• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.1-9
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• 2011

Recently, as mobile multimedia devices are used more and more, the needs for high-performance and low-energy multimedia processors are increasing. Application-specific integrated circuits (ASIC) can meet the needed high performance for mobile multimedia, but they provide limited, if any, generality needed for various application requirements. DSP based systems can used for various types of applications due to their generality, but they require higher cost and energy consumption as well as less performance than ASICs. To solve this problem, this paper proposes a single instruction multiple data (SIMD) based many-core processor which supports high-performance and low-power image data processing while keeping generality. The proposed SIMD based many-core processor composed of 16 processing elements (PEs) exploits large data parallelism inherent in image data processing. Experimental results indicate that the proposed SIMD-based many-core processor higher performance (22 times better), energy efficiency (7 times better), and area efficiency (3 times better) than conversional commercial high-performance processors.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.50-55
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• 2012

This paper proposes an optima] many-core processor architecture that meets the requirements of low power and high performance for different ultrasonic image resolutions in hand-held ultrasonic devices. To identify the optimal many-core architecture, seven different PE configurations are simulated for processing ultrasonic images in terms of execution performance and energy consumption. Experimental results indicate that the highest energy efficiencies are achieved at PEs=1,024, 64, and 256 for ultrasonic images at $256{\times}256$, $320{\times}240$, and $800{\times}480$ resolutions, respectively. In addition, the maximum area efficiencies are obtained at PEs=256 (for $256{\times}256$ and $800{\times}480$ image resolutions) and 64 (for $320{\times}240$ image resolution).

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.119-128
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• 2011

This paper introduces design space exploration of many-core processors that meet high performance and low power required by the beamforming algorithm of image signals of mobile ultrasound. For the design space exploration of the many-core processor, we mapped different number of ultrasound image data to each processing element of many-core, and then determined an optimal many-core processor architecture in terms of execution time, energy efficiency and area efficiency. Experimental results indicate that PE=4096 and 1024 provide the highest energy efficiency and area efficiency, respectively. In addition, PE=4096 achieves 46x and 10x better than TI DSP C6416, which is widely used for ultrasound image devices, in terms of energy efficiency and area efficiency, respectively.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.1-10
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• 2012

This paper proposes design space exploration methodology of many-core processors including multimedia specific instructions to support high-performance and low power ultrasound imaging for portable devices. To explore the impact of multimedia instructions, we compare programs using multimedia instructions and baseline programs with a same many-core processor in terms of execution time, energy efficiency, and area efficiency. Experimental results using a $256{\times}256$ ultrasound image indicate that programs using multimedia instructions achieve 3.16 times of execution time, 8.13 times of energy efficiency, and 3.16 times of area efficiency over the baseline programs, respectively. Likewise, programs using multimedia instructions outperform the baseline programs using a $240{\times}320$ image (2.16 times of execution time, 4.04 times of energy efficiency, 2.16 times of area efficiency) as well as using a $240{\times}400$ image (2.25 times of execution time, 4.34 times of energy efficiency, 2.25 times of area efficiency). In addition, we explore optimal PE architecture of many-core processors including multimedia instructions by varying the number of PEs and memory size.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.1-10
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• 2012

Improving operating frequency of processors is no longer today's issues; a multiprocessor technique which integrates many processors has received increasing attention. Currently, high-performance processors that integrate 64 or 128 cores are developing for large data processing over 2, 4, or 8 processor cores. This paper proposes an optimal many-core processor for synthesizing guitar sounds. Unlike the previous research in which a processing element (PE) was assigned to support one of guitar strings, this paper evaluates the impacts of mapping different numbers of PEs to one guitar string in terms of performance and both area and energy efficiencies using architectural and workload simulations. Experimental results show that the maximum area energy efficiencies were achieved at PEs=24 and 96, respectively, for synthesizing guitar sounds with sampling rate of 44.1kHz and 16-bit quantization. The synthesized sounds were very similar to original guitar sounds in their spectra. In addition, the proposed many-core processor was 1,235 and 22 times better than TI TMS320C6416 in area and energy efficiencies, respectively.

• The Journal of the Acoustical Society of Korea
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• v.30 no.5
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• pp.281-294
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• 2011

Physics-based sound synthesis usually requires high computational costs and this results in a restriction of its use in real-time applications. This motivates us to implement the sound synthesis algorithm of plucked-string instruments using multi-core processor architectures and determine the optimal processing element (PE) configuration for the target instruments. To determine the optimal PE configuration, we evaluate the impacts of a sample-per-processing element (SPE) ratio that is defined as the amount of sample data directly mapped to each PE on system performance and both area and energy efficiencies using architectural and workload simulations. For the acoustic guitar, the highest area and energy efficiencies are achieved at a SPE ratio of 5,513 and 2,756, respectively, for the synthesis of musical sounds sampled at 44.1 kHz. In the case of the classical guitar, the maximum area and energy efficiencies are achieved at a SPE ratio of 22,050 and 5,513, respectively. In addition, the synthetic sounds were very similar to original sounds in their spectra. Furthermore, we conducted MUSHRA subjective listening test with ten subjects including nine graduate students and one professor from the University of Ulsan, and the evaluation of the synthetic sounds was excellent.

• The KIPS Transactions:PartA
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• v.18A no.2
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• pp.45-52
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• 2011

In the past, a patient went to the room where an ultrasound image diagnosis device was set, and then he or she was examined by a doctor. However, currently a doctor can go and examine the patient with a handheld ultrasound device who stays in a room. However, it was implemented with only fundamental functions, and can not meet the high performance required by the focusing algorithm of ultrasound beam which determines the quality of ultrasound image. In addition, low energy consumption was satisfied for the mobile ultrasound device. To satisfy these requirements, this paper proposes a high-performance and low-power single instruction, multiple data (SIMD) based multi-core processor that supports a representative beamforming algorithm out of several focusing methods of mobile ultrasound image signals. The proposed SIMD multi-core processor, which consists of 16 processing elements (PEs), satisfies the high-performance required by the beamforming algorithm by exploiting considerable data-level parallelism inherent in the echo image data of ultrasound. Experimental results showed that the proposed multi-core processor outperforms a commercial high-performance processor, TI DSP C6416, in terms of execution time (15.8 times better), energy efficiency (6.9 times better), and area efficiency (10 times better).