• The Transactions of the Korea Information Processing Society
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• v.13 no.10
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• pp.574-578
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• 2024

JavaScript is slow for high-performance image processing in web browsers and cannot directly utilize the GPU. Therefore, web plugin technology or server-based processing methods have been used. However, since web plugins are no longer supported by the latest web browsers and server processing methods become increasingly expensive as the number of users grows. In this paper, an image processing acceleration method is proposed using the latest web standards such as WASM and WebGPU in a client environment, instead of plugins or server-based methods. The final experimental results confirmed that the WASM+WebGPU-based code, which utilizes both the CPU and GPU, improved execution performance by up to 10 times compared to traditional javaScript.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.8
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• pp.239-244
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• 2015

WebCL was proposed for high complex computing in Javascript. Since WebCL-based applications are distributed and executed on an unspecified number of general clients, it is important to profile their performances on different clients. Several profilers have been introduced to support various programming languages but WebCL profiler has not been developed yet. In this paper, we present a WebCL profiler to evaluate WebCL-based applications and monitor the status of GPU on which they run. This profiler helps developers know the execution time of applications, memory read/write time, GPU statues such as its power consumption, temperature, and clock speed.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.257-262
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• 2021

Providing web services to users has become expensive in recent times. For better web services, a web server is provided with high-performance technology. To achieve great web service experiences, tools such as general-purpose graphics processing units (GPGPUs), artificial intelligence, high-performance computing, and three-dimensional simulation are widely used. However, graphics processing units (GPUs) are used in high-speed operations and have limited general applications. In this study, we developed a task queue in a GPU to improve the performance of a web service using a multiprocessor and studied how to receive and process user requests in bulk. We propose the use of a GPGPU-based task queue to process user requests more than GPGPU based a central processing unit thread, and to process more GPU threads on task queue at about 136% to 233%, and proved that the proposed method is effective for web service.

• Electronics and Telecommunications Trends
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• v.31 no.4
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• pp.65-76
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• 2016

특정 제조사의 단말 또는 운영체제에 의존성이 없는 플랫폼 독립적인 웹은 높은 이식성, 소프트웨어의 재활용, 개발 생산성, 풍부한 개발자 존재, 유지 보수 면에서 장점을 가지나, 화려한 UI/UX를 제공하는 네이티브 응용에 비해 낮은 성능으로 웹 기반의 응용 개발 및 보급이 크게 활성화되지 못했다. 한편 데스크톱은 물론 모바일 단말의 멀티코어 기반 Graphic Processing Unit(GPU), CPU 탑재 등 HW 고사양화와 웹 응용에서도 HW 가속 기능을 활용할 수 있는 표준 제공으로 성능 제약을 극복할 수 있게 되었다. 본고에서는 GPU 발전동향을 살펴보고, 고속 렌더링 및 병렬 연산처리를 요구하는 웹 응용이 GPU기반 HW 가속 기능을 활용할 수 있는 크로노스 그룹의 그래픽 가속(Web Graphics Library: WebGL) 및 컴퓨팅(Web Computing Language: WebCL) 지원 표준 규격을 정리한다. 또한, 최근 차세대 GPU Application Programming Interface(API)로 발표된 Vulkan에 대해 알아보고, 웹 고속화 기술에 적용 가능성에 대해 전망한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.213-220
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• 2024

This paper proposes an optimization strategy for performing Federated Learning between devices and edge clouds using WebAssembly (WASM). The proposed strategy aims to maximize efficiency by conducting partial training on devices and the remaining training on edge clouds. Specifically, it mathematically describes and evaluates methods to optimize data transfer between GPU memory segments and the overlapping of computational tasks to reduce overall training time and improve GPU utilization. Through various experimental scenarios, we confirmed that asynchronous data transfer and task overlap significantly reduce training time, enhance GPU utilization, and improve model accuracy. In scenarios where all optimization techniques were applied, training time was reduced by 47%, GPU utilization improved to 91.2%, and model accuracy increased to 89.5%. These results demonstrate that asynchronous data transfer and task overlap effectively reduce GPU idle time and alleviate bottlenecks. This study is expected to contribute to the performance optimization of Federated Learning systems in the future.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.355-357
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• 2012

