RRAM applications

Qualcomm Technologies has announced two new IOT chipsets, the Qualcomm QCC730M and Qualcomm QCC74xM modules. The company says that these modules are perfectly suited for IoT applications in the smart home, smart appliances and more.

The QCC730M chip is is a dual-band, micro-power Wi-Fi 4 module. Offering a dedicated 60Mhz MCU units, 640kB of SRAM and 1.5Mb  RRAM memory. The QCC730M also integrates hardware crypto accelerator, and secure boot, debug, and storage.

China-based Xianxin Technology, in collaboration with several research institutes in China, have developed the world's first 28 nm image quality adjustment chip that is powered by embedded RRAM memory.

The company says it is now mass producing the new driver IC, which will be supplied to high-end miniLED LCD TV makers. The company says that by adopting RRAM rather than the mainstream external Flash memory, it enables faster read operations, and lower cost production. 

China-based wireless IC designer New Radio Tech (NRT) introduced a new Ultra-WideBand (UWB) chip, the URSAMAJOR 82660, that integrates RRAM. We assume that the embedded RRAM technology was provided by Hefei Reliance Memory, but we're not certain.

The company says that integrating the RRAM into their chip is a major achievements, and it allows them to reduce the chip's footprint by 40%, while being highly cost effective compared to conventional chips that are based on external Flash or integrated eFlash solutions.

China-based OLED producer Visionox, together with Sunrise Display Microelectronics and Hefei Reliance Memory, developed the world's firs AMOLED device driver that is powered by RRAM memory. 

All AMOLED drivers on the market use a combination of SRAM memory, OTP (one-time programmable memory) and external Flash memory (for non-volatile memory), mostly to perform the Demura compensation function. The RRAM memory enables lower cost of production, higher efficiency - and smaller area.

Nuvoton Technology launched the M2L31, a new energy-efficient microcontroller, that features up to 512Kb of high-performance low-power non-volatile RRAM.

The M2L31 is based on an Arm Cortex-M23 core (up to 72Mhz), and is designed to meet the growing demand for sustainable high-performance embedded computing power. Nuvoton explains that a main contributor to the high efficiency of the new chip is its choice of memory, an on-chip RRAM instead of flash memory that draws less power and can be written to without an erase cycle beforehand.

Australia-based RRAM developer 4DS Memory announced a new type of RRAM technology specifically for AI processing, that enables high-bandwidth, high-endurance persistent memory for big data and neural net applications.

4DS says that as its RRAM requires no refresh within its persistence window and can be 'refreshed' within the DRAM operating window, it can uniquely deliver an energy efficient high bandwidth and high endurance memory technology for the AI Age.

Infineon says that its next generation Aurix TC4x microcontrollers will adopt RRAM memory, instead of the traditional embedded flash. The company expects the first samples of such chips to ship to customers before the end of 2023.

Infineo's next-gen Aurix chips will be produced at Taiwan Semiconductor Manufacturing Co (TSMC), using its 28nm CMOS process. The company says that RRAM memory will be more energy efficient at 28nm compared to the currently-used embedded flash memories. The RRAM memory will also enable higher disturb immunity and it allows for bit-wise writing without need for erase, which allows for superior performance over embedded flash. The cycling endurance and data retention are comparable with flash.

Israel-based RRAM developer Weebit Nano demonstrated (together with its partner, CEA-Leti) how its RRAM can provide an exciting new solution for artificial intelligence applications using spiking neural networks, at the Flash Memory Summit:

Neuromorphic computing makes it possible to emulate the brain’s natural operation. Using RRAM, this emulation is much more efficient than today’s simulations, consuming orders of magnitude less power, to allow sophisticated AI at a fraction of the power consumed by today’s systems. This is because the ReRAM (RRAM) cell has physical and functional similarities to a biological brain synapse.

CrossBar announced that its RRAM memory technology is inherently resistant to physical hacking targeting sensitive information and data stored in memory. This could lead to new applications where resistance to reverse engineering and physical attacks are essential requirements of the system.

Cross bar says that its filamentary-based ReRAM has been demonstrated to provide unique levels of security, including strong resistance to attempts to read the memory through invasive physical hacking. Cross further says that MicroNet Solutions (MSI) performed extensive delayering and inspection of CrossBar's ReRAM memory silicon through imaging techniques in an attempt to determine its stored content. After significant evaluation using sophisticated techniques such as measuring electron beam induced current and passive voltage contrast imaging, MSI was unsuccessful in determining the contents of the memory array.

CrossBar says that its partners are now starting to use its RRAM memory technology for few-time programmable (FTP) and one-time-programmable (OTP) NVM applications. This is in addition to CrossBar's "traditional" MTP non-volatile memory and PUF security applications.

CrossBar says that this new applications demand can be met with its current technology, but the company also offers to optimize its RRAM for FTP and OTP applications, which will significantly increase memory density and reduce the cost.