• Journal of Computing Science and Engineering
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• v.9 no.1
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• pp.20-28
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• 2015

General purpose computing applications have not yet been thoroughly explored in procedure level speculation, especially in the light-weighted profiling way. This paper proposes a light-weighted profiling mechanism to analyze speculative parallelism characterization in several classic general purpose computing applications from SPEC CPU2000 benchmark. By comparing the key performance factors in loop and procedure-level speculation, it includes new findings on the behaviors of loop and procedure-level parallelism under these applications. The experimental results are as follows. The best gzip application can only achieve a 2.4X speedup in loop level speculation, while the best mcf application can achieve almost 3.5X speedup in procedure level. It proves that our light-weighted profiling method is also effective. It is found that between the loop-level and procedure-level TLS, the latter is better on several cases, which is against the conventional perception. It is especially shown in the applications where their 'hot' procedure body is concluded as 'hot' loops.

• Smart Media Journal
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• v.3 no.1
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• pp.33-38
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• 2014

Even though the performance of microprocessor is improved continuously, the performance improvement of computing system becomes hard to increase, in order to some drawbacks including increased power consumption. To solve the problem, general-purpose computing on graphics processing units(GPGPUs), which execute general-purpose applications by using specialized parallel-processing device representing graphics processing units(GPUs), have been focused. However, the characteristics of applications related with graphics is substantially different from the characteristics of general-purpose applications. Therefore, GPUs cannot exploit the outstanding computational resources sufficiently due to various constraints, when they execute general-purpose applications. When designing GPUs for GPGPU, memory system is important to effectively exploit the GPUs since typically general-purpose applications requires more memory accesses than graphics applications. Especially, external memory access requiring long latency impose a big overhead on the performance of GPUs. Therefore, the GPU performance must be improved if hierarchical memory architecture which can reduce the number of external memory access is applied. For this reason, we will investigate the analysis of GPU performance according to hierarchical cache architectures in executing various benchmarks.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.1043-1061
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• 2013

Recent advances in computer technology introduce massive data and their analysis becomes important. The high performance computing is one of the most essential part in analysis of massive data. In this paper, we review the general purpose of the graphics processing unit and its application to parallel computing, which has been of great interest in statistics communities.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.480-483
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• 1997

A fossil power plant can be modeled by a lot of algebraic equations and differential equations. When we simulate a large, complicated fossil power plant by a computer such as workstation or PC, it takes much time until overall equations are completely calculated. Therefore, new processing systems which have high computing speed is ultimately needed to develope real-time simulators. Vital points of real-time simulators are accuracy, computing speed, and deadline observing. In this paper, we present a enhanced strategy in which we can provide powerful computing power by parallel processing of DSP processors with communication links. We designed general purpose DSP modules, and a VME interface module. Because the DSP module is designed for general purpose, we can easily expand the parallel system by just connecting new DSP modules to the system. Additionally we propose methods about downloading programs, initial data to each DSP module via VME bus, DPRAM and processing sequences about computing and updating values between DSP modules and CPU30 board when the simulator is working.

• 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.

• Journal of the Ergonomics Society of Korea
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• v.24 no.1
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• pp.43-46
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• 2005

The future information technologies and service paradigm will move from PC, the general purpose desktop computing environment, to the next-generation PC that provides information any where, any time, and any device. The next-generation PC such as wearable computers are specialized to the human-centric functionalities and always-on connected services. In this study, service infrastructure of wearable computing with WBAN(Wearable Body Area Network) was suggested for the ubiquitous computing environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.674-680
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• 2008

An SDR (Software Defined Radio) system based on general purpose computing platform has benefits of ease of software development process, high degree of software compatibility, and cost-effectiveness of general purpose processors. This paper discusses design and implementation of a dual-mode SDR system that supports both cordless phone and walkie-talky system running on Linux-based general purpose computing platform. For this purpose, we designed modulation and demodulation software on open source-based GNU radio middleware. We also designed a customized RF front-end hardware which performs frequency conversion between RF and IF. The proposed SDR system successfully exhibited its ability to operate both cordless phone and walkie-talky communication on Intel processor-based general purpose computing platform. But experience with the prototype SDR system shows that further research is required for run-time software reconfiguration and efficient integration with conventional TCP/IP protocol stacks.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1784-1787
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• 2010

General Purpose Graphic Processing Unit (GPGPU) computing is a technique that utilizes the high-performance many-core processors of high-end graphic cards for general-purpose computations such as 3D graphics, video/image processing, computer vision, scientific computing, HPC and many more. GPGPUs offer a vast amount of raw computing power, but programming is extremely challenging because of hardware idiosyncrasies. The open computing language (OpenCL) has been proposed as a vendor-independent GPGPU programming interface. OpenCL is very close to the hardware and thus does little to increase GPGPU programmability. In this paper we present how a set of digital camera image signal processing (ISP) filters can be realized efficiently on GPGPUs using OpenCL. Although we found ISP filters to be memory-bound computations, our GPGPU implementations achieve speedups of up to a factor of 64.8 over their sequential counterparts. On GPGPUs, our proposed optimizations achieved speedups between 145% and 275% over their baseline GPGPU implementations. Our experiments have been conducted on a Geforce GTX 275; because of OpenCL we expect our optimizations to be applicable to other architectures as well.

• Journal of IKEEE
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• v.14 no.2
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• pp.76-81
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• 2010

The need for dedicated hardware continue to decrease as the mobile CPU's performance increases. But, there is a limit to a mobile CPU's performance. GP-GPU(General-Purpose computing on Graphics Processing Units) can improve performance without adding other dedicated hardware. This paper presents the implementation of Inverse Quantization, Inverse DCT and Color Space Conversion module in H.264/AVC decoder using GP-GPU for a mobile environments. The proposed architecture improves approximately 40% of performance when it use all the features.

• Smart Media Journal
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• v.5 no.4
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• pp.69-74
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• 2016

Recently, parallel computing using GPGPU(General-Purpose computing on Graphics Processing Units) according to the development of the graphics processing unit is expanding. This can be achieved through the processing speeds faster than traditional computing environments across many fields, including science, medicine, engineering, and analysis. However, in using the GPU technology to implement the a parallel program there are many constraints. In this paper, we port a CPU-based program(Video Quality Measurement Program) to use technology. The program ported to GPU-based show about 1.83 times the execution speed than CPU-based program. We study on the acceleration of the GPU-based program. Also we discuss the technical constraints and problems that occur when you modify the CPU to the GPU-based programs.