On-chip memory (embedded memory) makes computing applications run faster. In the early days of the semiconductor industry, the desire to utilize large amount of on-chip memory was limited by cost, manufacturing difficulties and technology mismatches between logic and memory circuit implementations. Since then, advancements in semiconductor manufacturing have been bringing on-chip memory costs down. In parallel, leading edge process nodes have been throwing new challenges to embedded memories. Of course, high-speed I/O interfaces have made it easier to use off-chip memories without sacrificing computing application speed. At the same time, new applications such as AI, machine learning, mobile and other low-power applications have been fueling demands for large amounts of embedded memories. Many of the existing embedded memory technologies face challenges as the process node goes below 28nm. The challenges are due to additional material layers and masks, supply voltages, speed, read & write granularity and area.
It is in this context that eMemory Technology Inc. will be hosting a webinar that will be very informative and useful for chip designers and semiconductor companies. The webinar is titled “eMemory’s Embedded ReRAM Solution on Nanometer Technologies” and is scheduled for March 24th, 2021. I got an opportunity to preview the webinar content. Following is just a few of the salient points that I’d like to share in this blog. Please register for the webinar to learn the full and intricate details.
The webinar will focus on a very promising technology called Resistive RAM (ReRAM) that will be available in production very soon. ReRAM is specifically designed to work in 40nm and finer geometry process nodes. In contrast, many of the other memory types such as Split-Gate Flash, Logic process MTP and Logic Process EEPROM face challenges below 28nm.
Due to ReRAM’s simplicity for process manufacturing, it can be integrated into Back End of Line (BEOL) with only a few extra masks and steps. ReRAM technology enables high-speed, low-power write operations and increased storage density, all critical for AI computing-in-memory application as an example.
Attendees will gain insights into ReRAM cell structure, switching methodology, and the suitability of ReRAM to various prospective applications. eMemory Technology will also share measurement results of their 40nm ULP and 22nm ULL ReRAM reliability data at 85C and 125C operation and 10-year retention data after 10K cycles.
Anyone who is looking into designing chip solutions in advanced process nodes for applications that could benefit from embedded memories would learn a lot from attending this webinar. Register here for the “eMemory’s Embedded ReRAM Solution on Nanometer Technologies” webinar.Share this post via: