• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.5
• /
• pp.203-208
• /
• 2013

As smartphones are rapidly and widely spread, their applications request gradually larger computation power. Recently, in the personal computer, computing power of hardware has exceeded performance requirement of software sometimes. Computing power of smartphone, however, will not grow at the same pace as demand of applications because of form factor to seek thinner devices and power limitation by relatively slow technical progress of battery. Computation offloading is getting huge attention as one of solution for the problem. It has not commonly used technology in spite of advantages for performance and power consumption since the existing offloading frameworks are difficult for application developer to utilize. This paper presents an application developer-friendly offloading framework, named SorMob. Based on Aspect Oriented Programming model, SorMob provides a convenient environment for application development, and its performance was verified by comparing with the existing offloading framework.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.5 no.1
• /
• pp.85-100
• /
• 2001

In this paper we propose a block-type parallel preconditioner for solving large sparse nonsymmetric linear systems, which we expect to be scalable. It is Multi-Color Block SOR preconditioner, combined with direct sparse matrix solver. For the Laplacian matrix the SOR method is known to have a nondeteriorating rate of convergence when used with Multi-Color ordering. Since most of the time is spent on the diagonal inversion, which is done on each processor, we expect it to be a good scalable preconditioner. Finally, due to the blocking effect, it will be effective for ill-conditioned problems. We compared it with four other preconditioners, which are ILU(0)-wavefront ordering, ILU(0)-Multi-Color ordering, SPAI(SParse Approximate Inverse), and SSOR preconditioner. Experiments were conducted for the Finite Difference discretizations of two problems with various meshsizes varying up to 1024 x 1024, and for an ill-conditioned matrix from the shell problem from the Harwell-Boeing collection. CRAY-T3E with 128 nodes was used. MPI library was used for interprocess communications. The results show that Multi-Color Block SOR and ILU(0) with Multi-Color ordering give the best performances for the finite difference matrices and for the shell problem only the Multi-Color Block SOR converges.

• Journal of Power Electronics
• /
• v.16 no.5
• /
• pp.1821-1832
• /
• 2016

This study presents a strategy using the synchronized output regulation method (SOR) for controlling inverters operating in stand-alone and grid-connected modes. From the view point of networked dynamic systems, SOR involves nodes with outputs that are synchronized but also display a desirable wave shape. Under the SOR strategy, the inverter and grid are treated as two nodes that comprise a simple network. These two nodes work independently under the stand-alone mode. An intermediate mode, here is named the synchronization mode, is emphasized because the transition from the stand-alone mode to the grid-connected mode can be dealt as a standard SOR problem. In the grid-connected mode, the inverter operates in an independent way, in which the voltage reference changes for generalized synchronization where its output current satisfies the required power injection. Such a relatively independent design leads to a seamless transfer between operation modes. The closed-loop system is analyzed in the state space on the basis of the output regulation theory, which improves the robustness of the design. Simulations and experiments are performed to verify the proposed control strategy.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.5
• /
• pp.307-314
• /
• 2023

As supercomputing and hardware technology advances, climate prediction models are improving. The Korean Meteorological Administration adopted GloSea5 from the UK Met Office and now operates an updated GloSea6 tailored to Korean weather. Universities and research institutions use Low-GloSea6 on smaller servers, improving accessibility and research efficiency. In this paper, profiling Low-GloSea6 on smaller servers identified the tri_sor_dp_dp subroutine in the tri_sor.F90 atmospheric model as a CPU-intensive hotspot. Applying linear regression, a type of machine learning, to this function showed promise. After removing outliers, the linear regression model achieved an RMSE of 2.7665e-08 and an MAE of 1.4958e-08, outperforming Lasso and ElasticNet regression methods. This suggests the potential for machine learning in optimizing identified hotspots during Low-GloSea6 execution.

• The KIPS Transactions:PartA
• /
• v.8A no.3
• /
• pp.227-234
• /
• 2001

In this paper we propose a block-type parallel preconditioner for solving large sparse nonsymmetric linear systems, which we expect to be scalable. It is Multi-Color Block SOR preconditioner, combined with direct sparse matrix solver. For the Laplacian matrix the SOR method is known to have a nondeteriorating rate of convergence when used with Multi-Color ordering. Since most of the time is spent on the diagonal inversion, which is done on each processor, we expect it to be a good scalable preconditioner. We compared it with four other preconditioners, which are ILU(0)-wavefront ordering, ILU(0)-Multi-Color ordering, SPAI(SParse Approximate Inverse), and SSOR preconditiner. Experiments were conducted for the Finite Difference discretizations of two problems with various meshsizes varying up to $1025{\times}1024$. CRAY-T3E with 128 nodes was used. MPI library was used for interprocess communications, The results show that Multi-Color Block SOR is scalabl and gives the best performances.

