• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제6권5호
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• pp.457-467
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• 2000

본 논문에서는 분산 메모리 구조를 갖는 병렬 컴퓨터 상에서 방대한 크기를 갖는 볼륨 데이터의 효과적인 가시화를 위한 병렬 광선 투사법을 제안한다. 데이터의 압축을 기반으로 하는 본 기법은 다른 프로세서의 메모리로부터 데이터를 읽기보다는 자신의 지역 메모리에 존재하는 압축된 데이터를 빠르게 복원함으로써 병렬 렌더링 성능을 향상시키는 것을 목표로 한다. 본 기법은 객체-순서와 영상-순서 탐색 알고리즘 모두의 정점을 이용하여 성능을 향상시켰다. 즉, 블록 단위의 최대-최소 팔진트리의 탐색과 각 픽셀의 불투명도 값을 동적으로 유지하는 실시간 사진트리를 응용함으로써 객체-공간과 영상-공간 각각의 응집성을 이용하였다. 본 논문에서 제안하는 압축 기반 병렬 볼륨 렌더링 방법은 렌더링 수행 중 발생하는 프로세서간의 통신을 최소화하도록 구현되었는데, 이러한 특징은 프로세서 사이의 상당히 높은 데이터 통신 비용을 감수하여야 하는 PC 및 워크스테이션의 클러스터와 같은 더욱 실용적인 분산 환경에서 매우 유용하다. 본 논문에서는 Cray T3E 병렬 컴퓨터 상에서 Visible Man 데이터를 이용하여 실험을 수행하였다.

• 전자통신동향분석
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• 제35권3호
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• pp.76-84
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• 2020

Neuromorphic hardware refers to brain-inspired computers or components that model an artificial neural network comprising densely connected parallel neurons and synapses. The major element in the widespread deployment of neural networks in embedded devices are efficient architecture for neuromorphic hardware with regard to performance, power consumption, and chip area. Spiking neural networks (SiNNs) are brain-inspired in which the communication among neurons is modeled in the form of spikes. Owing to brainlike operating modes, SNNs can be power efficient. However, issues still exist with research and actual application of SNNs. In this issue, we focus on the technology development cases and market trends of two typical tracks, which are listed above, from the point of view of artificial intelligence neuromorphic circuits and subsequently describe their future development prospects.

• Computers and Concrete
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• 제16권1호
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• pp.179-190
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• 2015

An experimental program has been carried out to investigate the effect of edge-slope on compressive strength of concrete specimens. In this study, effect of such slope was investigated by testing 100 standard cylinder specimens and 40 standard cubes. When molds are put on a slanted place, wet concrete starts to flow through the open end of mold. It keeps flowing until it reaches to a parallel surface with the place over which it was placed. That creates a sloped surface over the loading area. Experimental results revealed significant relationships between failure loads and slope of loading surface for cylinders. Angled cracks occurred in sloped cylinder specimens. Tension cracks occurred in cube specimens. Fracture mechanisms were also evaluated by using finite element analyses approach. Experiments yielded an exponential curve with bandwidth for cylinders. Average value of curve is $y={\frac{\pi}{2}}e^{-cf}$ between slope and compressive strength. Inclination is much effective parameter for cylinders than cubes.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.45-48
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• 2003

We can easily buy network system for high performance micro-processor, progress computer architecture is caused of high bandwidth and low delay time. Coupling PC-based commodity technology with distributed computing methodologies provides an important advance in the development of single-user dedicated systems. Lately Network is joined PC or workstation by computers of high performance and low cost. Than it make intensive that Cluster system is resembled supercomputer. Unix, Linux, BSD, NT(Windows series) can use Cluster system OS(operating system). I'm chosen linux gain low cost, high performance and open technical documentation. This paper is benchmark performance of Beowulf clustering by UltraSPARC-1K(64bit-RISC processor). Benchmark tools use MPI(Message Passing Interface) and NetPIPE. Beowulf is a class of experimental parallel workstations developed to evaluate and characterize the design space of this new operating point in price-performance.

