• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.8
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• pp.1489-1496
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• 2010

A feed forward differential architecture of analog PRML decoder is investigated to implement on analog parallel processing circuits. The conventional PRML decoder performs the trellis processing with the implementation of single stage in digital and its repeated use. The analog parallel processing-based PRML comes from the idea that the decoding of PRML is done mainly with the information of the first several number of stages. Shortening the trellis processing stages but implementing it with analog parallel circuits, several benefits including higher speed, no memory requirement and no A/D converter requirement are obtained. Most of the conventional analog parallel processing-based PRML decoders are differential architecture with the feedback of the previous decoded data. The architecture used in this paper is without feedback, where error metric accumulation is allowed to start from all the states of the decoding stage, which enables to be decoded without feedback. The circuit of the proposed architecture is simpler than that of the conventional analog parallel processing structure with the similar decoding performance. Characteristics of the feed forward differential architecture are investigated through various simulation studies.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.41-51
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• 1996

In this paper, anew parallel processing system based on a cluster architecture which provides scalability of a parallel processing system while maintains shared memory multiprocessor characteristics is proposed. In recent days low cost, high performnce microprocessors have led to construction of large scale parallel processing systems. Such parallel processing systems provides large scalability but are mainly used for scientific applications which have large data parallelism. A shared memory multiprocessor system like TICOM is currently used as aserver for the commercial application, however, the shared memory multiprocessor system is known to have very limited scalability. The proposed architecture can support scalability and performance of the parallel processing system while it provides adaptability for the commerical application, hence it can overcome the limitation of the shared memory multiprocessor. The architecture and characteristics of the proposed system shall be described. A proprietary hierarchical crsossbar network is designed for this system, of which the protocol, routing and switching technique and the signal transfer technique are optimized for the proposed architecture. The design trade-offs for the network are described in this paper and with simulation usihng the SES/workbench, it is explored that the network fits to the proposed architecture.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.619-625
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• 2009

This paper proposes a parallel architecture of a Parity Checksum Generator adopted for packet synchronization and error detection in the ITU-T Recommendation J.83 Annex B. The proposed parallel processing architecture removes a performance bottleneck occurred in a conventional serial processing architecture, leading to significant decrease in processing time for generating a Parity Checksum. The implementation results show that the proposed parallel processing architecture reduces the processing time by 83.1% at the expense of 16% area increase.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.69-77
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• 2021

The widely used low-cost design methodology for IoT devices is very popular. In such a networked device, memory is composed of flash memory, SRAM, DRAM, etc., and because it processes a large amount of data, memory design is an important factor for system performance. Therefore, each device selects optimized design factors such as function, performance and cost according to market demand. The design of a memory architecture available for low-cost IoT devices is very limited with the configuration of SRAM, flash memory, and DRAM. In order to process as much data as possible in the same space, an architecture that supports parallel processing units is usually provided. Such parallel architecture is a design method that provides high performance at low cost. However, it needs precise software techniques for instruction and data mapping on the parallel architecture. This paper proposes an instruction/data mapping method to support optimized parallel processing performance. The proposed method optimizes system performance by actively using hardware and software parallelism.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.7
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• pp.909-915
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• 1999

In this paper, we propose an efficient VLSI architecture of Reed-Solomon(RS) decoder. To improve the speed. we develope an architecture featuring parallel and pipelined processing. To implement the parallel and pipelined processing architecture, we analyze the RS decoding algorithm and the honor's algorithm for parallel processing and we also modified the Euclid's algorithm to apply the efficient parallel structure in RS decoder. To show the proposed architecture, the performance of the proposed RS decoder is compared to Shao's and we obtain the 10 % efficiency in area and three times faster in speed when it's compared to Shao's time domain decoder. In addition, we implemented the proposed RS decoder with Altera FPGA Flex10K-50.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.647-650
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• 1988

This paper proposes and sketches out a new parallel architecture of transputer-based pyramidal parallel array computer (TPPAC) used to process computationally intensive problems for geometric processing applications such as computer vision, image processing etc. It explores how efficiently the pyramid computer architecture is designed using transputer chips, and poses a new interconnection scheme for TPPAC without using additional transputers.

• Journal of IKEEE
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• v.4 no.2 s.7
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• pp.212-224
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• 2000

In this paper, a parallel processing system is proposed for improving the processing speed of image related applications. The proposed parallel processing system is fully synchronous SIMD computer with pipelined architecture and consists of processing elements and a multi-access memory system. The multi-access memory system is made up of memory modules and a memory controller, which consists of memory module selection module, data routing module, and address calculating and routing module, to perform parallel memory accesses with the variety of types: block, horizontal, and vertical access way. Morphological filter had been applied to verify the parallel processing system and resulted in faithful processing speed.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.724-740
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• 2016

The performance issues of screening large database compounds and multiple query compounds in virtual screening highlight a common concern in Chemoinformatics applications. This study investigates these problems by choosing group fusion as a pilot model and presents efficient parallel solutions in parallel platforms, specifically, the multi-core architecture of CPU and many-core architecture of graphical processing unit (GPU). A study of sequential group fusion and a proposed design of parallel CUDA group fusion are presented in this paper. The design involves solving two important stages of group fusion, namely, similarity search and fusion (MAX rule), while addressing embarrassingly parallel and parallel reduction models. The sequential, optimized sequential and parallel OpenMP of group fusion were implemented and evaluated. The outcome of the analysis from these three different design approaches influenced the design of parallel CUDA version in order to optimize and achieve high computation intensity. The proposed parallel CUDA performed better than sequential and parallel OpenMP in terms of both execution time and speedup. The parallel CUDA was 5-10x faster than sequential and parallel OpenMP as both similarity search and fusion MAX stages had been CUDA-optimized.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.1655-1658
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• 2004

Current rendering processors are organized mainly to process a triangle as fast as possible and recently parallel 3D rendering processors, which can process multiple triangles in parallel with multiple rasterizers, begin to appear. For high performance in processing triangles, it is desirable for each rasterizer have its own local pixel cache. However, the consistency problem may occur in accessing the data at the same address simultaneously by more than one rasterizer. In this paper, we propose a parallel rendering processor architecture, called DAVID II, resolving such consistency problem effectively. Moreover, the proposed architecture reduces the latency due to a pixel cache miss significantly. The experimental results show that DAVID II achieves almost linear speedup at best case even in sixteen rasterizers.

• JSTS:Journal of Semiconductor Technology and Science
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• v.12 no.2
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• pp.150-161
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• 2012

Eye detection is widely used in applications, such as face recognition, driver behavior analysis, and human-computer interaction. However, it is difficult to achieve real-time performance with software-based eye detection in an embedded environment. In this paper, we propose a parallel hardware architecture for real-time eye detection. We use the AdaBoost algorithm with modified census transform(MCT) to detect eyes on a face image. We parallelize part of the algorithm to speed up processing. Several downscaled pyramid images of the eye candidate region are generated in parallel using the input face image. We can detect the left and the right eye simultaneously using these downscaled images. The sequential data processing bottleneck caused by repetitive operation is removed by employing a pipelined parallel architecture. The proposed architecture is designed using Verilog HDL and implemented on a Virtex-5 FPGA for prototyping and evaluation. The proposed system can detect eyes within 0.15 ms in a VGA image.