• Title/Summary/Keyword: Parallel Computer

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An Enhanced Instantaneous Circulating Current Control for Reactive Power and Harmonic Load Sharing in Islanded Microgrids

  • Lorzadeh, Iman;Abyaneh, Hossein Askarian;Savaghebi, Mehdi;Lorzadeh, Omid;Bakhshai, Alireza;Guerrero, Josep M.
    • Journal of Power Electronics
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    • v.17 no.6
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    • pp.1658-1671
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    • 2017
  • To address the inaccurate load demand sharing problems among parallel inverter-interfaced voltage-controlled distributed generation (DG) units in islanded microgrids (MGs) with different DG power ratings and mismatched feeder impedances, an enhanced voltage control scheme based on the active compensation of circulating voltage drops is proposed in this paper. Using the proposed strategy, reactive power and harmonic currents are shared accurately and proportionally without knowledge of the feeder impedances. Since the proposed local controller consists of two well-separated fundamental and harmonic voltage control branches, the reactive power and harmonic currents can be independently shared without having a remarkable effect on the amplitude or quality of the DGs voltage, even if nonlinear (harmonic) loads are directly connected at the output terminals of the units. In addition, accurate load sharing can also be attained when the plug-and-play performance of DGs and various loading conditions are applied to MGs. The effects of communication failures and latency on the performance of the proposed strategy are also explored. The design process of the proposed control system is presented in detail and comprehensive simulation studies on a three-phase MG are provided to validate the effectiveness of the proposed control method.

All-port Broadcasting Algorithms on Wormhole Routed Star Graph Networks (웜홀 라우팅을 지원하는 스타그래프 네트워크에서 전 포트 브로드캐스팅 알고리즘)

  • Kim, Cha-Young;Lee, Sang-Kyu;Lee, Ju-Young
    • Journal of KIISE:Computer Systems and Theory
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    • v.29 no.2
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    • pp.65-74
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    • 2002
  • Recently star networks are considered as attractive alternatives to the widely used hypercube for interconnection networks in parallel processing systems by many researchers. One of the fundamental communication problems on star graph networks is broadcasing In this paper we consider the broadcasting problems in star graph networks using wormhole routing. In wormhole routed system minimizing link contention is more critical for the system performance than the distance between two communicating nodes. We use Hamiltonian paths in star graph to set up link-disjoint communication paths We present a broadcast algorithm in n-dimensional star graph of N(=n!) nodes such that the total completion time is no larger than $([long_n n!]+1)$ steps where $([long_n n!]+1)$ is the lower bound This result is significant improvement over the previous n-1 step broadcasting algorithm.

Deep Learning-based Real-Time Super-Resolution Architecture Design (경량화된 딥러닝 구조를 이용한 실시간 초고해상도 영상 생성 기술)

  • Ahn, Saehyun;Kang, Suk-Ju
    • Journal of Broadcast Engineering
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    • v.26 no.2
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    • pp.167-174
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    • 2021
  • Recently, deep learning technology is widely used in various computer vision applications, such as object recognition, classification, and image generation. In particular, the deep learning-based super-resolution has been gaining significant performance improvement. Fast super-resolution convolutional neural network (FSRCNN) is a well-known model as a deep learning-based super-resolution algorithm that output image is generated by a deconvolutional layer. In this paper, we propose an FPGA-based convolutional neural networks accelerator that considers parallel computing efficiency. In addition, the proposed method proposes Optimal-FSRCNN, which is modified the structure of FSRCNN. The number of multipliers is compressed by 3.47 times compared to FSRCNN. Moreover, PSNR has similar performance to FSRCNN. We developed a real-time image processing technology that implements on FPGA.

Implementation of Neural Network Accelerator for Rendering Noise Reduction on OpenCL (OpenCL을 이용한 랜더링 노이즈 제거를 위한 뉴럴 네트워크 가속기 구현)

  • Nam, Kihun
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.4
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    • pp.373-377
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    • 2018
  • In this paper, we propose an implementation of a neural network accelerator for reducing the rendering noise using OpenCL. Among the rendering algorithms, we selects a ray tracing to assure a high quality graphics. Ray tracing rendering uses ray to render, less use of the ray will result in noise. Ray used more will produce a higher quality image but will take operation time longer. To reduce operation time whiles using fewer rays, Learning Base Filtering algorithm using neural network was applied. it's not always produce optimize result. In this paper, a new approach to Matrix Multiplication that is based on General Matrix Multiplication for improved performance. The development environment, we used specialized in high speed parallel processing of OpenCL. The proposed architecture was verified using Kintex UltraScale XKU6909T-2FDFG1157C FPGA board. The time it takes to calculate the parameters is about 1.12 times fast than that of Verilog-HDL structure.

Performance Analysis of Distributed Hadoop Systems (분산 하둡 시스템의 성능 비교 분석)

  • Bae, Byoung-Jin;Kim, Young-Joo;Kim, Young-Kuk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.479-482
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    • 2014
  • Nowadays open-source hadoop systems have been using widely to efficiently manage a fast-growing big data. Hadoop systems consist of distributed file processing system called HDFS (Hadoop Distributed File System) and distributed parallel processing system called MapReduce. The MapReduce reads and processes big data from HDFS and then processed results are written in HDFS again by the MapReduce. Such a processing method has different system structure respectively according to hadoop version. Therefore, this paper shows analysis results for performance of hadoop systems. For this, we devise a way which monitors hadoop systems and measure occurrence frequency of processes, threads, and variables generated in hadoop system itself using the devised way. So, by using the measured results as analysis indicator, we help the indicator predict inner performance of hadoop systems.

