• International journal of advanced smart convergence
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• v.6 no.1
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• pp.26-31
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• 2017

When mobile navigator device accesses data randomly, the cache memory performance is rapidly deteriorated due to low memory access locality. For instance, GPS (General Positioning System) of navigator program for automobiles or drones, that are currently in common use, uses data from 32 satellites and computes current position of a receiver. This computation of positioning is the major part of GPS which accounts more than 50% computation in the program. In this computation task, the satellite signals are received in real time and stored in buffer memories. At this task, since necessary data cannot be sequentially stored, the data is read and used at random. This data accessing patterns are generated randomly, thus, memory system performance is worse by low data locality. As a result, it is difficult to process data in real time due to low data localization. Improving the low memory access locality inherited on the algorithms of conventional communication applications requires a certain optimization technique to solve this problem. In this study, we try to do optimizations with data and memory to improve the locality problem. In experiment, we show that our case study can improve processing speed of core computation and improve our overall system performance by 14%.

• Convergence Security Journal
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• v.13 no.4
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• pp.19-25
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• 2013

The increasing demand for fast, flexible and guaranteed Quality of Service (QoS) in core networks has caused to deploy MultiProtocol Label Switching (MPLS) and Generalized MPLS (GMPLS) control plane. In GMPLS control plane, path computation and cooperation processes are one of the crucial element to maintain an acceptable level of service. The Internet Engineering Task Force (IETF) has proposed the Path Computation Element (PCE) architecture. The PCE is a dedicated network element devoted to path computation process and communications between Path Computation Clients (PCC) and PCEs is realized through the PCE Protocol (PCEP). This paper examines the PCE-based path computation architecture to include the design and implementation of PCEP. The functional modules including Finite State Machine (FSM) and related key design issues of each state are presented. In particular we also discuss internal/external protocol interfaces that efficiently control the communication channels.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.347-353
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• 2022

In this paper, we propose a method that performs a text-video retrieval model by replacing video properties using captions. In general, the exisiting embedding-based models consist of both joint embedding space construction and the CNN-based video encoding process, which requires a lot of computation in the training as well as the inference process. To overcome this problem, we introduce a video-captioning module to replace the visual property of video with captions generated by the video-captioning module. To be specific, we adopt the caption generator that converts candidate videos into captions in the inference process, thereby enabling direct comparison between the text given as a query and candidate videos without joint embedding space. Through the experiment, the proposed model successfully reduces the amount of computation and inference time by skipping the visual processing process and joint embedding space construction on two benchmark dataset, MSR-VTT and VATEX.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.188-196
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• 2022

Recently, neural architecture search (NAS) has received increasing attention as it can replace human experts in designing the architecture of neural networks for different tasks and has achieved remarkable results in many challenging tasks. In this study, a path-based computation neural architecture encoder (PCE) was proposed. Our PCE first encodes the computation of information on each path in a neural network, and then aggregates the encodings on all paths together through an attention mechanism, simulating the process of information computation along paths in a neural network and encoding the computation on the neural network instead of the structure of the graph, which is more consistent with the computational properties of neural networks. We performed an extensive comparison with eight encoding methods on two commonly used NAS search spaces (NAS-Bench-101 and NAS-Bench-201), which included a comparison of the predictive capabilities of performance predictors and search capabilities based on two search strategies (reinforcement learning-based and Bayesian optimization-based) when equipped with different encoders. Experimental evaluation shows that PCE is an efficient encoding method that effectively ranks and predicts neural architecture performance, thereby improving the search efficiency of neural architectures.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.68-70
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• 1996

In this paper, an efficient parallel computation method for solving large sparse systems of linear algebraic equations by using Cholesky's method in the finite element method is studied. The methods of minimizing the number of fill-ins in the factorization process of factorization are investigated for minimizing the amount of memory and computation time. The parallel programming is implemented under the PVM(Parallel Virtual Machine) environment. The method of load-distribution is studied for minimizing the computation time and the communication time.

• MALSORI
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• no.51
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• pp.71-84
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• 2004

In this paper, we propose the automatic speech database verification method(or called automatic verification) based on confidence measure for a large speech database. This method verifies the consistency between given transcription and speech using the confidence measure. The automatic verification process consists of two stages : the word-level likelihood computation stage and multi-level likelihood ratio computation stage. In the word-level likelihood computation stage, we calculate the word-level likelihood using the viterbi decoding algorithm and make the segment information. In the multi-level likelihood ratio computation stage, we calculate the word-level and the phone-level likelihood ratio based on confidence measure with anti-phone model. By automatic verification, we have achieved about 61% error reduction. And also we can reduce the verification time from 1 month in manual to 1-2 days in automatic.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.596-605
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• 2001

In this paper we propose a method, called the range-based cube partitioning (RCP)method for reducing I/O cost of cube computation in OLAP The method improves I/O performance of cube partitioning process by overlapping some computation between partitioning stages. For overlapping the computation, the method partitions the cube based on the ranges of attribute values, not the points of attribute value, Through analysis any experiments, we show the performance of the proposed method with comparison of the previous cube partitioning method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3482-3497
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• 2021

Artificial intelligence has emerged as the core of the 4th industrial revolution, and large amounts of data processing, such as big data technology and rapid data analysis, are inevitable. The most fundamental and universal data interpretation technique is an analysis of information through regression, which is also the basis of machine learning. Ridge regression is a technique of regression that decreases sensitivity to unique or outlier information. The time-consuming calculation portion of the matrix computation, however, basically includes the introduction of an inverse matrix. As the size of the matrix expands, the matrix solution method becomes a major challenge. In this paper, a new algorithm is introduced to enhance the speed of ridge regression estimator calculation through series expansion and computation recycle without adopting an inverse matrix in the calculation process or other factorization methods. In addition, the performances of the proposed algorithm and the existing algorithm were compared according to the matrix size. Overall, excellent speed-up of the proposed algorithm with good accuracy was demonstrated.

• Smart Media Journal
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• v.12 no.3
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• pp.68-76
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• 2023

Emerging mobile edge computing (MEC) can be used in battery-constrained Internet of things (IoT). The execution latency of IoT applications can be improved by offloading computation-intensive tasks to an MEC server. Recently, the popularity of unmanned aerial vehicles (UAVs) has increased rapidly, and UAV-based MEC systems are receiving considerable attention. In this paper, we propose a dynamic computation offloading paradigm for UAV-based MEC systems, in which a UAV flies over an urban environment and provides edge services to IoT devices on the ground. Since most IoT devices are energy-constrained, we formulate our problem as a Markov decision process considering the energy level of the battery of each IoT device. We also use model-free Q-learning for time-critical tasks to maximize the system utility. According to our performance study, the proposed scheme can achieve desirable convergence properties and make intelligent offloading decisions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.812-815
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• 2005

The incremental forming process employs several tens or hundreds of continuous local strokes, so the entire process is difficult to analyze due to much computation time and large computer memory. The objective of this work is to propose a new numerical scheme of the finite element method, automatic expansion of domain (AED), and to reduce computation time and computer memory. In the AED scheme, an effective analysis domain in each local forming step is defined and then the domain is automatically expanded in accordance with the repeated process. In order to verify the validity of the criterion for the AED scheme and the applicability of the AED scheme, two-dimensional incremental plane-strain forging process is first analyzed using the proposed scheme with various criteria and full domain. In addition, three-dimensional incremental radial forging process is analyzed to verify the applicability of the proposed scheme to a practical incremental forging process.