• 한국컴퓨터정보학회논문지
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• 제22권10호
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• pp.101-107
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• 2017

In this paper, we study the problem of parallel machine scheduling considering the moving time of multiple servers. The parallel machine scheduling is to assign jobs to parallel machines so that the total completion time(makespan) is minimized. Each job has a setup phase, a processing phase and a removal phase. A processing phase is performed by a parallel machine alone while a setup phase and a removal phase are performed by both a server and a parallel machine simultaneously. A server is needed to move to a parallel machine for a setup phase and a removal phase. But previous researches have been done under the assumption that the server moving time is zero. In this study we have proposed an efficient algorithm for the problem of parallel machine scheduling considering multiple server moving time. We also have investigated experimentally how the number of servers and the server moving time affect the total completion time.

• Journal of information and communication convergence engineering
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• 제17권4호
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• pp.267-273
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• 2019

South Korea has allowed parallel importation since 1995. Parallel importation causes competition among importers in the logistics process allowing, consumers to purchase foreign brand products at low prices. Most parallel importers base product pricing on subjective judgements. Fashion products in particular, have different sales rates depending on trends and seasons, so sales performance varies greatly depending on selling price timing and policy. The merchandiser (MD) set the price on parallel importation products by aggregating information on imported products and pricing goods. However, this customized process is very time consuming for the MD. This is because the logistics process of parallel importation's customs clearance procedures and repair works is complicated and takes a significant amount of time. In this paper, we propose an improved parallel importation logistics process based on big data, which automatically sets the price of parallel importation products.

• International Journal of Internet, Broadcasting and Communication
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• 제11권3호
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• pp.1-7
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• 2019

Previously, parallel computing was mainly used in areas requiring high computing performance, but nowadays, multicore CPUs and GPUs have become widespread, and parallel programming advantages can be obtained even in a PC environment. Various parallel programming frameworks using multicore CPUs such as OpenMP and PPL have been announced. Nvidia and AMD have developed parallel programming platforms and APIs for program developers to take advantage of multicore GPUs on their graphics cards. In this paper, we develop digital image transformation programs that runs on each of the major parallel programming frameworks, and measure the execution time. We analyze the characteristics of each framework through the execution time comparison. Also a constant K indicating the ratio of program execution time between different parallel computing environments is presented. Using this, it is possible to predict rough execution time without implementing a parallel program.

• 대한수학회지
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• 제43권2호
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• pp.399-411
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• 2006

Let L be a subspace lattice on a Hilbert space H and X and Y be operators acting on a Hilbert space H. Let P be the projection onto $\frac\;{R(X)}$, where RX is the range of X. If PE = EP for each $E\;\in\;L$, then there exists an operator A in AlgL such that AX = Y if and only if $$sup\{{\parallel}E^{\bot}Yf{\parallel}/{\parallel}E^{\bot}Xf{\parallel}\;:\;f{\in}H,\; E{\in}L}=K\;<\;\infty$$ Moreover, if the necessary condition holds, then we may choose an operator A such that AX = Y and ${\parallel}A{\parallel} = K.$ Let x and y be vectors in H and let $P_x$ be the projection onto the singlely generated space by x. If $P_xE = EP_x$ for each $E\inL$, then the assertion that there exists an operator A in AlgL such that Ax = y is equivalent to the condition $$K_0\;:\;=\;sup\{{\parallel}E^{\bot}y{\parallel}/{\parallel}E^{\bot}x\;:\;E{\in}L}=<\;\infty$$ Moreover, we may choose an operator A such that ${\parallel}A{\parallel} = K_0$ whose norm is $K_0$ under this case.

• Journal of Information Processing Systems
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• 제12권4호
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• pp.724-740
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• 2016

The performance issues of screening large database compounds and multiple query compounds in virtual screening highlight a common concern in Chemoinformatics applications. This study investigates these problems by choosing group fusion as a pilot model and presents efficient parallel solutions in parallel platforms, specifically, the multi-core architecture of CPU and many-core architecture of graphical processing unit (GPU). A study of sequential group fusion and a proposed design of parallel CUDA group fusion are presented in this paper. The design involves solving two important stages of group fusion, namely, similarity search and fusion (MAX rule), while addressing embarrassingly parallel and parallel reduction models. The sequential, optimized sequential and parallel OpenMP of group fusion were implemented and evaluated. The outcome of the analysis from these three different design approaches influenced the design of parallel CUDA version in order to optimize and achieve high computation intensity. The proposed parallel CUDA performed better than sequential and parallel OpenMP in terms of both execution time and speedup. The parallel CUDA was 5-10x faster than sequential and parallel OpenMP as both similarity search and fusion MAX stages had been CUDA-optimized.

