• 제목/요약/키워드: Local optimization method

검색결과 486건 처리시간 0.023초

FPGA 상에서 OpenCL을 이용한 병렬 문자열 매칭 구현과 최적화 방향 (Parallel String Matching and Optimization Using OpenCL on FPGA)

  • 윤진명;최강일;김현진
    • 전기학회논문지
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    • 제66권1호
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    • pp.100-106
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    • 2017
  • In this paper, we propose a parallel optimization method of Aho-Corasick (AC) algorithm and Parallel Failureless Aho-Corasick (PFAC) algorithm using Open Computing Language (OpenCL) on Field Programmable Gate Array (FPGA). The low throughput of string matching engine causes the performance degradation of network process. Recently, many researchers have studied the string matching engine using parallel computing. FPGA's vendors offer a parallel computing platform using OpenCL. In this paper, we apply the AC and PFAC algorithm on DE1-SoC board with Cyclone V FPGA, where the optimization that considers FPGA architecture is performed. Experiments are performed considering global id, local id, local memory, and loop unrolling optimizations using PFAC algorithm. The performance improvement using loop unrolling is 129 times greater than AC algorithm that not adopt loop unrolling. The performance improvements using loop unrolling are 1.1, 0.2, and 1.5 times greater than those using global id, local id, and local memory optimizations mentioned above.

콤플렉스 시스템의 신뢰도 최적화를 위한 발견적 합성해법의 개발 (A Hybrid-Heuristic for Reliability Optimization in Complex Systems)

  • 김재환
    • 해양환경안전학회지
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    • 제5권2호
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    • pp.87-97
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    • 1999
  • This study is concerned with developing a hybrid heuristic algorithm for solving the redundancy optimization problem which is very important in system safety, This study develops a HH(Hybrid Heuristic) method combined with two strategies to alleviate the risks of being trapped at a local optimum. One of them is to construct the populations of the initial solutions randomly. The other is the additional search with SA(Simulated Annealing) method in final step. Computational results indicate that HH performs consistently better than the KY method proposed in Kim[8]. Therefore, the proposed HH is believed to an attractive to other heuristic methods.

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집적회로의 새로운 계층적 배치 기법 (A New Method for Hierarchical Placement of Integrated Circuits)

  • 김청희;신현철
    • 전자공학회논문지A
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    • 제30A권6호
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    • pp.58-65
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    • 1993
  • In this research, we developed a new algorithm for hierarchical placement of integrated circuits. For efficient placement of a large circuit, the given circuit is recursively partitioned to form a hierarchy tree and then simulated-annealing-based placement method is applied at each level of the hierarchy to find a near optimum solution. During the placemtnt, global optimization is performed at high levels of the hierarchy and local optimization is performed at low levels. When compared with conventional placement methods, the new hierarchical placement method produced favorable results.

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Controller Optimization for Bidirectional Power Flow in Medium-Voltage DC Power Systems

  • Chung, Il-Yop;Liu, Wenxin;Cartes, David A.;Cho, Soo-Hwan;Kang, Hyun-Koo
    • Journal of Electrical Engineering and Technology
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    • 제6권6호
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    • pp.750-759
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    • 2011
  • This paper focuses on the control of bidirectional power flow in the electric shipboard power systems, especially in the Medium-Voltage Direct Current (MVDC) shipboard power system. Bidirectional power control between the main MVDC bus and the local zones can improve the energy efficiency and control flexibility of electric ship systems. However, since the MVDC system contains various nonlinear loads such as pulsed power load and radar in various subsystems, the voltage of the MVDC and the local zones varies significantly. This voltage variation affects the control performance of the bidirectional DC-DC converters as exogenous disturbances. To improve the control performance regardless of uncertainties and disturbances, this paper proposes a novel controller design method of the bidirectional DC-DC converters using $L_1$ control theory and intelligent optimization algorithm. The performance of the proposed method is verified via large-scale real-time digital simulation of a notional shipboard MVDC power system.

병렬의 동일기계에서 처리되는 순서의존적인 작업들의 스케쥴링을 위한 유전알고리즘 (A Genetic Algorithm for Scheduling Sequence-Dependant Jobs on Parallel Identical Machines)

  • 이문규;이승주
    • 대한산업공학회지
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    • 제25권3호
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    • pp.360-368
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    • 1999
  • We consider the problem of scheduling n jobs with sequence-dependent processing times on a set of parallel-identical machines. The processing time of each job consists of a pure processing time and a sequence-dependent setup time. The objective is to maximize the total remaining machine available time which can be used for other tasks. For the problem, a hybrid genetic algorithm is proposed. The algorithm combines a genetic algorithm for global search and a heuristic for local optimization to improve the speed of evolution convergence. The genetic operators are developed such that parallel machines can be handled in an efficient and effective way. For local optimization, the adjacent pairwise interchange method is used. The proposed hybrid genetic algorithm is compared with two heuristics, the nearest setup time method and the maximum penalty method. Computational results for a series of randomly generated problems demonstrate that the proposed algorithm outperforms the two heuristics.