• Journal of Preventive Medicine and Public Health
• /
• v.42 no.1
• /
• pp.67-72
• /
• 2009

Objectives : Using the population-based cancer registry in Jejudo, we found that Jejudo had lower incidence in stomach cancer than other regions in Korea. The aim of this study was to evaluate reasons for this difference. Methods : Citrus is the leading agricultural production in Jejudo, suggesting that lower cancer incidence in Jejudo could be explained by citrus fruit intake. We evaluated this hypothesis with quantitative systematic review(QSR). Results : Stomach cancer incidence was significantly lower, with a summary odds ratio(SOR) after QSR of 0.72 [95% CI=0.64-0.81]. In addition, the SOR of pancreatic cancer tended to be lower at 0.83 [95% CI=0.70-0.98]. The SOR of prostate cancer was slightly higher at 1.03 [0.89-1.19]. Conclusions : Quantitative systematic reviews for the effect of citrus fruit intake on cancer occurrence suggested that lower cancer incidence in Jejudo could be explained by intake of citrus fruits.

• Journal of the Korean Mathematical Society
• /
• v.49 no.4
• /
• pp.805-827
• /
• 2012

In this paper, we first study convergence of a special type of multisplitting methods with preweighting, and then we provide some comparison results of those multisplitting methods. Next, we propose both parallel implementation of an SOR-like multisplitting method with preweighting and an application of the SOR-like multisplitting method with preweighting to a parallel preconditioner of Krylov subspace method. Lastly, we provide parallel performance results of both the SOR-like multisplitting method with preweighting and Krylov subspace method with the parallel preconditioner to evaluate parallel efficiency of the proposed methods.

• Korean Journal of Food Science and Technology
• /
• v.47 no.2
• /
• pp.246-253
• /
• 2015

In this study, we evaluated the lipoprotein lipase (LPL) inhibitory activity of 11 water extracts derived from Cinnamomum cassia Blume, Sarcodon aspratus, Cordyceps militaris, Crataegus pinnatifida Bunge, Corni fructus, Allium cepa, Coix lacryma-jobi, Plantago asiatica L., Lentinus edodes, Rosa rugosa, and Foeniculum fructus. The results of the LPL secretion and activity assay showed Sarcodon aspratus (NE) extract have an LPL secretion inhibitory acitivity. The cause of reduction in LPL secretion after NE treatment was investigated using molecular biology methods. NE treatment affected the LPL content in cells, but did not affect LPL mRNA expression. It also increased the mRNA expression level of sortilin-related receptor LDLR class A (SorLA), a receptor that induces endocytosis and intracellular trafficking of LPL. Finally, cell fractionation revealed that NE treatment induced the expression of CCAAT-enhancer-binding protein beta ($C/EBP{\beta}$), a SorLA transcription factor, in the nuclei of 3T3-L1 adipocytes. These results show that NE's anti-obesity effect involves inhibition of LPL secretion through $C/EBP{\beta}$-mediated induction of SorLA expression.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.6
• /
• pp.489-498
• /
• 2023

Advancements in hardware performance and computing technology have facilitated the progress of climate prediction models to address climate change. The Korea Meteorological Administration employs the GloSea6 model with supercomputer technology for operational use. Various universities and research institutions utilize the Low-GloSea6 model, a low-resolution coupled model, on small to medium-scale servers for weather research. This paper presents an analysis using Intel VTune Profiler on Low-GloSea6 to facilitate smooth weather research on small to medium-scale servers. The tri_sor_dp_dp function of the atmospheric model, taking 1125.987 seconds of CPU time, is identified as a hotspot. Nonlinear regression models, a machine learning technique, are applied and compared to existing functions conducting numerical operations. The K-Nearest Neighbors regression model exhibits superior performance with MAE of 1.3637e-08 and SMAPE of 123.2707%. Additionally, the Light Gradient Boosting Machine regression model demonstrates the best performance with an RMSE of 2.8453e-08. Therefore, it is confirmed that applying a nonlinear regression model to the tri_sor_dp_dp function during the execution of Low-GloSea6 could be a viable alternative.

• Information Systems Review
• /
• v.24 no.2
• /
• pp.67-88
• /
• 2022

This study proposed a research model that can explain the usage intentions of users and non-users by considering the performance aspects of personal mobility and external environmental factors based on the SOR (Stimulus-Organism-Response) model, A survey was conducted targeting domestic users and non-users, and research models and hypotheses were verified through Partial Least Square (PLS) and Artificial Neural Network (ANN). As a result of the analysis, it was confirmed that the users' perceived satisfaction and perceived trust had a positive effect on their intention to use, and that perceived risk and environmental value had a significant relationship with perceived satisfaction and perceived trust. For non-users, it was found that there was a positive correlation between perceived satisfaction and intention to use, and it was verified that perceived risk and environmental value, like users, were significant antecedents of perceived satisfaction and perceived trust. Among the remaining variables, the perceived mobility of users and the perceived ease of use of non-users were respectively presented as important influencing factors on perceived satisfaction.