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Big Data-based Sensor Data Processing and Analysis for IoT Environment (IoT 환경을 위한 빅데이터 기반 센서 데이터 처리 및 분석)

  • Shin, Dong-Jin;Park, Ji-Hun;Kim, Ju-Ho;Kwak, Kwang-Jin;Park, Jeong-Min;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.117-126
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    • 2019
  • The data generated in the IoT environment is very diverse. Especially, the development of the fourth industrial revolution has made it possible to increase the number of fixed and unstructured data generated in manufacturing facilities such as Smart Factory. With Big Data related solutions, it is possible to collect, store, process, analyze and visualize various large volumes of data quickly and accurately. Therefore, in this paper, we will directly generate data using Raspberry Pi used in IoT environment, and analyze using various Big Data solutions. Collected by using an Sqoop solution collected and stored in the database to the HDFS, and the process is to process the data by using the solutions available Hive parallel processing is associated with Hadoop. Finally, the analysis and visualization of the processed data via the R programming will be used universally to end verification.

Thread Block Scheduling for Multi-Workload Environments in GPGPU (다중 워크로드 환경을 위한 GPGPU 스레드 블록 스케줄링)

  • Park, Soyeon;Cho, Kyung-Woon;Bahn, Hyokyung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.2
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    • pp.71-76
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    • 2022
  • Round-robin is widely used for the scheduling of large-scale parallel workloads in the computing units of GPGPU. Round-robin is easy to implement by sequentially allocating tasks to each computing unit, but the load balance between computing units is not well achieved in multi-workload environments like cloud. In this paper, we propose a new thread block scheduling policy to resolve this situation. The proposed policy manages thread blocks generated by various GPGPU workloads with multiple queues based on their computation loads and tries to maximize the resource utilization of each computing unit by selecting a thread block from the queue that can maximally utilize the remaining resources, thereby inducing load balance between computing units. Through simulation experiments under various load environments, we show that the proposed policy improves the GPGPU performance by 24.8% on average compared to Round-robin.

Oral rehabilitation of edentulous patient with mandibular implant overdenture using surgical guide (서지컬 가이드를 이용한 하악 임플란트 피개의치 수복 증례)

  • Lee, Dong Hwan;Ryu, Jae Jun
    • The Journal of Korean Academy of Prosthodontics
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    • v.60 no.4
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    • pp.339-346
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    • 2022
  • Compared with traditional full dentures, mandibular implant overdentures have the advantage in that good support and retention can be obtained even with two implants. When manufacturing a mandibular implant overdenture using two implants, it is important to place the implant in the correct position. The long-term prognosis of overdenture is good when two implants are placed in the direction vertical to the occlusal plane and parallel to each other at the canine position. However, it is difficult to place two implants in the correct position in edentulous patients, and if you use surgical guides in these cases, you can get help in placing the implants in a prosthetically advantageous position. This case, a 57-year-old male patient, came to our hospital with all upper and lower teeth removed due to periodontal disease. Therefore, the maxilla was restored with a traditional full denture and the mandible was restored with an implant overdenture using two implants, which resulted in satisfactory functional and esthetic results.

Many-to-many voice conversion experiments using a Korean speech corpus (다수 화자 한국어 음성 변환 실험)

  • Yook, Dongsuk;Seo, HyungJin;Ko, Bonggu;Yoo, In-Chul
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.3
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    • pp.351-358
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    • 2022
  • Recently, Generative Adversarial Networks (GAN) and Variational AutoEncoders (VAE) have been applied to voice conversion that can make use of non-parallel training data. Especially, Conditional Cycle-Consistent Generative Adversarial Networks (CC-GAN) and Cycle-Consistent Variational AutoEncoders (CycleVAE) show promising results in many-to-many voice conversion among multiple speakers. However, the number of speakers has been relatively small in the conventional voice conversion studies using the CC-GANs and the CycleVAEs. In this paper, we extend the number of speakers to 100, and analyze the performances of the many-to-many voice conversion methods experimentally. It has been found through the experiments that the CC-GAN shows 4.5 % less Mel-Cepstral Distortion (MCD) for a small number of speakers, whereas the CycleVAE shows 12.7 % less MCD in a limited training time for a large number of speakers.

A Study on the Activation of Vocational Training Exploiting Company Oriented Qualification (기업 맞춤형 자격 제도를 통한 직업훈련 활성화 방안 연구)

  • Sang-Bong Lee;Eun-Hae Kim;Seung-Hwan Jeon;Byungil Jang;Jun-Ki Min
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.259-271
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    • 2023
  • The purpose of this study is to prepare a plan to activate vocational training through a company-customized qualification system that meets the needs of the industry and responds promptly to changes in the external environment and trends. The BRIDGE 3.0 model was presented as Establishment of qualification system based on education and training result certification, a customized qualification operation system based on local companies by setting the qualification system as a strategy centered on companies that are consumers. To this end, the current status and limitations of vocational competency development projects, the current status and limitations of the domestic qualification system, government policies related to vocational competency development, FGI of corporate personnel managers, surveys of personnel managers of SME, expert advice.