In this paper, three encoding schemes, namely Integer, Boolean, Decimal, are proposed to encode each image as a one-dimensional structure. Then, the intersection/union region from these images can be computed by using the compare operations, Boolean operators and lookup table method. Finally, the comparison work is done as the union region computation, and the similarity score can be calculated by the definition of Tanimoto coefficient. The above methods for the region computation are also implemented in the multi-core CPUs environment with the OpenMP. From the experimental results, in the encoding phase, the performance by the Boolean scheme is the best than that by others; in the region computation phase, the performance by Decimal is the best when the number of images is large. The speedup ratio can achieve 12 based on 16 CPUs. This work was supported by the Ministry of Science and Technology under the grant MOST 106-2221-E-182-070.Keywords: Drosophila driver image, Drosophila neuron images, intersection/union computation, parallel processing, OpenMP
Procedia PDF Downloads 232525 An Improved Method to Compute Sparse Graphs for Traveling Salesman Problem
Authors: Y. Wang
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The Traveling salesman problem (TSP) is NP-hard in combinatorial optimization. The research shows the algorithms for TSP on the sparse graphs have the shorter computation time than those for TSP according to the complete graphs. We present an improved iterative algorithm to compute the sparse graphs for TSP by frequency graphs computed with frequency quadrilaterals. The iterative algorithm is enhanced by adjusting two parameters of the algorithm. The computation time of the algorithm is O(CNmaxn2) where C is the iterations, Nmax is the maximum number of frequency quadrilaterals containing each edge and n is the scale of TSP. The experimental results showed the computed sparse graphs generally have less than 5n edges for most of these Euclidean instances. Moreover, the maximum degree and minimum degree of the vertices in the sparse graphs do not have much difference. Thus, the computation time of the methods to resolve the TSP on these sparse graphs will be greatly reduced.Keywords: frequency quadrilateral, iterative algorithm, sparse graph, traveling salesman problem
Procedia PDF Downloads 226524 An Efficient Book Keeping Strategy for the Formation of the Design Matrix in Geodetic Network Adjustment
Authors: O. G. Omogunloye, J. B. Olaleye, O. E. Abiodun, J. O. Odumosu, O. G. Ajayi
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The focus of the study is to proffer easy formulation and computation of least square observation equation’s design matrix by using an efficient book keeping strategy. Usually, for a large network of many triangles and stations, a rigorous task is involved in the computation and placement of the values of the differentials of each observation with respect to its station coordinates (latitude and longitude), in their respective rows and columns. The efficient book keeping strategy seeks to eliminate or reduce this rigorous task involved, especially in large network, by simple skillful arrangement and development of a short program written in the Matlab environment, the formulation and computation of least square observation equation’s design matrix can be easily achieved.Keywords: design, differential, geodetic, matrix, network, station
Procedia PDF Downloads 348523 Aerodynamic Coefficients Prediction from Minimum Computation Combinations Using OpenVSP Software
Authors: Marine Segui, Ruxandra Mihaela Botez
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OpenVSP is an aerodynamic solver developed by National Aeronautics and Space Administration (NASA) that allows building a reliable model of an aircraft. This software performs an aerodynamic simulation according to the angle of attack of the aircraft makes between the incoming airstream, and its speed. A reliable aerodynamic model of the Cessna Citation X was designed but it required a lot of computation time. As a consequence, a prediction method was established that allowed predicting lift and drag coefficients for all Mach numbers and for all angles of attack, exclusively for stall conditions, from a computation of three angles of attack and only one Mach number. Aerodynamic coefficients given by the prediction method for a Cessna Citation X model were finally compared with aerodynamics coefficients obtained using a complete OpenVSP study.Keywords: aerodynamic, coefficient, cruise, improving, longitudinal, openVSP, solver, time
Procedia PDF Downloads 226522 Motion Estimator Architecture with Optimized Number of Processing Elements for High Efficiency Video Coding
Authors: Seongsoo Lee
