• The KIPS Transactions:PartA
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• v.12A no.3 s.93
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• pp.263-272
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• 2005

The addressing mode for data is performed by the software in yon Neumann-concept(SISD) computer a priori without hardware design of an address counter for operands. Therefore, in the addressing mode for the vector the corresponding variables as much as the number of the elements should be specified and used also in the software method. This is because not for operand but only for an instructions, quasi PC(program counter) is designed in hardware physically. A vector has a characteristic of a structural dimension. In this paper we propose to design a hardware unit physically external to the CPU for addressing only the elements of a vector unit with the structure and dimension. Because of the high speed performance for a vector processing it should be designed in the SIMD pipeline mechanics. The proposed mechanics is evaluated through a simulation. Our result shows $12\%$ to $30\%$ performance enhancement over CRAY architecture under the same hardware consideration(processing unit).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.65-77
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• 2009

This paper proposes fast image processing algorithms using SSE (Streaming SIMD Extensions) instructions. The CPU's supporting SSE instructions have 128bit XMM registers; data included in these registers are processed at the same time with the SIMD (Single Instruction Multiple Data) mode. This paper develops new SIMD image processing algorithms for Mean filter, Sobel horizontal edge detector, and Morphological erosion operation which are most widely used in automated optical inspection systems and compares their processing times. In order to objectively evaluate the processing time, the developed algorithms are compared with OpenCV 1.0 operated in SISD (Single Instruction Single Data) mode, Intel's IPP 5.2 and MIL 8.0 which are fast image processing libraries supporting SIMD mode. The experimental result shows that the proposed algorithms on average are 8 times faster than the SISD mode image processing library and 1.4 times faster than the SIMD fast image processing libraries. The proposed algorithms demonstrate their applicability to practical image processing systems at high speed without commercial image processing libraries or additional hardwares.

• Annual Conference of KIPS
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• 2005.05a
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• pp.1473-1476
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• 2005

데이터 주소의 계수를 위한 하드웨어 설계가 없는 본 노이만(von Neumann) 개념(SISD)의 컴퓨터에서 데이터의 주소지정은 소프트웨어적으로 수행된다. 그러므로 벡터 데이터 요소들의 주소지정은 인덱싱 기법에 의해 그 요소 수만큼 해당 변수들을 만들어서 사용해야 한다. 이것은 데이터 계수기 없이 명령어 계수기, 즉 PC(program counter)만 하드웨어로 설계되기 때문이다. 본 연구에서는 중앙처리장치 외부에 외형적 구조와 크기를 갖는 단위 벡터의 요소를 액세스하는 하드웨어 유닛의 설계를 제안한다. 제안한 방법은 시뮬레이션을 통하여 성능 검증을 하였으며, 실험 결과 동일한 프로세싱 유닛을 가지는 벡터 머신 아키텍쳐보다 12 - 30 % 정도 우수한 성능을 내는 것을 확인하였다.