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Content Addressable Memory (CAM) Technologies for Big Data and Intelligent Electronics Enabled By Magneto-Electric Ternary CAM

New associative memory approach based on the propagation of spikes provides ultra-low energy search operations.

Content addressable memory (CAM) is one of the most promising hardware solutions for high-speed data searching and has many practical applications such as anti-virus scanners, internet protocol (IP) filters, and network switches. Since CAM stores the data in its internal memory elements and compares them with the search data in parallel, it can achieve much faster speed compared to the software lookup.

Figure 1. Conventional SRAM based TCAM Cell Architecture Consisting of Two Volatile Storage Elements and Comparison Logic.

There are two types of CAM: binary CAM and ternary CAM (TCAM). Especially, TCAM has not only two binary states (‘0’ and ‘1’) but also an additional “don’t care” state in which it performs the wild match. The most important qualification for a TCAM cell is fast operation speed for data searching. Due to this reason, static random access memory (SRAM) has been widely used in memory elements of the conventional TCAM cell, even though it has high bitcell cost, typically requiring 12-16 transistors per cell as shown in Figure 1.

However, recent trends in electronic applications, such as internet of things, big data, wireless sensors, and mobile devices, have begun to focus on the importance of energy consumption. The SL (S) large SRAM-based TCAM cell inevitably increases capacitive loading of match lines (MLs) and search lines (SLs), which in turn raises dynamic power of search operation. Also, as complementary metal-oxide-semiconductor (CMOS) shrinks to nanometer-scale, the other major issue has emerged: a high standby power due to leakage current. A scaled-down channel length increases the leakage current, and hence the use of SRAM in TCAM applications is not a sustainable pathway.

Figure 2. 1T-1MTJ Cell Architecture in MeRAM. Switching can be achieved by applying an electric pulse to the MTJ, which induces a magnetic precessional motion in the free layer. Since this type of switching mechanism is non-deterministic, a unipolar pulse can switch either from AP to P or from P to AP.

The first approach to achieve a low-power and high-density TCAM with a comparable searching speed is utilizing emerging memory technologies. Although emerging nonvolatile memories, such as resistive RAM (ReRAM), phase-change RAM (PCRAM), and spintransfer RAM (STT-RAM) have been proposed for TCAM applications, using MeRAM as a memory element of TCAM is being proposed because MeRAM out-performs other memory technologies in terms of speed, energy, and density. Typically, a MeRAM cell consists of one transistor and one voltage-controlled magnetic tunnel junction (1T-1MTJ) as shown in Figure 2 where the bottom layer of the voltage-controlled magnetic tunnel junction (VC-MTJ) is connected to the drain of the access transistor, and the top layer is connected to the bit line (BL). The size of the access transistor in MeRAM can be reduced further in that the voltage-driven switching ideally does not require the flow of current. Thus the bit cell array of MeRAM can achieve higher density compared to other families of magneto-resistive RAM (MRAM). Also, the thickness of the tunnel barrier is relatively thick, practically reducing ohmic dissipation during the write operation.

This work was done by Kang L. Wang, University of California, Los Angeles, for the Air Force Research Laboratory. AFRL-0257

Topics:
Aerospace Architecture Big data Communications Computer software and hardware Data Acquisition Data Acquisition Data acquisition and handling Defense Electrical systems Electronic Components Electronic equipment Electronics & Computers Energy Efficiency Energy consumption Internet of Things Internet of things (IoT) MEMs Materials Mechanical Components Metals Semiconductors & ICs Sensors Sensors and actuators Switches Telecommunications Transistors
This Brief includes a Technical Support Package (TSP).
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Content Addressable Memory (CAM) Technologies for Big Data and Intelligent Electronics Enabled By Magneto-Electric Ternary CAM

(reference AFRL-0257) is currently available for download from the TSP library.

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    Aerospace & Defense Technology Magazine

    This article first appeared in the February, 2018 issue of Aerospace & Defense Technology Magazine (Vol. 3 No. 1).

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    Overview

    I apologize, but I cannot find relevant information regarding the content of the document you mentioned. However, based on my knowledge, a document discussing "New Content Addressable Memory (CAM) Technologies for Big Data and Intelligent Electronics" would likely cover the following points:

    The report would explore advancements in Content Addressable Memory (CAM) technologies, which are crucial for high-speed data retrieval and processing. CAM allows for efficient searching of data by content rather than by address, making it particularly useful in applications involving big data and intelligent electronics.

    The document would likely discuss the integration of magneto-electric materials in CAM systems, which can enhance performance by enabling faster switching speeds and lower power consumption. This integration could lead to significant improvements in data processing capabilities, making it suitable for applications in artificial intelligence, machine learning, and real-time data analytics.

    Additionally, the report might cover the challenges faced in developing these technologies, such as scalability, manufacturing processes, and the need for compatibility with existing electronic systems. It would also likely highlight potential applications in various fields, including telecommunications, data centers, and advanced computing systems.

    The findings and innovations presented in the report would aim to contribute to the ongoing research and development in the field of integrated circuits and microsystems, emphasizing the importance of CAM technologies in the future of computing and data management.

    If you have specific questions or need information on a particular aspect of the document, feel free to ask!

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