• 대한수학회보
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• 제60권6호
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• pp.1555-1566
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• 2023

A Hilbert space operator A ∈ B(H) is a generalised n-projection, denoted A ∈ (G-n-P), if A^*n = A. (G-n-P)-operators A are normal operators with finitely countable spectra σ(A), subsets of the set $\{0\}\,{\cup}\,\{\sqrt[n+1]{1}\}.$ The Aluthge transform à of A ∈ B(H) may be (G - n - P) without A being (G - n - P). For doubly commuting operators A, B ∈ B(H) such that σ(AB) = σ(A)σ(B) and ${\parallel}A{\parallel}\,{\parallel}B{\parallel}\;{\leq}\;{\parallel}{\tilde{AB}}{\parallel},$ ${\tilde{AB}}\;{\in}\;(G\,-\,n\,-\,P)$ if and only if $A\;=\;{\parallel}{\tilde{A}}{\parallel}\,(A_{00}\,{\oplus}\,(A_0\,{\oplus}\,A_u))$ and $B\;=\;{\parallel}{\tilde{B}}{\parallel}\,(B_0\,{\oplus}\,B_u),$ where A₀₀ and B₀, and A₀ ⊕ A_u and B_u, doubly commute, A₀₀B₀ and A₀ are 2 nilpotent, A_u and B_u are unitaries, A^*n_u = A_u and B^*n_u = B_u. Furthermore, a necessary and sufficient condition for the operators αA, βB, αà and ${\beta}{\tilde{B}},\;{\alpha}\,=\,\frac{1}{{\parallel}{\tilde{A}}{\parallel}}$ and ${\beta}\,=\,\frac{1}{{\parallel}{\tilde{B}}{\parallel}},$ to be (G - n - P) is that A and B are spectrally normaloid at 0.

• International Journal of Reliability and Applications
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• 제12권2호
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• pp.103-116
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• 2011

A series-parallel system with independent but non-identical components is considered. The expressions have been derived for the joint reliability importance (JRI) of m (${\geq}2$) components, chosen from a series-parallel system. JRIs of components of two different series-parallel systems are studied analytically and graphically.

• 한국정보통신학회논문지
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• 제14권4호
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• pp.859-867
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• 2010

본 논문에서는 일반적인 비트기반의 비선형 결합함수를 고속화하기 위하여 워드기반 스트림 암호에서 적용될 워드기반 비선형 결합함수 구조를 제안하였다. 특히, 워드기반 병렬구조를 갖는 PS-WFSR을 제안하였고, 이를 활용하여 비트 기반 비선형 결합함수를 고속화시킨 4가지 형태의 워드기반 병렬형 비선형 결합함수를 다음과 같이 제안하였다. m-병렬 워드기반 비메모리 비선형 결합함수, m-병렬 워드기반 메모리 비선형 결합함수, m-병렬 워드기반 비선형 필터함수, m-병렬 워드기반 클럭조절형 함수를 제안하였고, 마지막으로 m-병렬 워드기반 DRAGON의 병렬 구조를 통하여 그 성능을 분석하였다.

• 한국통신학회논문지
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• 제33권6C호
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• pp.438-443
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• 2008

The efficient method to implement the Max-Log-MAP algorithm is proposed by modifying the conventional algorithm. It is called a parallel soft output Viterbi algorithm (SOVA) and the rigorous proof is given for the equivalence between the Max-Log-MAP algorithm and the parallel SOVA. The parallel SOVA is compared with the conventional algorithms and we show that it is an efficient algorithm implementing the modified SOVA in parallel.

• East Asian mathematical journal
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• 제19권1호
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• pp.73-80
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• 2003

Let D be a bounded domain in $\mathbb{C}^n$ with $C^2$ boundary. In this paper, we prove the following inequality $${\parallel}u{\parallel}_{p_2,{\alpha}_2}{\lesssim}{\parallel}u{\parallel}_{p_1,{\alpha}_1}+{\parallel}\bar{\partial}u{\parallel}_{p_1,{\alpha}_1+p_1}/2$$, where $1{\leq}p_1{\leq}p_2<\infty,\;{\alpha}_j>0,(n+{\alpha}_1)/p_1=(n+{\alpha}_1)/p_1=(n+{\alpha}_2)/p_2$, and $1/p_2{\geq}1/p_1-1/2n$.