• Journal of KIISE:Computing Practices and Letters
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• v.16 no.7
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• pp.775-787
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• 2010

Unlike general-purpose CPUs, the GPUs have been specialized as many-core streaming processors, and are frequently replacing the CPUs in an increasing range of computations thanks to their outstanding parallel computing capacity. In order to respond to such trend, NVIDIA has recently issued a new parallel computing architecture called CUDA(Compute Unified Device Architecture), offering a flexible GPU programming environment for GPGPU(General Purpose GPU) computing. In general, when programmers use the CUDA API, they should clearly understand many aspects of GPU's computing architecture to produce efficient parallel software. In this article, we explain several optimization techniques for CUDA programming that we have verified through a lot of experiment and trial and error, and review how those techniques affect the performance of code execution. In particular, we use a specific problem as an example to analyze several elements that affect performances, such as effective accesses to hierarchical memory system, processor occupancy, and latency hiding. In conclusion, we present several directions that may be utilized effectively in CUDA-based parallel programming.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.75-84
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• 2014

In order to solve the problems such as overload, single point of failure, non-optimized data path, and network scalability in conventional central mobility management protocols, distributed mobility management schemes have been continually studied in and around the IETF. In this paper, a network-based partially-distributed mobility management mechanism, pDMMv6, is suggested and the performance comparison with traditional protocols such as PMIPv6 and MIPv6 is made through simulation under the various user traffic environment. The simulation results include UDP packet delivery ratio, end-to-end packet delay, binding delay for registration signaling, CPU utilization in each node, and response delays in several server-client TCP applications such as web browsing, e-mail, telnet remote login, FTP file up/down-load, and database access.

• Journal of the Korea Society of Computer and Information
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• v.15 no.7
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• pp.75-81
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• 2010

In this paper, we propose an emotion messenger which recognizes face or hand gestures of a user using a WebCAM, converts recognized emotions (joy, anger, grief, happiness) to flash-cones, and transmits them to the counterpart. This messenger consists of face recognition module, hand gesture recognition module, and messenger module. In the face recognition module, it converts each region of the eye and the mouth to a binary image and recognizes wink, kiss, and yawn according to shape change of the eye and the mouth. In hand gesture recognition module, it recognizes gawi-bawi-bo according to the number of fingers it has recognized. In messenger module, it converts wink, kiss, and yawn recognized by the face recognition module and gawi-bawi-bo recognized by the hand gesture recognition module to flash-cones and transmits them to the counterpart. Through simulation, we confirmed that CPU share ratio of the emotion messenger is minimized. Moreover, with respect to recognition ratio, we show that the hand gesture recognition module performs better than the face recognition module.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.1-9
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• 2010

Generally, dynamic hand gesture recognition is formed through preprocessing step, hand tracking step and hand shape detection step. In this paper, we present advanced dynamic hand gesture recognizing method that improves performance in preprocessing step and hand shape detection step. In preprocessing step, we remove noise fast by using dynamic table and detect skin color exactly on complex background for controling skin color range in skin color detection method using YCbCr color space. Especially, we increase recognizing speed in hand shape detection step through detecting Start Image and Stop Image, that are elements of dynamic hand gesture recognizing, using Guideline. Guideline is edge of input hand image and hand shape for comparing. We perform various experiments with nine web-cam video clips that are separated to complex background and simple background for dynamic hand gesture recognition method in the paper. The result of experiment shows similar recognition ratio but high recognition speed, low cpu usage, low memory usage than recognition method using learning exercise.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.1-8
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• 2024

In the API gateway, API composition is an essential function that can reduce the number of client calls and prevent over-fetching and under-fetching. API composition that operate with IMJ (In-Memory Join) consume a lot of resources, putting a burden on the performance of the API gateway. In this paper, to improve the problem of IMJ-style API composition, we propose SAPIC (Stream-based API Composition), which delivers the data to be composed to the client by streaming. SAPIC calls each MSA API that makes up the client response data and immediately streams the received response data to the client, reducing the resource consumption of the API gateway and providing faster response time compared to IMJ. As a result of a comparison experiment with GraphQL, a representative API combination technology, SAPIC recorded a maximum CPU occupancy rate of approximately 21 to 70 % lower, a maximum heap usage rate of approximately 16 to 74 % lower, and a throughput rate that was 1 to 2.3 times higher than GraphQL.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.