• 제목/요약/키워드: Pipeline implementation

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FPGA Implementation of Real-time 2-D Wavelet Image Compressor (실시간 2차원 웨이블릿 영상압축기의 FPGA 구현)

  • 서영호;김왕현;김종현;김동욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제27권7A호
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    • pp.683-694
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    • 2002
  • In this paper, a digital image compression codec using 2D DWT(Discrete Wavelet Transform) is designed using the FPGA technology for real time operation The implemented image compression codec using wavelet decomposition consists of a wavelet kernel part for wavelet filtering process, a quantizer/huffman coder for quantization and huffman encoding of wavelet coefficients, a memory controller for interface with external memories, a input interface to process image pixels from A/D converter, a output interface for reconstructing huffman codes, which has irregular bit size, into 32-bit data having regular size data, a memory-kernel buffer to arrage data for real time process, a PCI interface part, and some modules for setting timing between each modules. Since the memory mapping method which converts read process of column-direction into read process of the row-direction is used, the read process in the vertical-direction wavelet decomposition is very efficiently processed. Global operation of wavelet codec is synchronized with the field signal of A/D converter. The global hardware process pipeline operation as the unit of field and each field and each field operation is classified as decomposition levels of wavelet transform. The implemented hardware used FPGA hardware resource of 11119(45%) LAB and 28352(9%) ESB in FPGA device of APEX20KC EP20k600CB652-7 and mapped into one FPGA without additional external logic. Also it can process 33 frames(66 fields) per second, so real-time image compression is possible.

Necessity of the Physical Distribution Cooperation to Enhance Competitive Capabilities of Healthcare SCM -Bigdata Business Model's Viewpoint- (의료 SCM 경쟁역량 강화를 위한 물류공동화 도입 필요성 -빅데이터 비즈니스 모델 관점-)

  • Park, Kwang-O;Jung, Dae-Hyun;Kwon, Sang-Min
    • Management & Information Systems Review
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    • 제39권3호
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    • pp.17-35
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    • 2020
  • The purpose of this study is to develop business models for current situational scenarios reflecting customer needs emphasize the need for implementing a logistics cooperation system by analyzing big data to strengthen SCM competitiveness capacities. For healthcare SCM competitiveness needed for the logistics cooperation usage intent, they were divided into product quality, price leadership, hand-over speed, and process flexibility for examination. The wordcloud results that analyzed major considerations to realize work efficiency between medical institutes, words like unexpected situations, information sharing, delivery, real-time, delivery, convenience, etc. were mentioned frequently. It can be analyzed as expressing the need to construct a system that can immediately respond to emergency situations on the weekends. Furthermore, in addition to pursuing communication and convenience, the importance of real-time information sharing that can share to the efficiency of inventory management were evident. Accordingly, it is judged that it is necessary to aim for a business model that can enhance visibility of the logistics pipeline in real-time using big data analysis on site. By analyzing the effects of the adaptability of a supply chain network for healthcare SCM competitiveness, it was revealed that obtaining competitive capacities is possible through the implementation of logistics cooperation. Stronger partnerships such as logistics cooperation will lead to SCM competitive capacities. It will be necessary to strengthen SCM competitiveness by searching for a strategic approach among companies in a direction that can promote mutual partnerships among companies using the joint logistics system of medical institutes. In particular, it will be necessary to search for ways to utilize HCSM through big data analysis according to the construction of a logistics cooperation system.

Design and Implementation of Memory-Centric Computing System for Big Data Analysis

  • Jung, Byung-Kwon
    • Journal of the Korea Society of Computer and Information
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    • 제27권7호
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    • pp.1-7
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    • 2022
  • Recently, as the use of applications such as big data programs and machine learning programs that are driven while generating large amounts of data in the program itself becomes common, the existing main memory alone lacks memory, making it difficult to execute the program quickly. In particular, the need to derive results more quickly has emerged in a situation where it is necessary to analyze whether the entire sequence is genetically altered due to the outbreak of the coronavirus. As a result of measuring performance by applying large-capacity data to a computing system equipped with a self-developed memory pool MOCA host adapter instead of processing large-capacity data from an existing SSD, performance improved by 16% compared to the existing SSD system. In addition, in various other benchmark tests, IO performance was 92.8%, 80.6%, and 32.8% faster than SSD in computing systems equipped with memory pool MOCA host adapters such as SortSampleBam, ApplyBQSR, and GatherBamFiles by task of workflow. When analyzing large amounts of data, such as electrical dielectric pipeline analysis, it is judged that the measurement delay occurring at runtime can be reduced in the computing system equipped with the memory pool MOCA host adapter developed in this research.

The effect of external influence and operational management level on urban water system from water-energy nexus perspective (물-에너지 넥서스 관점에서 외부영향과 운영관리 수준이 도시물순환시스템에 미치는 영향)

  • Choi, Seo Hyung;Shin, Bongwoo;Song, Youngseok;Kim, Dongkyun;Shin, Eunher
    • Journal of Korea Water Resources Association
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    • 제56권9호
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    • pp.587-602
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    • 2023
  • Due to climate change, population growth, and economic development, the demand for water in the urban water system (UWS) and the energy required for water use constantly increase. Therefore, beyond the traditional method of considering only the water sector, the Nexus approach, which considers synergies and trade-offs between the water and energy sectors, has begun to draw attention. In previous researches, the Nexus methodology was used to demonstrate that the UWS is an energy-intensive system, analyze the water-energy efficiency relationship surrogated by energy intensity, and identify climate (long-term climate change, drought, type), geographic characteristics (topography, flat ratio, location), system characteristics (total supply water amount, population density, pipeline length), and operational management level (water network pressure, leakage rate, water saving) effects on the UWS. Through this, it was possible to suggest the direction of policies and institutions to UWS managers. However, there was a limit to establishing and implementing specific action plans. This study built the energy intensity matrix of the UWS, quantified the impact of city conditions, external influences, and operational management levels on the UWS using the water-energy Nexus model, and introduced water-energy efficiency criteria. With this, UWS managers will be able to derive strategies and action plans for efficient operation management of the UWS and evaluate suitability and validity after implementation.