• 한국학교수학회논문집
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• 제2권1호
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• pp.181-195
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• 1999

This research is produced as a applet of learning materials, and is made with the internet languages HTML, Java, and NamoWebeditor. It contains "Greatest Common Divisor and Least Common Multiple", "Parallel translation of function of second order", "Pythagoras Theorem", which is the current middle school mathmatics textbook for third graders. The keynote of this research is that the students can study individually through logging into the internet on their own computers; the program is made using graphics and animation on order to develop the learners′ interest in mathematics. I hope that this research can supplement our currently insufficient internet educational data.

• 한국가시화정보학회지
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• 제5권2호
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• pp.9-13
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• 2007

Typhoon simulation based on dynamical forecasting results is demonstrated by utilizing geodesic model GME (operational global numerical weather prediction model of German Weather Service). It is based on uniform icosahedral-hexagonal grid. The GME gridpoint approach avoids the disadvantages of spectral technique as well as the pole problem in latitude-longitude grids and provides a data structure extremely well suited to high efficiency on distributed memory parallel computers. In this study we made an attempt to simulate typhoon 'NARI' that passed over the Korean Peninsula in 2007. GME has attributes of numerical weather prediction model and its high resolution can provide details on fine scale. High resolution of GME can play key role in the study of severe weather phenomenon such as typhoons. Simulation of future typhoon that is assumed to occur under the global warming situation shows that the life time of that typhoon will last for a longer time and the intensity will be extremely stronger.

• 전자공학회논문지B
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• 제30B권11호
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• pp.11-16
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• 1993

VLIW architecture capable of testing multiple conditions in a cycle must support an efficient mechanism for multi-way branches. This paper proposes a mechanism to speed up the execution of multi-way branches and an efficient memory packing method of instructions, which reduced the wasted memory space. Also, we develops a new compiler technique which can transform program segments that are not applied to multi-way branches into ones that are applied to multi-way branches. The benefits gained by the transformation are to reduce branch penalty and to increase instruction-level parallelism.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2003년도 추계 학술대회논문집
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• pp.63-68
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• 2003

The Grid[1] is a communication service that collaborates dispersed high performance computers so that those can be shared and worked together. So, the Grid enables a researcher to analyze a huge-sized problem which was impossible by using local resources. However, diverse communication speeds among computing resources and heterogeneity of computing resources can reduce parallel efficiency in the Grid, The present paper focuses on the development of an efficient load balancing algorithm suitable for the Grid. Proposed algorithm classifies the whole processors into several groups with relatively faster communication speeds. Computational domain is firstly partitioned to each group and then to the processor level considering the performance of each processor. Developed algorithm is validated in the homogeneous system by comparing the present result with the result of equally partitioned meshes and then applied to the heterogeneous system. Additionally, the present algorithm is expanded to be able to solve the decomposed domains and applied to some problems.

• 전기학회논문지
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• 제66권7호
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• pp.1078-1082
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• 2017

This paper presents an L1 optimization based filtering technique which effectively eliminates the optical misalignment effects encountered in the squint guidance mode with strapdown seekers. We formulated a series of L1 optimization problems in order to separate the bias and the gradient components from the measured data, and solved them via the alternating direction method of multipliers (ADMM) and sparse matrix decomposition techniques. The proposed technique was able to rapidly detect arbitrary discontinuities and gradient changes from the measured signals, and was shown to effectively cancel the undesirable effects coming from the seeker misalignment angles. The technique was implemented on embedded flight computers and the real-time operational performance was verified via the hardware-in-the-loop simulation (HILS) tests in parallel with the automatic target recognition algorithms and the intra-red synthetic target images.

• Journal of information and communication convergence engineering
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• 제16권2호
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• pp.99-105
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• 2018

k-Nearest neighbor join (k-NN Join) is a computationally intensive algorithm that is designed to find k-nearest neighbors from a dataset S for every object in another dataset R. Most related studies on k-NN Join are based on single-computer operations. As the data dimensions and data volume increase, running the k-NN Join algorithm on a single computer cannot generate results quickly. To solve this scalability problem, we introduce the locality-sensitive hashing (LSH) k-NN Join algorithm implemented in Spark, an approach for high-dimensional big data. LSH is used to map similar data onto the same bucket, which can reduce the data search scope. In order to achieve parallel implementation of the algorithm on multiple computers, the Spark framework is used to accelerate the computation of distances between objects in a cluster. Results show that our proposed approach is fast and accurate for high-dimensional and big data.