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Optimized Programming for STT-MTJ-Based TCAM for Low-Energy Approximate Computing

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Applications of Emerging Memory Technology

Part of the book series: Springer Series in Advanced Microelectronics ((MICROELECTR.,volume 63))

Abstract

In the advent of data-driven systems and processes, high speed and energy-efficient computing techniques are highly desirable. Such systems and techniques are already being employed in many applications, which mainly depends on a huge amount of data like information analysis, transmission, policy, decision-making, etc. An electronic system used in these applications, require to perform the operations like data capture, storage, visualization, and -analysis. Most of such systems employ content addressable memories (CAMs), also known as associative memories for high-speed data search/compare and compute operation. In this chapter, an optimized programming scheme for magnetic tunnel junction (MTJ) based resistive ternary content addressable memory (ReTCAM) for approximate computing (AC) application is presented. Basic key concepts related to MTJ structure, physics, electrical behavior, bit-cell design, and AC are also discussed. Error-tolerant behavior of AC and stochastic writing of ReTCAM cell are exploited to achieve low write energy. Case study of 3-bit (LSB) write operation using the proposed programming scheme is also investigated based on distance match accuracy. ReTCAM bit-cell is designed using perpendicular magnetic anisotropic (PMA) MTJ device with 32 nm diameter and 90 nm CMOS technology.

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Authors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, 110016, India

    Ashwani Kumar & Manan Suri

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  1. Ashwani Kumar
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  2. Manan Suri
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Correspondence to Manan Suri .

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  1. Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, Delhi, India

    Manan Suri

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Kumar, A., Suri, M. (2020). Optimized Programming for STT-MTJ-Based TCAM for Low-Energy Approximate Computing. In: Suri, M. (eds) Applications of Emerging Memory Technology. Springer Series in Advanced Microelectronics, vol 63. Springer, Singapore. https://doi.org/10.1007/978-981-13-8379-3_6

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  • DOI: https://doi.org/10.1007/978-981-13-8379-3_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-8378-6

  • Online ISBN: 978-981-13-8379-3

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