• JSTS:Journal of Semiconductor Technology and Science
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• v.9 no.1
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• pp.1-7
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• 2009

This paper describes design of high energy efficiency 32 bit parallel processor core using instruction-levels data gating and dynamic voltage scaling (DVS) techniques. We present instruction-levels data gating technique. We can control activation and switching activity of the function units in the proposed data technique. We present instruction-levels DVS technique without using DC-DC converter and voltage scheduler controlled by the operation system. We can control powers of the function units in the proposed DVS technique. The proposed instruction-levels DVS technique has the simple architecture than complicated DVS which is DC-DC converter and voltage scheduler controlled by the operation system and a hardware implementation is very easy. But, the energy efficiency of the proposed instruction-levels DVS technique having dual-power supply is similar to the complicated DVS which is DC-DC converter and voltage scheduler controlled by the operation system. We simulate the circuit simulation for running test program using Spectra. We selected reduced power supply to 0.667 times of the supplied power supply. The energy efficiency of the proposed 32 bit parallel processor core using instruction-levels data gating and DVS techniques can improve about 88.4% than that of the 32 bit parallel processor core without using those. The designed high energy efficiency 32 bit parallel processor core can utilize as the coprocessor processing massive data at high speed.

• Korean Journal of Optics and Photonics
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• v.13 no.5
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• pp.425-429
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• 2002

In this paper, we propose new simple schemes for all-optical serial-to-parallel and parallel-to-serial data format converters based on a semiconductor laser amplifier in a loop mirror (SLALOM) for all-optical data processing. They have the advantages of simple and easily expandable structure, efficient operation and easy implementation. We implement the proposed all-optical data converters. and experimentally demonstrate their operation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.4 s.109
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• pp.355-365
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• 2006

The coupled time-integration method with a staggered algorithm based on computational structural dynamics (CSD), finite element method (FEM) and computational fluid dynamics (CFD) has been developed in order to demonstrate physical vibration phenomena due to dynamic aeroelastic excitations. Virtual flutter tests for the spanwise curved ing model have been effectively conducted using the present advanced computational method with high speed parallel processing technique. In addition, the present system can simultaneously give a recorded data file to generate virtual animation for the flutter safety test. The results for virtual flutter test are compared with the experimental data of wind tunnel test. It is shown from the results that the effect of spanwise curvature have a tendency to decrease the flutter dynamic pressure for the same flight condition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2155-2160
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• 2014

In this paper, we proposes a new document summarization method using the extracted semantic feature which the semantic feature is extracted by distributed parallel processing based Hadoop. The proposed method can well represent the inherent structure of documents using the semantic feature by the non-negative matrix factorization (NMF). In addition, it can summarize the big data document using Hadoop. The experimental results demonstrate that the proposed method can summarize the big data document which a single computer can not summarize those.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1263-1271
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• 1999

This paper designs the performance analysis layer for the various performance analysis of parallel programs using event expressions are similar to the normal program language to analyze the events which display a dynamic state exchange of a program. The event expressions suggest operations for overloading and functions which are needed in performance analysis, such as a filtering operation, data format translation functions, performance analysis, static functions, and etc. By using the event expressions, the programmer can modify the event trace data to analyze the performance and analyze more easily and variously than the pre-developed tools.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1284-1286
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• 2003

There is a growing demand on remotely sensed and GIS data services in modern society. However, conventional WEB applications based on client/server pattern can not meet the criteria in the future . Grid computing provides a promising resolution for establishing spatial information system toward future applications. Here, a new architecture of the distributed environment for remotely sensed data processing based on the middleware technology was proposed. In addition, in order to utilize the new environment, a problem had to be algorithmically expressed as comprising a set of concurrently executing sub-problems or tasks. Experiment of the algorithm was implemented, and the results show that the new environmental can achieve high speedups for applications compared with conventional implementation.

• Journal of IKEEE
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• v.20 no.1
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• pp.75-81
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• 2016

This paper proposes a design of the tile based on graphic pipeline to improve the graphic application performance in SIMT based GP-GPU. The proposed Tile based on graphics pipeline avoids unnecessary graphic processing operation, and processes the rasterization step in parallel. The massive data processing in parallel through SIMT architecture improve the computational performance, thereby improving the 3D graphic pipeline performance. The more vertex data of 3D model, the higher performance. The proposed structure was confirmed to improve processing performance of up to 3 times from about 1.18 times as compared to 'RAMP' and previous studies.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.122-129
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• 2005

On the cluster system, the parallel code of rigid-plastic FEM has been developed. The cluster system, Simforge, has 15 processors and the total memory is 4.5GBytes. In the developed parallel code, the distributed data of the column-wise partitioned stiffness are stored as the compressed row storage and the diagonal preconditioned conjugate gradient solver is applied. The analysis of block upsetting is performed with the parallel code on Simforge cluster system. In this paper, the analysis results are compared and discussed.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.409-410
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• 2008

This paper presents nonlinear and parallel design for synchronous pipelining in IP-based H.264 decoder implementation. Since H.264 decoder includes the dataflow of feedback loop, the data dependency requires one NOP stage per pipelining latency to drop the throughput into 1/2. Further, it is found that, in execution time, the stage scheduled for MC is more occupied than that for CAVLD/ITQ/DF. The less efficient stage would be improved by nonlinear scheduling, while the fully-utilized stage could be accelerated by parallel scheduling of IP. The optimization yields 3 nonlinear {CAVLD&ITQ}|3 parallel (MC/IP&Rec.)| 3 nonlinear {DF} pipelined architecture for IP-based H.264 decoder. In experiments, the nonlinear and parallel pipelined H.264 decoder, including existing IPs, could deal with full HD video at 41.86MHz, in real time processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3182-3202
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• 2015

Flexibly expanding the storage capacity required to process a large amount of rapidly increasing unstructured log data is difficult in a conventional computing environment. In addition, implementing a log processing system providing features that categorize and analyze unstructured log data is extremely difficult. To overcome such limitations, we propose and design a MongoDB-based unstructured log processing system (MdbULPS) for collecting, categorizing, and analyzing log data generated from banks. The proposed system includes a Hadoop-based analysis module for reliable parallel-distributed processing of massive log data. Furthermore, because the Hadoop distributed file system (HDFS) stores data by generating replicas of collected log data in block units, the proposed system offers automatic system recovery against system failures and data loss. Finally, by establishing a distributed database using the NoSQL-based MongoDB, the proposed system provides methods of effectively processing unstructured log data. To evaluate the proposed system, we conducted three different performance tests on a local test bed including twelve nodes: comparing our system with a MySQL-based approach, comparing it with an Hbase-based approach, and changing the chunk size option. From the experiments, we found that our system showed better performance in processing unstructured log data.