• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.13 no.1
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• pp.13-20
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• 2009

The IPSAP which is a finite element analysis program has been developed for high parallel performance computing. This program consists of various analysis modules - stress, vibration and thermal analysis module, etc. The M orthogonal block Lanczos algorithm with shiftinvert transformation is used for solving eigenvalue problems in the vibration module. And the multifrontal algorithm which is one of the most efficient direct linear equation solvers is applied to factorization and triangular system solving phases in this block Lanczos iteration routine. In this study, the performance enhancement procedures of the IPSAP are composed of the following stages: 1) communication volume minimization of the factorization phase by modifying parallel matrix subroutines. 2) idling time minimization in triangular system solving phase by partial inverse of the frontal matrix and the LCM (least common multiple) concept.

• Speech Sciences
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• v.11 no.4
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• pp.53-66
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• 2004

The nonlinear speech enhancement method with interactive parallel-extended Kalman filter is applied to speech contaminated by additive white noise. To represent the nonlinear and nonstationary nature of speech. we assume that speech is the output of a nonlinear prediction HMM (NPHMM) combining both neural network and HMM. The NPHMM is a nonlinear autoregressive process whose time-varying parameters are controlled by a hidden Markov chain. The simulation results shows that the proposed method offers better performance gains relative to the previous results [6] with slightly increased complexity.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.12
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• pp.439-446
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• 2016

In this paper, an efficient prediction accuracy enhancement strategy is proposed for improving the performance of the prediction-based parallel event-driven gate-level timing simulation. The proposed new strategy adopts the static double prediction and the dynamic prediction for input and output values of local simulations. The double prediction utilizes another static prediction data for the secondary prediction once the first prediction fails, and the dynamic prediction tries to use the on-going simulation result accumulated dynamically during the actual parallel simulation execution as prediction data. Therefore, the communication overhead and synchronization overhead, which are the main bottleneck of parallel simulation, are maximally reduced. Throughout the proposed two prediction enhancement techniques, we have observed about 5x simulation performance improvement over the commercial parallel multi-core simulation for six test designs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.666-672
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• 2016

Recently the fingerprint is widely used as one of biometrics to improve the security of financial mobile applications, because of its user convenience and high recognition rate. However, in order to apply fingerprint algorithms to finance and security applications, the recognition rate and processing speed of the fingerprint algorithms have to be improved further. In this paper, we propose the parallel fingerprint enhancement algorithm on general-purpose computing on graphics processing unit (GPGPU) using OpenCL. We discuss the analysis of the parallelism in the fingerprint algorithm as well as the exploration of optimization parameters of the parallel fingerprint algorithm to improve the performance. The experimental results showed that the execution of parallel fingerprint enhancement algorithm on GPGPUs was accelerated from 29.4 upto 69.2 times compared with the execution of the original one on the host CPUs.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.05a
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• pp.353-356
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• 2010

A computational study on the enhancement of parallel supersonic-subsonic mixing wakes is conducted and compared with available experimental data. The first aim of the present work is to show a direct comparison between numerical predictions and equivalent experimental data for the baseline case. The Pitot pressure distribution data are in good agreement between computation and experiment, and the results show that Menter's SST model with the compressibility correction gives the best performance. Further we investigate the effects of primary parameters such as the position of the cavity, and the arrangement of the cavity at the given flow condition.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.8
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• pp.797-802
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• 2012

In this study, the potential performance enhancement in a dual heat pump system through series operation was investigated by a comparison between the performance for parallel and series operation for a heating supply temperature of $60^{\circ}C$. To compare the performance of each configuration fairly, the heat transfer surface area of the heat exchangers was fixed. The inlet temperatures and the flow rates of the heat source and the load were also fixed. In addition, the heat transfer and pressure drop characteristics of the working fluids were considered to achieve a more realistic comparison. The results show that the heating coefficient of performance (COP) of the series configuration is approximately 5% higher than that of the parallel configuration under the simulation conditions considered in the present study.

• Journal of the Korea Society for Simulation
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• v.3 no.2
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• pp.15-25
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• 1994

Efficient event evaluation and propagation techniques are proposed to enhance the advancement of simulation clocks of conservative and optimistic logic simulation protocols on parallel processing environments. The first idea of the techniques proposed in this paper is to allow more than one event evaluation per simulation cycle and to pack more than one propagation event in a single message. The second idea is to use advancement windows resulted in good performance in parallelism and execution times.

• Speech Sciences
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• v.14 no.2
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• pp.115-126
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• 2007

There have been many research efforts to improve the performance of the speech recognizer in noisy conditions. Among them, the model compensation method and the speech enhancement approach have been used widely. In this paper, we propose to combine the two different approaches to further enhance the recognition rates in the noisy speech recognition. For the speech enhancement, the minimum mean square error-short time spectral amplitude (MMSE-STSA) has been adopted and the parallel model combination (PMC) and Jacobian adaptation (JA) have been used as the model compensation approaches. From the experimental results, we could find that the hybrid approach that applies the model compensation methods to the enhanced speech produce better results than just using only one of the two approaches.

• 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.

• Spatial Information Research
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• v.17 no.3
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• pp.371-379
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• 2009

Recently, GPU (Graphics Processing Unit) has been improved rapidly on the need of speed for gaming. As a result, GPU contains multiple ALU (Arithmetic Logic Unit) for parallel processing of a lot of graphics data, such as transform, ray tracing, etc. Therefore, this paper proposed a technique for parallel processing of spatial data using GPU. Spatial data consists of multiple coordinates, and each coordinate contains value of x and y axis. To display spatial data graphics operations have to be processed to large amount of coordinates. Because the graphics operation is identical and coordinates are multiple data, SIMD (Single Instruction Multiple Data) parallel processing of GPU can be used for processing of spatial data to improve performance. This paper implemented SIMD parallel processing of spatial data using two kinds of SDK (Software Development Kit). CUDA and ATI Stream are used for NVIDIA and ATI GPU respectively. Experiments that measure time of calculation for graphics operations are carried out to observe enhancement of performance. Experimental result is reported that proposed method can enhance performance up to 1,162% for graphics operations. The proposed method that uses parallel processing with GPU for spatial data can be generally used to enhance performance for applications which deal with large amount of spatial data.