%20(1).png)
In the Semi Engineering article by Brett Lowe, "Developing ReRAM As Next Generation On-Chip Memory For Machine Learning, Image Processing And Other Advanced CPU Applications," the focus is on the burgeoning field of Resistive Random Access Memory (ReRAM) as a promising solution for the limitations of current on-chip CPU memory. The article highlights the inefficiencies in modern CPU operations, primarily due to the energy consumption and delays caused by data transfer between the CPU and off-chip memory. SRAM, the prevalent on-chip memory, falls short in meeting the requirements of advanced applications like AI and 8K video processing, which demand memory access bandwidths up to 10 terabytes per second. ReRAM emerges as a viable alternative, boasting a non-volatile memory cell structure that uses memristor materials to enable data storage. This technology facilitates significant improvements in storage density by employing a 3D stacking approach.
The article delves into the intricacies of ReRAM's structure and functionality, utilizing SEMulator3D Virtual Fabrication for process simulation and architectural visualization. The discussed 3D ReRAM model comprises multiple layers of wordlines and memristors, strategically organized for optimized storage density. The programming of memristors in ReRAM, requiring low current and voltage, aligns well with the integration into advanced logic devices. The piece concludes with the assertion that ReRAM stands as a robust contender to replace SRAM in on-chip memory, particularly for high-bandwidth CPU applications. Its potential to significantly reduce energy consumption and processing delays in data movement positions ReRAM as a pivotal innovation for future CPU developments.
No comments:
Post a Comment