• 제목/요약/키워드: Processing Optimization

검색결과 1,584건 처리시간 0.031초

아날로그 셀룰라 병렬 처리 회로망(CPPN)을 이용한 Pattern Classification (Pattern Classification with the Analog Cellular Parallel Processing Networks)

  • 오태완;이혜정;김형석
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.2367-2370
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    • 2003
  • A fast pattern classification algorithm with Cellular Parallel Processing Network-based dynamic programming is proposed. The Cellular Parallel Processing Networks is an analog parallel processing architecture and the dynamic programming is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast Pattern classification with optimization is formed. On such CPPN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

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A Genetic Approach for Joint Link Scheduling and Power Control in SIC-enable Wireless Networks

  • Wang, Xiaodong;Shen, Hu;Lv, Shaohe;Zhou, Xingming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권4호
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    • pp.1679-1691
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    • 2016
  • Successive interference cancellation (SIC) is an effective means of multi-packet reception to combat interference at the physical layer. We investigate the joint optimization issue of channel access and power control for capacity maximization in SIC-enabled wireless networks. We propose a new interference model to characterize the sequential detection nature of SIC. Afterward, we formulize the joint optimization problem, prove it to be a nondeterministic polynomial-time-hard problem, and propose a novel approximation approach based on the genetic algorithm (GA). Finally, we discuss the design and parameter setting of the GA approach and validate its performance through extensive simulations.

Code Generation and Optimization for the Flow-based Network Processor based on LLVM

  • Lee, SangHee;Lee, Hokyoon;Kim, Seon Wook;Heo, Hwanjo;Park, Jongdae
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2012년도 추계학술발표대회
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    • pp.42-45
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    • 2012
  • A network processor (NP) is an application-specific instruction-set processor for fast and efficient packet processing. There are many issues in compiler's code generation and optimization due to NP's hardware constraints and special hardware support. In this paper, we describe in detail how to resolve the issues. Our compiler was developed on LLVM 3.0 and the NP target was our in-house network processor which consists of 32 64-bit RISC processors and supports multi-context with special hardware structures. Our compiler incurs only 9.36% code size overhead over hand-written code while satisfying QoS, and the generated code was tested on a real packet processing hardware, called S20 for code verification and performance evaluation.

Performance Optimization of Big Data Center Processing System - Big Data Analysis Algorithm Based on Location Awareness

  • Zhao, Wen-Xuan;Min, Byung-Won
    • International Journal of Contents
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    • 제17권3호
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    • pp.74-83
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    • 2021
  • A location-aware algorithm is proposed in this study to optimize the system performance of distributed systems for processing big data with low data reliability and application performance. Compared with previous algorithms, the location-aware data block placement algorithm uses data block placement and node data recovery strategies to improve data application performance and reliability. Simulation and actual cluster tests showed that the location-aware placement algorithm proposed in this study could greatly improve data reliability and shorten the application processing time of I/O interfaces in real-time.

은닉 마르코프 모델의 확률적 최적화를 통한 자동 독순의 성능 향상 (Improved Automatic Lipreading by Stochastic Optimization of Hidden Markov Models)

  • 이종석;박철훈
    • 정보처리학회논문지B
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    • 제14B권7호
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    • pp.523-530
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    • 2007
  • 본 논문에서는 자동 독순(automatic lipreading)의 인식기로 쓰이는 은닉 마르코프 모델(HMM: hidden Markov model)의 새로운 확률적 최적화 기법을 제안한다. 제안하는 기법은 전역 최적화가 가능한 확률적 기법인 모의 담금질과 지역 최적화 기법을 결합하는 것으로써, 알고리즘의 빠른 수렴과 좋은 해로의 수렴을 가능하게 한다. 제안하는 알고리즘이 전역 최적해로 수렴함을 수학적으로 보인다. 제안하는 기법을 통해 HMM을 학습함으로써 기존의 알고리즘이 지역해만을 찾는 단점을 개선함으로써 향상된 독순 성능을 나타냄을 실험으로 보인다.

Optimization of Etching Profile in Deep-Reactive-Ion Etching for MEMS Processes of Sensors

  • Yang, Chung Mo;Kim, Hee Yeoun;Park, Jae Hong
    • 센서학회지
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    • 제24권1호
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    • pp.10-14
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    • 2015
  • This paper reports the results of a study on the optimization of the etching profile, which is an important factor in deep-reactive-ion etching (DRIE), i.e., dry etching. Dry etching is the key processing step necessary for the development of the Internet of Things (IoT) and various microelectromechanical sensors (MEMS). Large-area etching (open area > 20%) under a high-frequency (HF) condition with nonoptimized processing parameters results in damage to the etched sidewall. Therefore, in this study, optimization was performed under a low-frequency (LF) condition. The HF method, which is typically used for through-silicon via (TSV) technology, applies a high etch rate and cannot be easily adapted to processes sensitive to sidewall damage. The optimal etching profile was determined by controlling various parameters for the DRIE of a large Si wafer area (open area > 20%). The optimal processing condition was derived after establishing the correlations of etch rate, uniformity, and sidewall damage on a 6-in Si wafer to the parameters of coil power, run pressure, platen power for passivation etching, and $SF_6$ gas flow rate. The processing-parameter-dependent results of the experiments performed for optimization of the etching profile in terms of etch rate, uniformity, and sidewall damage in the case of large Si area etching can be summarized as follows. When LF is applied, the platen power, coil power, and $SF_6$ should be low, whereas the run pressure has little effect on the etching performance. Under the optimal LF condition of 380 Hz, the platen power, coil power, and $SF_6$ were set at 115W, 3500W, and 700 sccm, respectively. In addition, the aforementioned standard recipe was applied as follows: run pressure of 4 Pa, $C_4F_8$ content of 400 sccm, and a gas exchange interval of $SF_6/C_4F_8=2s/3s$.

임베디드 모듈 기반 지능형 영상감시 시스템의 최적화에 관한 연구 (A Study on Optimization of Intelligent Video Surveillance System based on Embedded Module)

  • 김진수;김민구;반성범
    • 스마트미디어저널
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    • 제7권2호
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    • pp.40-46
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    • 2018
  • 기존 사건 사고를 예방하기 위한 감시 시스템은 한 사람이 여러 대의 CCTV를 감시할 경우 22분 후에는 95%를 발견하지 못하는 문제점이 있다. 이를 해결하기 위해 비정상적인 상황이 발생할 경우 알림을 주는 컴퓨터 기반 지능형 영상감시 시스템에 대한 연구가 이루어지고 있지만, 소비전력 및 비용 등의 단점이 있어 실제 환경에서 활용하기에는 어려움이 있다. 이에 대한 대책으로 소형 디바이스 기반 지능형 영상감시 시스템에 대한 연구가 진행되고 있다. 본 논문에서는 침입자 검출, 화재 검출, 배회 낙상 검출을 수행하는 임베디드 모듈 기반 지능형 영상감시 시스템을 구현한다. 또한, 실시간 처리를 위해 알고리즘 및 임베디드 모듈 최적화 방법을 적용한다. 임베디드 모듈 기반 지능형 영상감시 시스템을 라즈베리파이에 구현하였으며, 알고리즘 처리 시간은 최적화 전 라즈베리파이 0.95초, 최적화 후 라즈베리파이 0.47초로 최적화 전 후 비교 결과 50.52% 처리 시간이 감소되었다. 따라서, 임베디드 모듈 기반 지능형 영상감시 시스템의 실시간 구동 가능성을 확인하였다.

QoS Constrained Optimization of Cell Association and Resource Allocation for Load Balancing in Downlink Heterogeneous Cellular Networks

  • Su, Gongchao;Chen, Bin;Lin, Xiaohui;Wang, Hui;Li, Lemin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권5호
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    • pp.1569-1586
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    • 2015
  • This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l1-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.

Hyperion 영상의 제약선형분광혼합분석 기반 무감독 Endmember 추출 최적화 기법 (Unsupervised Endmember Selection Optimization Process based on Constrained Linear Spectral Unmixing of Hyperion Image)

  • 최재완;김용일;유기윤
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2006년도 춘계학술발표회 논문집
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    • pp.211-216
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    • 2006
  • The Constrained Linear Spectral Unmixing(CLSU) is investigated for sub-pixel image processing, Its result is the abundance map which mean fractions of endmember existing in a mixed pixel. Compared to the Linear Spectral Unmixing using least square method, CLSU uses the NNLS (Non-Negative Least Square) algorithm to guarantee that the estimated fractions are constrained. But, CLSU gets Into difficulty in image processing due to select endmember at a user's disposition. In this study, endmember selection optimization method using entropy in the error-image analysis is proposed. In experiments which is used hyperion image, it is shown that our method can select endmember number than CLSU based on unsupervised endemeber selection.

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GPU의 병렬 처리 기능을 이용한 PSO(Particle Swarm Optimization) 알고리듬 구현 (Implementation of PSO(Particle Swarm Optimization) Algorithm using Parallel Processing of GPU)

  • 김은수;김조환;김종욱
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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    • pp.181-182
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    • 2008
  • 본 논문에서는 연산 최적화 알고리듬 중 PSO(Particle Swarm Optimization) 알고리듬을 NVIDIA사(社)에서 제공한 CUDA(Compute Unified Device Architecture)를 이용하여 새롭게 구현하였다. CUDA는 CPU가 아닌 GPU(Graphic Processing Unit)의 다양한 병렬 처리 능력을 사용해 복잡한 컴퓨팅 문제를 해결하는 소프트웨어 개발을 가능케 하는 기술이다. 이 기술을 연산 최적화 알고리듬 중 PSO에 적용함으로써 알고리듬의 수행 속도를 개선하였다. CUDA를 적용한 PSO 알고리듬의 검증을 위해 언어 기반으로 프로그래밍하고 다양한 Test Function을 통해 시뮬레이션 하였다. 그리고 기존의 PSO 알고리듬과 비교 분석하였다. 또한 알고리듬의 성능 향상으로 여러 가지 최적화 분야에 적용 할 수 있음을 보인다.

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