Semiconductor Engineering4h
Barriers To Chiplet Sockets
Perfection sometimes stands in the way of progress, and there is evidence this may be happening with chiplets. It may be time ...
Semiconductor Engineering3h
Data Routing In Heterogeneous Chip Designs
Ensuring data gets to where it’s supposed to go at exactly the right time is a growing challenge for design engineers and architects developing heterogeneous systems. There is more data moving around ...
Semiconductor Engineering2d
Fine-Grained Functional Partitioning For Low Level SRAM Cache in 3D-IC designs (imec)
A new technical paper titled “Towards Fine-grained Partitioning of Low-level SRAM Caches for Emerging 3D-IC Designs” was ...
Semiconductor Engineering2d
Memristors: Flexible Behavioral Model ( Israel Institute of Technology)
A Compact Behavioral Model for Volatile Memristors” was published by researchers at Technion – Israel Institute of Technology ...
Semiconductor Engineering5d
Optimizing Wafer Edge Processes For Chip Stacking
Several critical processes address wafer flatness, wafer edge defects and what's needed to enable bonded wafer stacks.
Semiconductor Engineering4d
Using AI To Glue Disparate IC Ecosystem Data
Why the chip industry is so focused on large language models for designing and manufacturing chips, and what problems need to ...
Semiconductor Engineering6d
Models for Both Strained and Unstrained GAA FETs Using Neural Networks
A new technical paper titled “Impact of Strain on Sub-3 nm Gate-all-Around CMOS Logic Circuit Performance Using a Neural ...
Semiconductor Engineering3d
Dualtronics: Photonic Devices on the Cation Face and Electronic Devices on the Anion Face of the Same Wafer
A new technical paper titled “Using both faces of polar semiconductor wafers for functional devices” was published by ...
Semiconductor Engineering4d
RAG-Enabled AI Stops Hallucinations, Adds Sources
For many use cases, fine-tuning is the last step in turning a foundation model into a specialist resource. However, to ensure ...
Semiconductor Engineering6d
Characteristics and Potential HW Architectures for Neuro-Symbolic AI
A new technical paper titled “Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture” ...
Semiconductor Engineering6d
Research Bits: Sept. 24
“While experiments have shown devices can retain information for over 10 years, the models used in the community show that ...
Semiconductor Engineering3d
Hardware Acceleration Approach for KAN Via Algorithm-Hardware Co-Design
A new technical paper titled “Hardware Acceleration of Kolmogorov-Arnold Network (KAN) for Lightweight Edge Inference” was ...