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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization
Procedia PDF Downloads 356521 Parallel Evaluation of Sommerfeld Integrals for Multilayer Dyadic Green's Function
Authors: Duygu Kan, Mehmet Cayoren
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Sommerfeld-integrals (SIs) are commonly encountered in electromagnetics problems involving analysis of antennas and scatterers embedded in planar multilayered media. Generally speaking, the analytical solution of SIs is unavailable, and it is well known that numerical evaluation of SIs is very time consuming and computationally expensive due to the highly oscillating and slowly decaying nature of the integrands. Therefore, fast computation of SIs has a paramount importance. In this paper, a parallel code has been developed to speed up the computation of SI in the framework of calculation of dyadic Green’s function in multilayered media. OpenMP shared memory approach is used to parallelize the SI algorithm and resulted in significant time savings. Moreover accelerating the computation of dyadic Green’s function is discussed based on the parallel SI algorithm developed.Keywords: Sommerfeld-integrals, multilayer dyadic Green’s function, OpenMP, shared memory parallel programming
Procedia PDF Downloads 243520 Exploiting Non-Uniform Utility of Computing: A Case Study
Authors: Arnab Sarkar, Michael Huang, Chuang Ren, Jun Li
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The increasing importance of computing in modern society has brought substantial growth in the demand for more computational power. In some problem domains such as scientific simulations, available computational power still sets a limit on what can be practically explored in computation. For many types of code, there is non-uniformity in the utility of computation. That is not every piece of computation contributes equally to the quality of the result. If this non-uniformity is understood well and exploited effectively, we can much more effectively utilize available computing power. In this paper, we discuss a case study of exploring such non-uniformity in a particle-in-cell simulation platform. We find both the existence of significant non-uniformity and that it is generally straightforward to exploit it. We show the potential of order-of-magnitude effective performance gain while keeping the comparable quality of output. We also discuss some challenges in both the practical application of the idea and evaluation of its impact.Keywords: approximate computing, landau damping, non uniform utility computing, particle-in-cell
Procedia PDF Downloads 253519 A Parallel Computation Based on GPU Programming for a 3D Compressible Fluid Flow Simulation
Authors: Sugeng Rianto, P.W. Arinto Yudi, Soemarno Muhammad Nurhuda
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A computation of a 3D compressible fluid flow for virtual environment with haptic interaction can be a non-trivial issue. This is especially how to reach good performances and balancing between visualization, tactile feedback interaction, and computations. In this paper, we describe our approach of computation methods based on parallel programming on a GPU. The 3D fluid flow solvers have been developed for smoke dispersion simulation by using combinations of the cubic interpolated propagation (CIP) based fluid flow solvers and the advantages of the parallelism and programmability of the GPU. The fluid flow solver is generated in the GPU-CPU message passing scheme to get rapid development of haptic feedback modes for fluid dynamic data. A rapid solution in fluid flow solvers is developed by applying cubic interpolated propagation (CIP) fluid flow solvers. From this scheme, multiphase fluid flow equations can be solved simultaneously. To get more acceleration in the computation, the Navier-Stoke Equations (NSEs) is packed into channels of texel, where computation models are performed on pixels that can be considered to be a grid of cells. Therefore, despite of the complexity of the obstacle geometry, processing on multiple vertices and pixels can be done simultaneously in parallel. The data are also shared in global memory for CPU to control the haptic in providing kinaesthetic interaction and felling. The results show that GPU based parallel computation approaches provide effective simulation of compressible fluid flow model for real-time interaction in 3D computer graphic for PC platform. This report has shown the feasibility of a new approach of solving the compressible fluid flow equations on the GPU. The experimental tests proved that the compressible fluid flowing on various obstacles with haptic interactions on the few model obstacles can be effectively and efficiently simulated on the reasonable frame rate with a realistic visualization. These results confirm that good performances and balancing between visualization, tactile feedback interaction, and computations can be applied successfully.Keywords: CIP, compressible fluid, GPU programming, parallel computation, real-time visualisation
