• Title/Summary/Keyword: Parallel computing model

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High-resolution Urban Flood Modeling using Cellular Automata-based WCA2D in the Oncheon-cheon Catchment in Busan, South Korea (셀룰러 오토마타 기반 WCA2D 모형을 이용한 부산 온천천 유역 고해상도 도시 침수 해석)

  • Choi, Hyeonjin;Lee, Songhee;Woo, Hyuna;Noh, Seong Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.5
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    • pp.587-599
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    • 2023
  • As climate change increasesthe frequency and risk of flooding in major cities around theworld, the importance ofsimulation technology that can quickly and accurately analyze high-resolution 2D flooding information in large-scale areasis emerging. The physically-based approaches based on the Shallow Water Equations (SWE) often requires huge computer resources hindering high-resolution flood prediction. This study investigated the theoretical background of Weighted Cellular Automata 2D (WCA2D), which simulates spatio-temporal changes offlooding using transition rules and weight-based system, and assessed feasibility to simulate pluvial flooding in the urbancatchment, theOncheon-cheon catchmentinBusan, SouthKorea.Inaddition,the computation performancewas compared by applying versions using OpenComputing Language (OpenCL) andOpenMulti-Processing (OpenMP) parallel computing techniques. Simulationresultsshowed that the maximuminundation depthmap by theWCA2Dmodel cansimilarly reproduce historical inundation maps. Also, it can precisely simulate spatio-temporal changes of flooding extent in the urban catchment with complex topographic characteristics. For computation efficiency, parallel computing schemes, theOpenCLandOpenMP, improved the computation by about 8~14 and 5~6 folds respectively, compared to the sequential computation.

Scalable Prediction Models for Airbnb Listing in Spark Big Data Cluster using GPU-accelerated RAPIDS

  • Muralidharan, Samyuktha;Yadav, Savita;Huh, Jungwoo;Lee, Sanghoon;Woo, Jongwook
    • Journal of information and communication convergence engineering
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    • v.20 no.2
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    • pp.96-102
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    • 2022
  • We aim to build predictive models for Airbnb's prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.

A framework for parallel processing in multiblock flow computations (다중블록 유동해석에서 병렬처리를 위한 시스템의 구조)

  • Park, Sang-Geun;Lee, Geon-U
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.21 no.8
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    • pp.1024-1033
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    • 1997
  • The past several years have witnessed an ever-increasing acceptance and adoption of parallel processing, both for high performance scientific computing as well as for more general purpose applications. Furthermore with increasing needs to perform the complex flow calculations in an efficient manner, the use of the message passing model on distributed networks has emerged as an important alternative to the expensive supercomputers. This work attempts to provide a generic framework to enable the parallelization of all CFD-related works using the master-slave model. This framework consists of (1) input geometry, (2) domain decomposition, (3) grid generation, (4) flow computations, (5) flow visualization, and (6) output display as the sequential components, but performs computations for (2) to (5) in parallel on the workstation clustering. The flow computations are parallized by having multiple copies of the flow-code to solve a PDE on different spatial regions on different processors, while their flow data are exchanged across the region boundaries, and the solution is time-stepped. The Parallel Virtual Machine (PVM) is used for distributed communication in this work.

Parallel Finite Element Simulation of the Incompressible Navier-stokes Equations (병렬 유한요소 해석기법을 이용한 유동장 해석)

  • Choi H. G.;Kim B. J.;Kang S. W.;Yoo J. Y.
    • 한국전산유체공학회:학술대회논문집
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    • 2002.05a
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    • pp.8-15
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    • 2002
  • For the large scale computation of turbulent flows around an arbitrarily shaped body, a parallel LES (large eddy simulation) code has been recently developed in which domain decomposition method is adopted. METIS and MPI (message Passing interface) libraries are used for domain partitioning and data communication between processors, respectively. For unsteady computation of the incompressible Wavier-Stokes equation, 4-step splitting finite element algorithm [1] is adopted and Smagorinsky or dynamic LES model can be chosen fur the modeling of small eddies in turbulent flows. For the validation and performance-estimation of the parallel code, a three-dimensional laminar flow generated by natural convection inside a cube has been solved. Then, we have solved the turbulent flow around MIRA (Motor Industry Research Association) model at $Re = 2.6\times10^6$, which is based on the model height and inlet free stream velocity, using 32 processors on IBM SMP cluster and compared with the existing experiment.

