• Title/Summary/Keyword: 폰 노이만 구조

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A Survey on Advanced Computing for the Next Generation Multimedia Application (차세대 멀티미디어 응용을 위한 고등 컴퓨팅의 서베이와 전망)

  • Kim, Hyuk;Park, Jung-Sun;Ha, Sun-Ju;Eun, Seong-Bae
    • Proceedings of the Korea Multimedia Society Conference
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    • 2012.05a
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    • pp.410-413
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    • 2012
  • 폰 노이만 구조는 VLSI 발전에 현재까지 성공적으로 발전하였으나 공정상 더 이상 발전하기 어려운 단계에 이르렀다. 본 논문에서는 과거 폰 노이만 구조를 벗어난 혹은 폰 노이만 구조 문제 해결에 대한 많은 연구들을 조사 분류하였다. 그 결과 앞으로 고등 컴퓨터 기술 발전은 병렬 컴퓨터로 발전 될 가능성을 제시한다.

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Design of In-Memory Computing Adder Using Low-Power 8+T SRAM (저 전력 8+T SRAM을 이용한 인 메모리 컴퓨팅 가산기 설계)

  • Chang-Ki Hong;Jeong-Beom Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.2
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    • pp.291-298
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    • 2023
  • SRAM-based in-memory computing is one of the technologies to solve the bottleneck of von Neumann architecture. In order to achieve SRAM-based in-memory computing, it is essential to design efficient SRAM bit-cell. In this paper, we propose a low-power differential sensing 8+T SRAM bit-cell which reduces power consumption and improves circuit performance. The proposed 8+T SRAM bit-cell is applied to ripple carry adder which performs SRAM read and bitwise operations simultaneously and executes each logic operation in parallel. Compared to the previous work, the designed 8+T SRAM-based ripple carry adder is reduced power consumption by 11.53%, but increased propagation delay time by 6.36%. Also, this adder is reduced power-delay-product (PDP) by 5.90% and increased energy-delay- product (EDP) by 0.08%. The proposed circuit was designed using TSMC 65nm CMOS process, and its feasibility was verified through SPECTRE simulation.

A Multithreaded Architecture for the Efficient Execution of Vector Computations (벡타 연산을 효율적으로 수행하기 위한 다중 스레드 구조)

  • Yun, Seong-Dae;Jeong, Gi-Dong
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.6
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    • pp.974-984
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    • 1995
  • This paper presents a design of a high performance MULVEC (MULtithreaded architecture for the VEctor Computations), as a building block of massively parallel Processing systems. The MULVEC comes from the synthesis of the dataflow model and the extant super sclar RISC microprocesso r. The MULVEC reduces, using status fields, the number of synchronizations in the case of repeated vector computations within the same thread segment, and also reduces the amount of the context switching, network traffic, etc. After be nchmark programs are simulated on the SPARC station 20(super scalar RISC microprocessor)the performance (execution time of programs and the utilization of processors) of MULVEC and the performance(execution time of a program) of *Taccording the different numbers of node are analyzed. We observed that the execution time of the program in MULVEC is faster than that in * T about 1-2 times according the number of nodes and the number of the repetitions of the loop.

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