• Journal of Computing Science and Engineering
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• v.6 no.4
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• pp.287-293
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• 2012

We introduce a methodology for the study of the application-level performance of time-sharing parallel jobs on a set of compute nodes in high performance clusters and report our findings. We assume that parallel jobs arriving at a cluster need to share a set of nodes with the jobs of other users, in that they must compete for processor time in a time-sharing manner and other limited resources such as memory and I/O in a space-sharing manner. Under the assumption, we developed a methodology to simulate job arrivals to a set of compute nodes, and gather and process performance data to calculate the percentage slowdown of parallel jobs. Our goal through this study is to identify a better combination of jobs that minimize performance degradations due to resource sharing and contention. Through our experiments, we found a couple of interesting behaviors for overlapped parallel jobs, which may be used to suggest alternative job allocation schemes aiming to reduce slowdowns that will inevitably result due to resource sharing on a high performance computing cluster. We suggest three job allocation strategies based on our empirical results and propose further studies of the results using a supercomputing facility at the San Diego Supercomputing Center.

• The Research Journal of the Costume Culture
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• v.17 no.1
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• pp.177-188
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• 2009

SCM as the important marketing strategy enhance the firm's efficiency and compatibility in global market environment such as global outsourcing. Firms adopted SCM realized the need to evaluate precisely the performance of SCM. In spite of importance of SCM, there was not much intention and research to measure SCM performance in textile fashion industry. Therefore, the purpose of this case study was to measure performance of supply chain management in textile fashion business using BSC(Balanced Score Card) to measure not only financial perspective but also non-financial perspectives such as customer perspective, internal business perspectives, financial perspective, and innovation & learning perspective. The questionnaire developed by the reviews of the literature was adopted for this study. The results of this study showed that SCM performance was enhanced from the point of customer perspective(cost, quality, time, service), financial perspective(cash cycle time, inventory turn over, inventory obsolescence, return on asset, return on investment, capacity utilization), and innovation & learning perspective(cost for human resource management, service for human resources). But there was same performance level regarding internal business perspective(lead time, cost for manufacturing process, product quality control, productive flexibility for time, quantity, and variety). Therefore, we should keep close relationship and two way communication among supply chain members to promote better SCM performance.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.7
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• pp.377-392
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• 2005

A lot of studies to measure and analyze the system performance have been done in areas such as system modeling, performance measurement, monitoring, and performance prediction since the advent of a computer system. Studies on a framework to unify the performance related areas have rarely been performed although many studies in the various areas have been done, however. In the case of TMO(Time-Triggered Message-Triggered Object), a real-time programming model, it hardly provides tools and frameworks on the performance except a simple run-time monitor. So it is difficult to analyze the performance of the real-time system and the process based on TMO. Thus, in this paper, we propose a framework for the dynamic analysis of the real-time system based on TMO, TDAF(TMO based Dynamic Analysis Framework). TDAF treats all the processes for the performance measurement and analysis, and Provides developers with more reliable information systematically combining a load model, a performance model, and a reporting model. To support this framework, we propose a load model which is extended by applying TMO model to the conventional one, and we provide the load calculation algorithm to compute the load of TMO objects. Additionally, based on TMO model, we propose performance algorithms which implement the conceptual performance metrics, and we present the reporting model and algorithms which can derive the period and deadline for the real-time processes based on the load and performance value. In last, we perform some experiments to validate the reliability of the load calculation algorithm, and provide the experimental result.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.4
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• pp.163-170
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• 2014

A pseudolite is used as a GPS backup system, and is also used for the purpose of indoor navigation and correction information transmission. It is installed on the ground, and transmits signals that are similar to those of a GPS satellite. In addition, in recent years, studies on the improvement of positioning accuracy using the pseudorange measurement of a pseudolite have been performed. As for the effect of the time synchronization error between a pseudolite and a GPS satellite, a time synchronization error of 1 us generally induces a pseudorange error of 300 m; and to achieve meter-level positioning, ns-level time synchronization between a pseudolite and a GPS satellite is required. Therefore, for the operation of a pseudolite, a time synchronization algorithm between a GPS satellite and a pseudolite is essential. In this study, for the time synchronization of a pseudolite, "a pseudolite time synchronization method using the time source of UTC (KRIS)" and "a time synchronization method using a GPS timing receiver" were introduced; and the time synchronization performance depending on the pseudolite time source and reference time source was evaluated by designing a software-based pseudolite time synchronization performance evaluation simulation platform.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.21-25
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• 2005