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Speedup Analysis Model for High Speed Network based Distributed Parallel Systems (고속 네트웍 기반의 분산병렬시스템에서의 성능 향상 분석 모델)

  • 김화성
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.12C
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    • pp.218-224
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    • 2001
  • The objective of Distributed Parallel Computing is to solve the computationally intensive problems, which have several types of parallelism, on a suite of high performance and parallel machines in a manner that best utilizes the capabilities of each machine. In this paper, we propose a computational model including the generalized graph representation method of distributed parallel systems for speedup analysis, and analyze how the super-linear speedup is achieved when scheduling of programs with diverse embedded parallelism modes onto a distributed heterogeneous supercomputing network environment. The proposed representation method can also be applied to simple homogeneous or heterogeneous systems whose components are heterogeneous only in terms of the processor speed. In order to obtain the core speedup, the matching of the parallelism characteristics between tasks and parallel machines should be carefully handled while minimizing the communication overhead.

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Dynamic Available-Resource Reallocation based Job Scheduling Model in Grid Computing (그리드 컴퓨팅에서 유효자원 동적 재배치 기반 작업 스케줄링 모델)

  • Kim, Jae-Kwon;Lee, Jong-Sik
    • Journal of the Korea Society for Simulation
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    • v.21 no.2
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    • pp.59-67
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    • 2012
  • A grid computing consists of the physical resources for processing one of the large-scale jobs. However, due to the recent trends of rapid growing data, the grid computing needs a parallel processing method to process the job. In general, each physical resource divides a requested large-scale task. And a processing time of the task varies with an efficiency and a distance of each resource. Even if some resource completes a job, the resource is standing by until every divided job is finished. When every resource finishes a processing, each resource starts a next job. Therefore, this paper proposes a dynamic resource reallocation scheduling model (DDRSM). DDRSM finds a waiting resource and reallocates an unfinished job with an efficiency and a distance of the resource. DDRSM is an efficient method for processing multiple large-scale jobs.

Tree-dimensional FE Analysis of Acoustic Emission of Fiber Breakage using Explicit Time Integration Method (외연적 시간적분법을 이용한 복합재료 섬유 파단 시 음향방출의 3차원 유한요소 해석)

  • Paik, Seung-Hoon;Park, Si-Hyong;Kim, Seung-Jo
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2005.04a
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    • pp.172-175
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    • 2005
  • The numerical simulation is performed for the acoustic emission and the wave propagation due to fiber breakage in single fiber composite plates by the finite element transient analysis. The acoustic emission and the following wave motions from a fiber breakage under a static loading is simulated to investigate the applicability of the explicit finite element method and the equivalent volume force model as a simulation tool of wave propagation and a modeling technique of an acoustic emission. For such a simple case of the damage event under static loading, various parameters affecting the wave motion are investigated for reliable simulations of the impact damage event. The high velocity and the small wave length of the acoustic emission require a refined analysis with dense distribution of the finite element and a small time step. In order to fulfill the requirement for capturing the exact wave propagation and to cover the 3-D simulation, we utilize the parallel FE transient analysis code and the parallel computing technology.

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Crack Identification Using Evolutionary Algorithms in Parallel Computing Environment (병렬 환경하의 진화 이론을 이용한 결함인식)

  • Sim, Mun-Bo;Seo, Myeong-Won
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.9
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    • pp.1806-1813
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    • 2002
  • It is well known that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a classical optimization technique was adopted by previous researchers. That technique overcame the difficulty of finding the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However, it is hard to select a trial solution initially for optimization because the defined objective function is heavily multimodal. A method is presented in this paper, which uses continuous evolutionary algorithms(CEAs). CEAs are effective for solving inverse problems and implemented on PC clusters to shorten calculation time. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising with high parallel efficiency over about 94%.

A Parallel Pipeline Execution Algorithm for H.264/AVC Intra Prediction (H.264/AVC의 인트라 예측 병렬 파이프라인 실행 알고리즘)

  • Xu, Jia-Yue;Cho, Hyo-Moon;Cho, Sang-Bock
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.5
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    • pp.79-86
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    • 2008
  • H.264/AVC is the newest international video coding standard developed by the joint ITU-T and ISO/IEC standards organizations. This newest video coding standard offers much higher coding efficiency than the H.261, H.263 and MPEG-4. But it has high computing complexity and high H/W resources wasting problem. This paper described the two unit parallel pipeline structure. This new structure comparing with standard model decreased the computing complexity of 67% and the H/W resources waste of 3%.