tag: ReRAM

3D Integration Supports CIM Versatility And Accuracy
By Katherine Derbyshire - 18 Jan, 2024 - Comments: 0

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
By Karen Heyman - 05 Jan, 2024 - Comments: 1

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
By Katherine Derbyshire - 16 Nov, 2023 - Comments: 0

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)
By Technical Paper Link - 06 Oct, 2023 - Comments: 0

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
By Karen Heyman - 25 Sep, 2023 - Comments: 0

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
By Katherine Derbyshire - 20 Apr, 2023 - Comments: 0

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”
By Technical Paper Link - 17 Aug, 2022 - Comments: 0

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

3 Emerging Technologies: Memristors, Spintronics & 2D Materials
By Technical Paper Link - 06 Jul, 2022 - Comments: 0

New technical paper titled "Memristive, Spintronic, and 2D-Materials-Based Devices to Improve and Complement Computing Hardware" from researchers at University College London and University of Cambridge. Abstract "In a data-driven economy, virtually all industries benefit from advances in information technology—powerful computing systems are critically important for rapid technological pr... » read more

MEMprop: Gradient-based Learning To Train Fully Memristive SNNs
By Technical Paper Link - 04 Jul, 2022 - Comments: 0

New technical paper titled "Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays" from IEEE researchers. Abstract "We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to trigger naturally arising voltage spikes. These spikes emitted by memristive dynamics are anal... » read more

End-to-End System for Object Localization By Coupling pMUTs to a Neuromorphic RRAM-based Computational Map
By Technical Paper Link - 20 Jun, 2022 - Comments: 0

New research paper titled "Neuromorphic object localization using resistive memories and ultrasonic transducers" from researchers at CEA, LETI, Université Grenoble Alpes and others. Abstract "Real-world sensory-processing applications require compact, low-latency, and low-power computing systems. Enabled by their in-memory event-driven computing abilities, hybrid memristive-Complementary... » read more

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