• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.1
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• pp.21-27
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• 2016

An integrated display software platform for small UAV is developed based on parallel processing technique in this paper. When the small UAV with high-performance camera and avionic modules is employed to various surveillance-related missions, it is important to reduce the operator's workload and increase the monitoring efficiency. For this purpose, it is needed to develop an efficient monitoring software enable to manipulate the image and flight data obtained during flight within the given processing time and display them simultaneously. In this paper, we set up requirements and suggest the architecture for the software platform. The integrated software platform is implemented with parallel processing scheme. Based on AR drone, we verified that the various data are concurrently displayed by the suggest software platform.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2561-2564
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• 2003

Data mining is an effective method of the discovery of useful information such as rules and previously unknown patterns existing in large databases. The discovery of association rules is an important data mining problem. We have developed a new parallel mining called Distributed Frequent Pattern Tree (abbreviated by DFPT) algorithm on a distributed shared nothing parallel system to detect association rules. DFPT algorithm is devised for parallel execution of the FP-growth algorithm. It needs only two full disk data scanning of the database by eliminating the need for generating the candidate items. We have achieved good workload balancing throughout the mining process by distributing the work equally to all processors. We implemented the algorithm on a PC cluster system, and observed that the algorithm outperformed the Improved Count Distribution scheme.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.157-162
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• 2005

Parallel implementation and performance assessment of the grid assembly in a structured chimera grid approach is studied. The grid assembly process, involving hole cutting and searching donor, is parallelized on the PC cluster. A message passing programming model based on the MPI library is implemented using the single program multiple data(SPMD) paradigm. The coarse-grained communication is optimized with the minimized memory allocation because that the parallel grid assembly can access the decomposed geometry data in other processors by only message passing in the distributed memory system such as a PC cluster. The grid assembly workload is based on the static load balancing tied to flow solver. A goal of this work is a development of parallelized grid assembly that is suited for handling multiple moving body problems with large grid size.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.10
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• pp.337-342
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• 2015

We develop a new parallelization method for Sieve of Eratosthenes algorithm, which enhances both computation speed and energy efficiency. A pipeline scheduling is included for better load balancing after proper workload partitioning. They run on multicore CPUs with hybrid parallel programming model which uses both message passing and multithreading computation. Experimental results performed on both small scale clusters and a PC with a mobile processor show significant improvement in execution time and energy consumptions.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.823-835
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• 2019

Purpose: This study deals with a production planning and scheduling problem to minimize the total weighted tardiness on hybrid flow shop with sets of non-identical parallel machines on stages, where parallel machines in the set are dedicated to perform specific subsets of jobs and sequence-dependent setup times are also considered. Methods: A two-stage approach, that applies MILP model in the 1st stage and dispatching rules in the 2nd stage, is proposed in this paper. The MILP model is used to assign jobs to a specific machine in order to equalize the workload of the machines at each stage, while new dispatching rules are proposed and applied to sequence jobs in the queue at each stage. Results: The proposed two-stage approach was implemented by using a commercial MILP solver and a commercial simulation software and a case study was developed based on the spark plug manufacturing process, which is an automotive component, and verified using the company's actual production history. The computational experiment shows that it can reduce the tardiness when used in conjunction with the dispatching rule. Conclusion: This proposed two-stage approach can be used for HFS systems with dedicated machines, which can be evaluated in terms of tardiness and makespan. The method is expected to be used for the aggregated production planning or shop floor-level production scheduling.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.439-446
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• 2001

The main stream of parallel programming today is using synchronous algorithms, where processor synchronization for correct computation and workload balance are essential. Overall performance of the whole system is dependent upon the performance of the slowest processor, if workload is not well-balanced or heterogeneous clusters are used. Asynchronous iteration is a way to mitigate such problems, but most of the works done so far are for shared memory systems. In this paper, we suggest and implement a parallel large sparse linear system solver that improves performance on distributed memory systems like clusters by reducing processor idle times as much as possible by asynchronous iterations.

• Journal of the Ergonomics Society of Korea
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• v.28 no.2
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• pp.9-16
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• 2009

The aim of this study was to evaluate the effects of the driving performance and workload according to changing driving environment and types of steering wheel. Twelve drivers who participated in this study consisted of two groups; six Japanese as the left-lane drivers who was accustomed to driving on left-hand side of the road, and six Europeans, Americans, and Korean as the right-lane drivers who was accustomed to driving on right-hand side of the road. They were asked to operate a driving simulator while using two different types of steering wheel (for the left-hand side driving and the right-hand side driving). During the experiment, a range of data were measured including driving performance, mental workload, and eye movements which were recorded in order to identify the amount of time looking towards the in-vehicle route guidance. Results indicated that the use of the steering wheel by parallel moving led to increase high attentional demand and worse glance behavior to traffic signs for the left-lane drivers. In the case of the right-lane drivers, the effects by changing driving direction were more effective than the types of steering wheel due to their habit or traits.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.411-422
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• 2002

Recently, there have been active researches about the VPCS (Virtual Parallel Computing System) based on multiple agents. The PVCS uses personal computers or workstations that are dispersed all over the internet, rather than a high-cost supercomputer, to solve complex problems that require a huge number of calculations. It can be made up with either homogeneous or heterogeneous computers, depending on resources available on the internet. In this paper, we propose a new method in order to distribute worker agents and work packages efficiently on the VPCS based on the IBM Aglets. The previous methods use mainly the master-slave pattern for distributing worker agents and work packages. However, in these methods the workload increases dramatically at the central master as the number of agents increases. As a solution to this problem, our method appoints worker agents to distribute worker agents and workload packages. The proposed method is evaluated in several ways on the VPCS, and its results are improved to be worthy of close attention as compared with the previous ones.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.8
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• pp.245-252
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• 2015

Recently, parallel processing methods with accelerator have been introduced into a high performance computing and a mobile computing. The photomosaic application can be parallelized by using inherent data parallelism and accelerator. In this paper, we propose a way to distribute the workload of the photomosaic application into a CPU and GPU heterogeneous computing environment. That is, the photomosaic application is parallelized using both CPU and GPU resource with the asynchronous mode of OpenCL, and then the optimal workload distribution rate is estimated by measuring the execution time with CPU-only and GPU-only distribution rates. The proposed approach is simple but very effective, and can be applied to parallelize other applications on a CPU and GPU heterogeneous computing environment. Based on the experimental results, we confirm that the performance is improved by 141% into a heterogeneous computing environment with the optimal workload distribution compared with using GPU-only method.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.483-486
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• 1998

In parallel system, the execution times of tasks cannot be accurately estimated and tasks may arrive at any time. In case, processors are overweighted with workload, the system utilization deteriorates. To solve this problem, dynamic load balancing that rearranges tasks in overloaded processors is required. We prospose the improved dynamic load balancing algorithm for $\textsc{k}-ary$ n-cubes using the property of ring and MWA which is the dynamic load balancing one for mesh. The proposed algorithm which uses the global load information has less communication cost than GDE, DDE and load difference within 1.