Research Bits: Dec. 3


Self-assembly of mixed-metal oxide arrays Researchers from North Carolina State University and Iowa State University demonstrated a technique for self-assembling electronic devices. The proof-of-concept work was used to create diodes and transistors with high yield and could be used for more complex electronic devices. “Our self-assembling approach is significantly faster and less expensi... » read more

Chip Industry Technical Paper Roundup: Dec. 3


New technical papers recently added to Semiconductor Engineering’s library: [table id=391 /] » read more

Chiplet-Based NPUs to Accelerate Vehicular AI Perception Workloads


A new technical paper titled "Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception" was published by researchers at UC Irvine. Abstract "We study the application of emerging chiplet-based Neural Processing Units to accelerate vehicular AI perception workloads in constrained automotive settings. The motivation stems from how chiplets technology i... » read more

Chip Companies Play Bigger Role In Shaping University Curricula


A shortage of senior engineers with the necessary skills and experience is forcing companies to hire and train fresh graduates, a more time-consuming process but one that allows them to rise through the ranks using the companies' preferred technology and systems. Universities and companies share the goal of helping a graduate become productive in the workplace as quickly as possible, and the... » read more

Chip Industry Week In Review


Intel CEO Pat Gelsinger retired on Dec. 1, according to the company. He will be replaced by two interim co-CEOs, David Zinsner, who also continues to serve as CFO  and Michelle Johnston Holthaus, who has been named CEO of Intel Products. In addition, Frank Yeary was named interim executive chairman. Intel has been under pressure investors as non-traditional rivals, including Arm and NVIDIA, co... » read more

STCO for Dense Edge Architectures using 3D Integration and NVM (imec,, et al.)


A new technical paper titled "System-Technology Co-Optimization for Dense Edge Architectures using 3D Integration and Non-Volatile Memory" was published by researchers at imec, INESC-ID, Université Libre de Bruxelles, et al. "In this paper, we present an system-technology co-optimization (STCO) framework that interfaces with workload-driven system scaling challenges and physical design-enab... » read more

Gate-All-Around: TCAD and DTCO Approach To Evaluate Power and Performance (imec, et al.)


A new technical paper titled "Exploring GAA-Nanosheet, Forksheet and GAA-Forksheet Architectures: a TCAD-DTCO Study at 90 nm & 120 nm Cell Height" was published by imec, Huawei Technologies and Global TCAD Solutions. Abstract "This study presents a Technology Computer Aided Design (TCAD) and comprehensive Design-Technology Co-Optimization (DTCO) approach to evaluate and enhance power an... » read more

Aging, Complexity, And AI In Analog Design


Experts at the Table: Semiconductor Engineering sat down to discuss abstraction in analog vs. digital, how analog circuits age, the growing role of AI, and why there is so much margin in analog designs, with Mo Faisal, president and CEO of Movellus; Hany Elhak, executive director of product management at Synopsys; Cedric Pujol, product manager at Keysight; and Pradeep Thiagarajan, principal pro... » read more

Critical Design Considerations For High-Bandwidth Chiplet Interconnects (TSMC)


A new technical paper titled "High-Bandwidth Chiplet Interconnects for Advanced Packaging Technologies in AI/ML Applications: Challenges and Solutions" was published by researchers at TSMC. Abstract: "The demand for chiplet integration using 2.5D and 3D advanced packaging technologies has surged, driven by the exponential growth in computing performance required by Artificial Intelligence a... » read more

Pooling CPU Memory for LLM Inference With Lower Latency and Higher Throughput (UC Berkeley)


A new technical paper titled "Pie: Pooling CPU Memory for LLM Inference" was published by researchers at UC Berkeley. Abstract "The rapid growth of LLMs has revolutionized natural language processing and AI analysis, but their increasing size and memory demands present significant challenges. A common solution is to spill over to CPU memory; however, traditional GPU-CPU memory swapping ofte... » read more

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