Procedia PDF Downloads 429518 A CORDIC Based Design Technique for Efficient Computation of DCT
Authors: Deboraj Muchahary, Amlan Deep Borah Abir J. Mondal, Alak Majumder
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A discrete cosine transform (DCT) is described and a technique to compute it using fast Fourier transform (FFT) is developed. In this work, DCT of a finite length sequence is obtained by incorporating CORDIC methodology in radix-2 FFT algorithm. The proposed methodology is simple to comprehend and maintains a regular structure, thereby reducing computational complexity. DCTs are used extensively in the area of digital processing for the purpose of pattern recognition. So the efficient computation of DCT maintaining a transparent design flow is highly solicited.Keywords: DCT, DFT, CORDIC, FFT
Procedia PDF Downloads 471517 Numerical Computation of Specific Absorption Rate and Induced Current for Workers Exposed to Static Magnetic Fields of MRI Scanners
Authors: Sherine Farrag
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Currently-used MRI scanners in Cairo City possess static magnetic field (SMF) that varies from 0.25 up to 3T. More than half of them possess SMF of 1.5T. The SMF of the magnet determine the diagnostic power of a scanner, but not worker's exposure profile. This research paper presents an approach for numerical computation of induced electric fields and SAR values by estimation of fringe static magnetic fields. Iso-gauss line of MR was mapped and a polynomial function of the 7th degree was generated and tested. Induced current field due to worker motion in the SMF and SAR values for organs and tissues have been calculated. Results illustrate that the computation tool used permits quick accurate MRI iso-gauss mapping and calculation of SAR values which can then be used for assessment of occupational exposure profile of MRI operators.Keywords: MRI occupational exposure, MRI safety, induced current density, specific absorption rate, static magnetic fields
Procedia PDF Downloads 422516 Computation of Natural Logarithm Using Abstract Chemical Reaction Networks
Authors: Iuliia Zarubiieva, Joyun Tseng, Vishwesh Kulkarni
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Recent researches has focused on nucleic acids as a substrate for designing biomolecular circuits for in situ monitoring and control. A common approach is to express them by a set of idealised abstract chemical reaction networks (ACRNs). Here, we present new results on how abstract chemical reactions, viz., catalysis, annihilation and degradation, can be used to implement circuit that accurately computes logarithm function using the method of Arithmetic-Geometric Mean (AGM), which has not been previously used in conjunction with ACRNs.Keywords: chemical reaction networks, ratio computation, stability, robustness
Procedia PDF Downloads 158515 Optoelectronic Hardware Architecture for Recurrent Learning Algorithm in Image Processing
Authors: Abdullah Bal, Sevdenur Bal
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This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware
Procedia PDF Downloads 502514 A New Paradigm to Make Cloud Computing Greener
Authors: Apurva Saxena, Sunita Gond
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Demand of computation, data storage in large amount are rapidly increases day by day. Cloud computing technology fulfill the demand of today’s computation but this will lead to high power consumption in cloud data centers. Initiative for Green IT try to reduce power consumption and its adverse environmental impacts. Paper also focus on various green computing techniques, proposed models and efficient way to make cloud greener.Keywords: virtualization, cloud computing, green computing, data center
Procedia PDF Downloads 545513 GPU Based Real-Time Floating Object Detection System
Authors: Jie Yang, Jian-Min Meng
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A GPU-based floating object detection scheme is presented in this paper which is designed for floating mine detection tasks. This system uses contrast and motion information to eliminate as many false positives as possible while avoiding false negatives. The GPU computation platform is deployed to allow detecting objects in real-time. From the experimental results, it is shown that with certain configuration, the GPU-based scheme can speed up the computation up to one thousand times compared to the CPU-based scheme.Keywords: object detection, GPU, motion estimation, parallel processing
Procedia PDF Downloads 466