Human performance of system control under excessive mental-workload may differ from stable situation. In this study, design guidelines of secondary control system were introduced to enhance performance of safety control system. Under urgent situation, the first performance criterion is not a reaction time but safe control reaction that prevents system disaster. Therefore it is important to find out the facts that are mainly related system safety. Experimental results show performance of primary task didn't reflect whole system influence within a limited short reaction time. In this situation, the secondary task is more sensitive to system influence that varied with some factors of urgent status. Therefore, when a system proceeds to abnormal and unsafe status, and even more the reaction time is limited within a very short time to control the system, the estimation of human performance is more sensitive using secondary task performance then primary task performance. Those results mean it is required to develop various secondary tasks to design safety control systems preventing disaster, And also require many studies of estimation methods human performances especially when system status varies dangerous and/or unsafe situation.

• Journal of Computing Science and Engineering
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• v.9 no.4
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• pp.177-189
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• 2015

High-performance processors using Non-Uniform Cache Architecture (NUCA) are increasingly used to deal with the growing wire delays in multicore/manycore processors. Due to the convergence of high-performance computing with embedded computing, NUCA caches are expected to benefit high-end embedded systems as well. However, for real-time systems that use multicore processors with NUCA caches, it is crucial to bound worst-case execution time (WCET) accurately and safely. In this paper, we developed a WCET analysis approach by considering the effect of static NUCA caches on WCET. We compared the WCET in real-time applications with different topologies of static NUCA caches. Our experimental results demonstrated that the static NUCA cache could improve the worst-case performance of realtime applications using multicore processor compared to the cache with uniform access time.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.375-378
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• 1996

Robot control software is a hard real-time system that must output the planned trajectory points within an explicit short time period. In this paper, we present a design and implementation method for robot control software using commercial real-time operating systems, RTKemel 4.5. Therefore, various robot motions, efficient user interface, and system failure check are easily implemented by using multitasking function, intertask communication mechanism, and real-time runtime libraries of RTKernel. The performance analysis of commercial real-time operating system for robot control is presented based on Timed Petri net(TPN) and we can use these results to design an optimal system.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.97-99
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• 2009

Bilateral teleoperation systems, connected to computer networks such as Internet have to deal with the time delay varying depending on factors such as congestion, bandwidth or distance. And the entire system is easy to become unstable due to irregular time delay. Passivity concept has been using as a framework to solve the stability problem in bilateral control of teleoperation. Acontrol scheme for teleoperation systems with varying time delay is proposed based on a passivity concept is proposed in this paper. One approach makinguse of the characteristic impedances is proposed to achieve a passive control. Since passive control does not mean that the system performance will be acceptable, another transmission scheme which focuses on both the passive feature and the acceptable performance is configured for varying time delay in this paper. The tracking performance has been proved through the computer simulation for varying time delay bilateral teleoperation system using Matlab Simulink.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.199-199
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• 2000

Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.82-89
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• 2023

Various machine-learning models may yield high predictive power for massive time series for time series prediction. However, these models are prone to instability in terms of computational cost because of the high dimensionality of the feature space and nonoptimized hyperparameter settings. Considering the potential risk that model training with a high-dimensional feature set can be time-consuming, we evaluate a feature-importance-based feature selection method to derive a tradeoff between predictive power and computational cost for time series prediction. We used two machine learning techniques for performance evaluation to generate prediction models from a retail sales dataset. First, we ranked the features using impurity- and Local Interpretable Model-agnostic Explanations (LIME) -based feature importance measures in the prediction models. Then, the recursive feature elimination method was applied to eliminate unimportant features sequentially. Consequently, we obtained a subset of features that could lead to reduced model training time while preserving acceptable model performance.