Memory On Logic: The Good And Bad

The chip industry is progressing rapidly toward 3D-ICs, but a simpler step has been shown to provide gains equivalent to a whole node advancement — extracting distributed memories and placing them on top of logic. Memory on logic significantly reduces the distance between logic and directly associated memory. This can increase performance by 22% and reduce power by 36%, according to one re... » read more

Building CFETs With Monolithic And Sequential 3D

Successive versions of vertical transistors are emerging as the likely successor to finFETs, combining lower leakage with significant area reduction. A stacked nanosheet transistor, introduced at N3, uses multiple channel layers to maintain the overall channel length and necessary drive current while continuing to reduce the standard cell footprint. The follow-on technology, the CFET, pushes... » read more

Developing ReRAM As Next Generation On-Chip Memory For Machine Learning, Image Processing And Other Advanced CPU Applications

In modern CPU device operation, 80% to 90% of energy consumption and timing delays are caused by the movement of data between the CPU and off-chip memory. To alleviate this performance concern, designers are adding additional on-chip memory to their CPUs. Traditionally, SRAM has been the most widely used on-chip CPU memory type. Unfortunately, SRAM is currently limited to a size of hundreds of ... » read more

3D Integration Supports CIM Versatility And Accuracy

Compute-in-memory (CIM) is gaining attention due to its efficiency in limiting the movement of massive volumes of data, but it's not perfect. CIM modules can help reduce the cost of computation for AI workloads, and they can learn from the highly efficient approaches taken by biological brains. When it comes to versatility, scalability, and accuracy, however, significant tradeoffs are requir... » read more

SRAM’s Role In Emerging Memories

Experts at the Table — Part 3: Semiconductor Engineering sat down to talk about AI, the latest issues in SRAM, and the potential impact of new types of memory, with Tony Chan Carusone, CTO at Alphawave Semi; Steve Roddy, chief marketing officer at Quadric; and Jongsin Yun, memory technologist at Siemens EDA. What follows are excerpts of that conversation. Part one of this conversation can be ... » read more

Increasing AI Energy Efficiency With Compute In Memory

Skyrocketing AI compute workloads and fixed power budgets are forcing chip and system architects to take a much harder look at compute in memory (CIM), which until recently was considered little more than a science project. CIM solves two problems. First, it takes more energy to move data back and forth between memory and processor than to actually process it. And second, there is so much da... » read more

Novel NVM Devices and Applications (UC Berkeley)

A dissertation titled “Novel Non-Volatile Memory Devices and Applications” was submitted by a researcher at University of California Berkeley. Abstract Excerpt "This dissertation focuses on novel non-volatile memory devices and their applications. First, logic MEM switches are demonstrated to be operable as NV memory devices using controlled welding and unwelding of the contacting electro... » read more

ReRAM Seeks To Replace NOR

Resistive RAM is gaining renewed attention as demand for faster and cheaper non-volatile memory alternatives continues to grow, particularly in applications such as automotive. Embedded flash has long left designers wishing for better write speeds and lower energy consumption, but as the leading edge of that technology shrunk to 28nm, another problem arose. Manufacturing flash memory at thos... » read more

ReRAMs Look To Silicon For Silicon Compatibility

For such a critical material, silicon oxide is not especially well understood. The semiconductor industry certainly understands how to grow high quality oxides with high breakdown voltages, but what happens in less ideal situations? What does the introduction of microstructure do? If there are regions that are oxygen-rich or silicon-rich relative to the stoichiometric SiO2 composition, how do t... » read more

Efficient Neuromorphic AI Chip: “NeuroRRAM”

New technical paper titled "A compute-in-memory chip based on resistive random-access memory" was published by a team of international researchers at Stanford, UCSD, University of Pittsburgh, University of Notre Dame and Tsinghua University. The paper's abstract states "by co-optimizing across all hierarchies of the design from algorithms and architecture to circuits and devices, we present ... » read more

← Older posts