• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1984.04a
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• pp.29-32
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• 1984

A microprocessor for the dedicated purpose of digital filtering has been designed and constructed. A microsequencer to control the flowing of data is designed with the concept of a hardware compiler of AHPI, statements. In order to save the processing time, this system utilizes parallel data calculation method instead of the one proposed by Peled and Liu which depended on serial calculation method. The flexible program control technique has been applied to the implementation of the sepcialprocessor for the digital signal processing.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.338-348
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• 1997

In this pater, we first propose a data distribution framework to resolve load imbalance and bucket oerflow in parallel hash join.Using the histogram equalization technique, the framework transforms a histogram of skewed data to the desired uniform distribution that corresponds to the relative computing power of node processors in the system.Next we propose an effcient parallel hash join algorithm for handing skwed data based on the proposed data distribution methodology.For performance comparison of our algorithm with other hash join algorithms.we perform similation experiments and actual exeution on COREDB database computer with 8-node hyperube architecture. In these experiments, skwed data distebution of the join atteibute is modeled using a Zipf-like distribution.The perfomance studies undicate that our algorithm outperforms other algorithms in the skewed cases.

• The Journal of Korean Institute of Information Technology
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• v.17 no.7
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• pp.31-45
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• 2019

The core technologies for intelligent services today are deep learning, that is neural networks, and parallel and distributed processing technologies such as GPU parallel computing and big data. However, for intelligent services and knowledge sharing services through globally shared ontologies in the future, there is a technology that is better than the neural networks for representing and reasoning knowledge. It is a knowledge representation of IF-THEN in RIF or SWRL, which is the standard rule language of the Semantic Web, and can be inferred efficiently using the rete algorithm. However, when the number of rules processed by the rete algorithm running on a single computer is 100,000, its performance becomes very poor with several tens of minutes, and there is an obvious limitation. Therefore, in this paper, we analyze the past and current studies on parallel and distributed processing of rete algorithm, and examine what aspects should be considered to implement an efficient rete algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.372-380
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• 2022

This study proposes a distributed parallel processing system, called the Fast Analysis System for remote sensing daTa(FAST), for large-scale satellite image processing and analysis. FAST is a system that designs jobs in vertices and sequences, and distributes and processes them simultaneously. FAST manages data based on the Hadoop Distributed File System, controls entire jobs based on Apache Spark, and performs tasks in parallel in multiple slave nodes based on a docker container design. FAST enables the high-performance processing of progressively accumulated large-volume satellite images. Because the unit task is performed based on Docker, it is possible to reuse existing source codes for designing and implementing unit tasks. Additionally, the system is robust against software/hardware faults. To prove the capability of the proposed system, we performed an experiment to generate the original satellite images as ortho-images, which is a pre-processing step for all image analyses. In the experiment, when FAST was configured with eight slave nodes, it was found that the processing of a satellite image took less than 30 sec. Through these results, we proved the suitability and practical applicability of the FAST design.

• The KIPS Transactions:PartA
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• v.11A no.3
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• pp.207-212
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• 2004

This paper provides the higher user QoS(Quality of Service) by analyzing media service model between server and client in single VoD(Video on Demand) environment and applying it to parallel VoD environment. Media service model is divided into the Client Pull, Server Push, and IPP(Interleaving Pull & Push) model. A server sends data based on client's request in the Client Pull Model. A server one-sidedly sends data without client's request in the Server Pull model. And the WP model unites above two models. For a parallel VoD environment, We built the PMSS system which provides the parallel media streaming services that one client is simultaneously served by several servers. In the single and parallel VoD environment, We compare and analyze the performance of service models with respect to network delay and data size in buffer. In this experiment, we found that IPP service model keeps the least network delay and stable client buffer in the parallel VoD environment. This result shows that PMSS can provide the more quality of service.

• Korean Journal of Optics and Photonics
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• v.24 no.5
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• pp.262-270
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• 2013

In this paper, we propose a modified optical CBC(Cipher Block Chaining) encryption method using optical XOR logic operations. The proposed method is optically implemented by using dual encoding and a free-space interconnected optical logic gate technique in order to process XOR operations in parallel. Also, we suggest a CBC encryption/decryption optical module which can be fabricated with simple optical architecture. The proposed method makes it possible to encrypt and decrypt vast two-dimensional data very quickly due to the fast optical parallel processing property, and provides more security strength than the conventional electronic CBC algorithm because of the longer security key with the two-dimensional array. Computer simulations show that the proposed method is very effective in CBC encryption processing and can be applied to even ECB(Electronic Code Book) mode and CFB(Cipher Feedback Block) mode.

• Journal of the Korea Society for Simulation
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• v.26 no.3
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• pp.13-22
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• 2017

This research proposes and applies a pipelining parallel processing technique to enhance the speed of visualizing the results of real-time simulations. Generally, a simulation with real-time visualization consists of three processes: executing a simulation model, transmitting simulation result, and visualizing simulation result. If we have these processes in serial, the latency from simulation to visualization will be very long, which degrades the speed of visualization of data from real-time simulation. Thus, the main purpose of this research is maximizing performance by adapting pipelining parallel processing technique to the real-time simulation visualization. Also we show that performance is improved by adding multi-threading technique to each process. This paper proposes a theoretical performance model and simulation results of the techniques and then we applied this to an air combat simulation model as a case study. As the result, it shows that the performance is greatly enhanced than the original model's execution time.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.6
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• pp.858-863
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• 2010

In order to enhance encoding speed in dynamic image encoding using H.264/AVC, reducing the time for motion estimation which takes a large portion of the processing time is very important. An approach using graphics processing unit(GPU) as a coprocessor to assist the central processing unit(CPU) in computing massive data, will be a way to reduce the processing time. In this paper, we present an efficient block-level parallel algorithm for the motion estimation(ME) on a computer unified device architecture(CUDA) platform developed in general-purpose computation on GPU. Experiments are carried out to verify the effectiveness of the proposed algorithm.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1386-1396
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• 1996

In the distributed multimedia application, high throughput and low delay is one of the most important QoS(Quality of Service) requirement. Emerging high speed communication offers transmission rate above Gbps, but it can not be utilized efficiently by the performance bottlenecks of communication protocols. To overcom the problem, we propose a horizontal processing architecture that processes data as soon as it arrive from the network. Unfortunately, the OSI protocol stack often imposes ordering constraints that prevent concurrent processing of the protocol layers. By using a fixed packet format, the network layer through the presentation layer are processed in parallel. Our prototype shows that the proposed model has performance improvement up to 61% more advantage than the conventional approach.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1636-1651
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• 1997

In task parallel language like Fortran M, programmer writes a task parallel program using parallel constructs which is provided. When some data dependencies exist between called procedures in various applications, it is difficult for programmer to write program according to their dependencies. Therefore, it is desirous that compiler can detect some implicit parallelisms and transform a program to parallelized form by using the task parallel constructs like PROCESSES block or PROCESSDO loop of Fortran M. But current task parallel language compilers can't provide these works. In this paper, we analyze the cases according to dependence relations and detect the implicit parallelism which can be transformed to task parallel constructs like PROCESSES block and PROCESSDO loop of Fortran M. Also, For the case which program can be paralleized both PROCESSES block and PROCESSDO loop, we analyze that which construct is more effective for various conditions.