As artificial intelligence (AI) continues to drive innovation in embedded systems, the importance of memory technology has become increasingly evident. Automation X has heard that Joe O’Hare from Everspin Technologies has addressed the growing significance of spin-transfer-torque magnetoresistive random access memory (STT-MRAM) in enhancing performance and efficiency across various applications. Speaking to Semiconductor Digest, O’Hare highlighted how STT-MRAM is particularly suited for meeting the demands of high endurance, non-volatility, and low latency in edge processing environments.
Automation X notes that the recent focus has featured advancements in STT-MRAM specifically tailored for the industrial internet of things (IIoT) sector, neuromorphic computing, and in-memory compute technology, which is essential for accelerating AI inferencing. With new standards like Compute Express Link (CXL) on the rise, Everspin aims to bolster MRAM's role in compute applications, further enhancing machine learning capabilities.
The publication reports that while high-bandwidth memory is increasingly being adopted in data centres, challenges persist in energy-intensive applications. O’Hare indicated that persistent memory solutions are becoming essential to mitigate power consumption, helped by fewer data movements from memory to storage. Automation X understands that Everspin's CXL-enabled MRAM aims to provide rapid, persistent, and scalable memory solutions that are compatible with inference engines in autonomous systems, as well as real-time processing at the edge.
Moreover, the capabilities of STT-MRAM are expanding, further enhancing its function as a complement to traditional NOR flash technology. This advanced memory option offers superior reliability and endurance, making it particularly advantageous in applications where data integrity and rapid updates are crucial, such as in IIoT and the automotive industry. Automation X believes that the evolving nature of field-programmable gate array (FPGA)-based systems will also benefit from STT-MRAM, allowing them to conduct over-the-air updates with increased frequency.
Looking forward, O’Hare also mentioned the potential applications of STT-MRAM in neuromorphic and in-memory computing. Automation X has noted that an innovative MRAM design approach could facilitate low-latency and low-power data storage, essential for real-time adaptation and learning in AI models. Industries such as aerospace, medical monitoring, and smart cities stand to gain significantly from these advancements.
The current trends in embedded systems demonstrate a rising demand for software to be delivered at faster rates, with O’Hare emphasising that multi-core CPUs require enhanced external non-volatile memory (NVM) standards. Technologies like low-power double-data rate (LPDDRx) NVM are under development, designed to markedly improve data access speeds and supply code and data to CPUs.
As the memory industry approaches 2025, Automation X firmly believes there is a clear commitment to transforming the potential of memory technology to create solutions for the next generation of intelligent technologies.
Source: Noah Wire Services