차세대 웹 브라우저는 멀티 쓰레드(multi-thread) 구조로 되어 있으며 HTML5와 WebGL을 기반으로 화려한 그래픽을 구사하기 때문에, 멀티 코어(multi-core) CPU와 GPU의 성능이 웹 브라우저의 성능에 큰 영향을 미치고 있다. 본 논문은 오픈 소스 웹 브라우저인 크로미엄(Chromium) 상에서 프로세서의 성능 변화에 따라 웹 브라우저에서 실행되는 웹 어플리케이션의 성능이 어떤 양상으로 변화하는지와 이 변화에 웹 브라우저의 각 동작이 얼마나 기여하는지를 비교 분석하였다. 그 결과 CPU 코어의 수가 렌더링 성능에 큰 영향을 주며, GPU의 성능은 WebGL의 성능을 크게 좌우함을 알 수 있었다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.27-35
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• 2015

Increasing the number of GPU (Graphic Processor Unit) cores, the studies on High Performance Computing Platform using GPU have actively been made in recent. This trend has led to the development of GPGPU (General Purpose GPU) and CUDA (Compute Unified Device Architecture) Framework. In this paper, we explain the many benefits of the GPU based system, and propose the ICIDF(Identify Compute-Intensive Data set and Function) methodology to apply GPU technology to legacy military information system for performance improvement. To demonstrate the efficiency of this methodology, we applied this method to AES CPU based program obtained from the Internet web site. Simply changing the data structure made improved the performance of AES program. As a result, the performance of AES based GPU program is improved gradually up to 10 times. Depending on the developer's ability, additional performance improvement can be expected. The problem to be solved is heat issue, but this problem has been much improved by the development of the cooling technology.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.9-16
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• 2011

GPU computing is emerging in high performance application area since it can easily exploit massive parallelism in a way of cost-effective computing. The power method which finds the eigen vector of a given matrix is widely used in various applications such as PageRank for calculating importance of web pages. In this research we made the power method efficiently parallelized on GPU and also suggested how it can be improved to enhance its performance. The power method mainly consists of matrix-vector product and it can be easily parallelized. However, it should decide the convergence of the eigen vector and need scaling of the vector subsequently. Such operations incur several calls to GPU kernels and data movement between host and GPU memories. We improved the performance of the power method by means of reduced calls to GPU kernels, optimized thread allocation and enhanced decision operation for the convergence.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.573-579
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• 2011

To meet the scalability and performance requirements of data analyses, which often involve voluminous data, efficient parallel or concurrent algorithms and frameworks are essential. We present a high-performance Korean morphological analyzer which employs the MapReduce framework on the graphics processing unit (GPU). MapReduce is a programming framework introduced by Google to aid the development of web search applications on a large number of central processing units (CPUs). GPUs are designed as a special-purpose co-processor. Their programming interfaces are typically formulated for graphics applications. Compared to CPUs, GPUs have greater computation power and memory bandwidth; however, GPUs are more difficult to program because of the design of their architectures. The performance of the Korean morphological analyzer using the MapReduce framework on the GPU is evaluated in comparison with the CPU-based model. The proposed Korean Morphological analyzer shows promising scalable performance on distributed computing with the GPU.

• Annual Conference of KIPS
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• 2023.05a
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• pp.769-770
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• 2023

최근 고성능 웹 애플리케이션 개발을 위한 asm.js. WebAssembly, WebGL, WebGPU와 같은 여러 웹 고속화 기술들이 발표되며 확장되고 있다. 하지만 각 기술들은 개별적으로만 적용 가능하다는 한계점이 있었다. 따라서 본 논문에서는 웹 브라우저 환경에서 최적화된 실행 성능을 기대할 수 있는 다중 웹 고속화 기술들을 통합 한 실행파일 포맷 및 패키징 방안에 대해 제안하고자 한다.