Our intelligent, interconnected, data-driven world demands more computation and capacity. Consider the variety of smart applications we now have. Cars can transport passengers to their destinations using local and remote AI decision making. Robot vacuum cleaners keep our homes tidy. Smart watches can detect a fall and call emergency services. With high-volume computations comes greater demand for high memory capacity, along with an absolute necessity to reduce system-on-chip (SoC) power, especially for battery-operated devices.
As data gets generated by more sources, the data needs to be processed and accessed swiftly—especially for always-on applications. Embedded Flash (eFlash) technology, a traditional memory solution, is nearing its end, as scaling it below 28nm is highly expensive. In response, designers of IoT and edge-device SoCs, along with other AI-enabled chips, are seeking a low cost, area- and power-efficient alternative to support their growing appetite for memory.
As it turns out, the new memory solution ideal for low-power, advanced-node SoCs isn’t so new at all. Embedded Magneto-Resistive Random Access Memory (eMRAM) emerged about two decades ago but is now undergoing an uplift in utilization thanks to its high capacity, high density, and ability to scale to lower geometries. In this blog post, we’ll take a closer look at how IoT and edge devices are creating shifts away from traditional memory technologies, why eMRAM is taking off now, and how Synopsys is helping to ease the process of designing with eMRAM.
Click here to read more ...