• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.362-369
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• 1998

The computational environment in which engineers perform their designs has been rapidly evolved from coarse serial machines to massively parallel machines. Although the recent development of high-performance computers are available for a number of years, only limited successful applications of the new computational environments in computational structural engineering field has been reported due to its limited availability and large cost associated with high-performance computing. As a new computational model for high-performance engineering computing without cost and availability problems, parallel structural analysis models for large scale structures on a network of personal computers (PCs) are presented in this paper. In structural analysis solving routine for the linear system of equations is the most time consuming part. Thus, the focus is on the development of efficient preconditioned conjugate gradient (PCG) solvers on the proposed computational model. Two parallel PCG solvers, PPCG-I and PPCG-II, are developed and applied to analysis of large scale space truss structures.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.7
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• pp.775-787
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• 2010

Unlike general-purpose CPUs, the GPUs have been specialized as many-core streaming processors, and are frequently replacing the CPUs in an increasing range of computations thanks to their outstanding parallel computing capacity. In order to respond to such trend, NVIDIA has recently issued a new parallel computing architecture called CUDA(Compute Unified Device Architecture), offering a flexible GPU programming environment for GPGPU(General Purpose GPU) computing. In general, when programmers use the CUDA API, they should clearly understand many aspects of GPU's computing architecture to produce efficient parallel software. In this article, we explain several optimization techniques for CUDA programming that we have verified through a lot of experiment and trial and error, and review how those techniques affect the performance of code execution. In particular, we use a specific problem as an example to analyze several elements that affect performances, such as effective accesses to hierarchical memory system, processor occupancy, and latency hiding. In conclusion, we present several directions that may be utilized effectively in CUDA-based parallel programming.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.441-448
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• 2008

The molecular docking system needs a large amount of computation and requires super-computing power. Since the experiment requires a large amount of time, the experiment is conducted in the distributed environment or in the grid environment. Recently, researches on using parallel GPU of far higher performance than that of CPU in scientific computing have been very actively conducted. CUDA is an open technique by which a parallel GPU programming is made possible. This study proposes the molecular docking system using CUDA. It also proposes algorithm that parallels energy-minimizing-computation. To verify such experiments, this study conducted a comparative analysis on the time required for experimenting molecular docking in general CPU and the time and performance of the parallel GPU-based molecular docking which is proposed in this study.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1932-1940
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• 2000

We must solve problems caused by mobile computing environments for supporting efficient mobile computing services. The problem is the use of wireless medium having high error rates and low bandwidth, and the sudden network disconnection to reduce the power consumption of a mobile host and the cost of the network connection. For these problems, we proposed the architecture of the partial connection manager and designed and implemented that in this paper. In particular, The partial connection manager creates the limited number of mobile agents according to priority and sends them in parallel to server systems and combines results of them process rapidly the user request. By applying the proposed partial connection manager to the mobile computing services called cybermarket, we knew that the mobile agent technique could be suited to the mobile computing environment and overcome the partial connection problem caused by eh mobile computing environment.

• Journal of Digital Contents Society
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• v.14 no.1
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• pp.65-72
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• 2013

Current and future parallel computing model has been suggested for running and solving large-scale application problems such as climate, bio, cryptology, and astronomy, etc. Parallel computing is a form of computation in which many calculations are carried out simultaneously. And we are able to shorten the execution time of the program, as well as can extend the scale of the problem that can be solved. In this paper, we perform the actual cryptographic algorithms through parallel processing and evaluate its efficiency. Length of the key, which is stable criterion of cryptographic algorithm, judged according to the amount of complete enumeration computation. So we present a detailed procedure of DES key search cryptographic algorithms for executing of enumeration computation in parallel processing environment. And then, we did the simulation through applying to clustering system. As a result, we can measure the safety and solidity of cryptographic algorithm.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.58-71
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• 2002

Generally, multi-dimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amount of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel high-dimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-n$\times$mD(disk) architecture which is the hybrid type of nP-nD and lP-nD. Its node structure increases fan-out and reduces the height of a index tree. Also, A range search algorithm that maximizes I/O parallelism is devised, and it is applied to K-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.6
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• pp.325-334
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• 2016

Recently, Open Computing Language (OpenCL) has been proposed to provide a framework that supports heterogeneous computing platforms. By using an OpenCL framework, digital communication systems can support various protocols in a unified computing environment to achieve both high portability and high performance. This article introduces a parallel software decoder of Low Density Parity Check (LDPC) codes for China Multimedia Mobile Broadcasting (CMMB) on a heterogeneous platform. Each step of LDPC decoding has different parallelization characteristics. In this paper, steps suitable for task-level parallelization are executed on the CPU, and steps suitable for data-level parallelization are processed by the GPU. To improve the performance of the proposed OpenCL kernels for LDPC decoding operations, explicit thread scheduling, loop-unrolling, and effective data transfer techniques are applied. The proposed LDPC decoder achieves high performance by using heterogeneous multi-core processors on a unified computing framework.

• Journal of computational fluids engineering
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• v.11 no.2 s.33
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• pp.19-24
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• 2006

A research to evaluate the efficiency of design optimization was carried out for aerodynamic design optimization problem in distributed computing environment. The aerodynamic analyses which take most of computational work during design optimization were divided into several jobs and allocated to associated PC clients through network. This is not a parallel process based on domain decomposition in a single analysis rather than a simultaneous distributed-analyses using network-distributed computers. GBOM(gradient-based optimization method), SAO(Sequential Approximate Optimization) and RSM(Response Surface Method) were implemented to perform design optimization of transonic airfoils and evaluate their efficiencies. dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in the present distributed computing system. The SAO was found fairly suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the most efficient algorithm in the present distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model deteriorate its efficiency from the practical point of view.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.44-53
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• 2011

This study designed and implemented a web-based computing environment for geovisual analytics using HTML5 canvas. The computing environment supports visualization tools and user's interaction. The visualization tools are cluster map, animated map, temporal parallel coordinate plot, and temporal heat map chart. Users can explore the temporal changes of cluster using multiple view and brushing technique. The computing environment that works well across browsers is used in the computing environment with multiple devices.

• Structural Engineering and Mechanics
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• v.37 no.1
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• pp.17-37
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• 2011

This paper presents a new Internet-based computational framework for the realistic simulation of multi-scale response of structural systems. Two levels of parallel processing are involved in this frame work: multiple local distributed computing environments connected by the Internet to form a cluster-to-cluster distributed computing environment. To utilize such a computing environment for a realistic simulation, the simulation task of a structural system has been separated into a simulation of a simplified global model in association with several detailed component models using various scales. These related multi-scale simulation tasks are distributed amongst clusters and connected to form a multi-level hierarchy. The Internet is used to coordinate geographically distributed simulation tasks. This paper also presents the development of a software framework that can support the multi-level hierarchical simulation approach, in a cluster-to-cluster distributed computing environment. The architectural design of the program also allows the integration of several multi-scale models to be clients and servers under a single platform. Such integration can combine geographically distributed computing resources to produce realistic simulations of structural systems.