In memory computation using quantum-dot cellular automata

IF 1.1 4区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IET Computers and Digital Techniques Pub Date : 2020-09-18 DOI:10.1049/iet-cdt.2020.0008
Mrinal Goswami, Jayanta Pal, Mayukh Roy Choudhury, Pritam P. Chougule, Bibhash Sen
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引用次数: 5

Abstract

The conventional computing system has been facing enormous pressure to cope with the uprising demand for computing speed in today's world. In search of high-speed computing in the nano-scale era, it becomes the utmost necessity to explore a viable alternative to overcome the challenges of the physical limit of complementary-metal-oxide-semiconductor (CMOS). Towards that direction, the processing-in-memory (PIM) is advancing its importance as it keeps the computation as adjacent as possible to memory. It promises to outperform the latencies of the conventional stored-program concept by embedding storage and data computation in a single unit. On the other hand, the bit storing and processing capability of Akers array provides the foundation of PIM. Again, quantum-dot cellular automata (QCA) emerges as a promising nanoelectronic to put back CMOS to give fast-paced devices at the nanoelectronics era. This work presents a novel PIM concept, embedding Akers array in QCA to achieve high-speed computing at the nano-scale era. QCA implementation of universal logic utilizing Akers array signifies its processing power and puts forth its potentials. A universal function is considered for testing the effectiveness of the proposed PIM cell. The performance evaluation indicates the efficacy of QCA PIM over the conventional Von Neumann architecture.

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使用量子点细胞自动机的内存计算
传统的计算系统一直面临着巨大的压力,以应对当今世界对计算速度日益增长的需求。在纳米时代寻求高速计算,探索一种可行的替代方案以克服互补金属氧化物半导体(CMOS)物理极限的挑战成为当务之急。朝着这个方向,存储器中的处理(PIM)正在提高其重要性,因为它使计算尽可能靠近存储器。通过在单个单元中嵌入存储和数据计算,它有望超越传统存储程序概念的延迟。另一方面,阿克斯阵列的比特存储和处理能力为PIM提供了基础。量子点细胞自动机(QCA)再次成为一种很有前途的纳米电子器件,它可以在纳米电子时代将CMOS放回原位,提供快节奏的器件。这项工作提出了一个新的PIM概念,将Akers阵列嵌入QCA中,以实现纳米级的高速计算。利用阿克斯阵列的通用逻辑的QCA实现表明了它的处理能力并展示了它的潜力。考虑了一个通用函数来测试所提出的PIM信元的有效性。性能评估表明QCA PIM优于传统Von Neumann架构。
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来源期刊
IET Computers and Digital Techniques
IET Computers and Digital Techniques 工程技术-计算机:理论方法
CiteScore
3.50
自引率
0.00%
发文量
12
审稿时长
>12 weeks
期刊介绍: IET Computers & Digital Techniques publishes technical papers describing recent research and development work in all aspects of digital system-on-chip design and test of electronic and embedded systems, including the development of design automation tools (methodologies, algorithms and architectures). Papers based on the problems associated with the scaling down of CMOS technology are particularly welcome. It is aimed at researchers, engineers and educators in the fields of computer and digital systems design and test. The key subject areas of interest are: Design Methods and Tools: CAD/EDA tools, hardware description languages, high-level and architectural synthesis, hardware/software co-design, platform-based design, 3D stacking and circuit design, system on-chip architectures and IP cores, embedded systems, logic synthesis, low-power design and power optimisation. Simulation, Test and Validation: electrical and timing simulation, simulation based verification, hardware/software co-simulation and validation, mixed-domain technology modelling and simulation, post-silicon validation, power analysis and estimation, interconnect modelling and signal integrity analysis, hardware trust and security, design-for-testability, embedded core testing, system-on-chip testing, on-line testing, automatic test generation and delay testing, low-power testing, reliability, fault modelling and fault tolerance. Processor and System Architectures: many-core systems, general-purpose and application specific processors, computational arithmetic for DSP applications, arithmetic and logic units, cache memories, memory management, co-processors and accelerators, systems and networks on chip, embedded cores, platforms, multiprocessors, distributed systems, communication protocols and low-power issues. Configurable Computing: embedded cores, FPGAs, rapid prototyping, adaptive computing, evolvable and statically and dynamically reconfigurable and reprogrammable systems, reconfigurable hardware. Design for variability, power and aging: design methods for variability, power and aging aware design, memories, FPGAs, IP components, 3D stacking, energy harvesting. Case Studies: emerging applications, applications in industrial designs, and design frameworks.
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