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시간대 제약이 있는 차량경로 결정문제를 위한 2단계 해법의 개발 (A Two-phase Method for the Vehicle Routing Problems with Time Windows)

  • 홍성철;박양병
    • 산업공학
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    • 제17권spc호
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    • pp.103-110
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    • 2004
  • This paper presents a two-phase method for the vehicle routing problems with time windows(VRPTW). In a supply chain management(SCM) environment, timely distribution is very important problem faced by most industries. The VRPTW is associated with SCM for each customer to be constrained the time of service. In the VRPTW, the objective is to design the least total travel time routes for a fleet of identical capacitated vehicles to service geographically scattered customers with pre-specified service time windows. The proposed approach is based on ant colony optimization(ACO) and improvement heuristic. In the first phase, an insertion based ACO is introduced for the route construction and its solutions is improved by an iterative random local search in the second phase. Experimental results show that the proposed two-phase method obtains very good solutions with respect to total travel time minimization.

Optimization of 3G Mobile Network Design Using a Hybrid Search Strategy

  • Wu Yufei;Pierre Samuel
    • Journal of Communications and Networks
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    • 제7권4호
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    • pp.471-477
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    • 2005
  • This paper proposes an efficient constraint-based optimization model for the design of 3G mobile networks, such as universal mobile telecommunications system (UMTS). The model concerns about finding a set of sites for locating radio network controllers (RNCs) from a set of pre-defined candidate sites, and at the same time optimally assigning node Bs to the selected RNCs. All these choices must satisfy a set of constraints and optimize an objective function. This problem is NP-hard and consequently cannot be practically solved by exact methods for real size networks. Thus, this paper proposes a hybrid search strategy for tackling this complex and combinatorial optimization problem. The proposed hybrid search strategy is composed of three phases: A constraint satisfaction method with an embedded problem-specific goal which guides the search for a good initial solution, an optimization phase using local search algorithms, such as tabu algorithm, and a post­optimization phase to improve solutions from the second phase by using a constraint optimization procedure. Computational results show that the proposed search strategy and the model are highly efficient. Optimal solutions are always obtained for small or medium sized problems. For large sized problems, the final results are on average within $5.77\%$ to $7.48\%$ of the lower bounds.

함수 근사화를 위한 방사 기저함수 네트워크의 전역 최적화 기법 (A Global Optimization Method of Radial Basis Function Networks for Function Approximation)

  • 이종석;박철훈
    • 정보처리학회논문지B
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    • 제14B권5호
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    • pp.377-382
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    • 2007
  • 본 논문에서는 방사 기저함수 네트워크의 파라미터를 전 영역에서 최적화하는 학습 알고리즘을 제안한다. 기존의 학습 알고리즘들은 지역 최적화만을 수행하기 때문에 성능의 한계가 있고 최종 결과가 초기 네트워크 파라미터 값에 크게 의존하는 단점이 있다. 본 논문에서 제안하는 하이브리드 모의 담금질 기법은 모의 담금질 기법의 전 영역 탐색 능력과 경사 기반 학습 알고리즘의 지역 최적화 능력을 조합하여 전 파라미터 영역에서 해를 찾을 수 있도록 한다. 제안하는 기법을 함수 근사화 문제에 적용하여 기존의 학습 알고리즘에 비해 더 좋은 학습 및 일반화 성능을 보이는 네트워크 파라미터를 찾을 수 있으며, 초기 파라미터 값의 영향을 크게 줄일 수 있음을 보인다.

설계민감도 해석에서 역전파 방법을 사용한 응력제한조건 위상최적설계 (Stress Constraint Topology Optimization using Backpropagation Method in Design Sensitivity Analysis)

  • 김민근;김석찬;김재승;이재경;이근호
    • 한국전산구조공학회논문집
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    • 제35권6호
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    • pp.367-374
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    • 2022
  • 본 논문에서는 역전파 방법 기반 자동미분법을 이용하여 설계민감도를 구하고 이를 응력제한조건을 고려한 위상최적설계에 적용하였다. 응력제한조건이 있는 위상최적화문제는 특이점(singularity)과 응력의 국부성(local nature of stress constraint)문제, 그리고 설계 변수에 대한 비선형성의 문제를 포함하고 최적해를 얻기가 매우 힘들다. 특이점 문제를 해결하기 위해서 응력 완화(stress relaxation) 기법을 사용하였고, 응력의 국부성을 해결하기 위해 p-norm을 이용한 전역 응력치를 제한조건에 사용하였다. 설계 변수에 대한 비선 형성을 극복하기 위해 해석적인 방법으로 정확한 설계민감도를 구하는 것이 중요하다. 위상최적설계에서 기존에는 보조변수방법 (adjoint variable method)을 사용하여 빠르고 정확한 설계민감도를 구했지만, 설계민감도를 해석적으로 구해야 하고, 보조평형방정식을 추가로 풀어야 하는 어려움이 있다. 이를 해결하기 위해서 인공신경망에서 최적 가중치(weights)와 편차(biases)를 구할 때 쓰이는 역전파 기법을 이용하여 설계민감도를 구하고 이를 응력제한조건을 고려한 위상최적설계에 적용하였다. 역전파 기법은 자동미분에 쓰이는 기법으로 목적함수나 제한조건에 대한 설계민감도를 별도의 수식유도 없이 간단하게 구할 수 있는 장점이 있다. 또한, 미분값을 구하는 역전파의 과정이 보조평형방정식을 푸는 것보다 계산시간이 빠르고 해석적 방법으로 구한 설계민감도와 같은 정확도를 보여준다.