tag: LLMs

Overflowing Zoo: The Power Of Compilers
By Steve Roddy - 16 Oct, 2025 - Comments: 0

The term “model zoo” first gained prominence in the world of Artificial Intelligence/Machine Learning (AI/ML) beginning in the 2016-2017 timeframe. Originally used to describe open-source public repositories of working AI models — the most prominent of which today is Hugging Face — the term has since been adopted by nearly all vendors of AI chips and licensable Neural Processors Units (... » read more

Heterogeneous System With Specialized HW For Disaggregated LLM Inference (Princeton Univ., Univ. of Washington)
By Technical Paper Link - 14 Oct, 2025 - Comments: 0

A new technical paper titled "SPAD: Specialized Prefill and Decode Hardware for Disaggregated LLM Inference" was published by researchers at Princeton University and University of Washington. Abstract "Large Language Models (LLMs) have gained popularity in recent years, driving up the demand for inference. LLM inference is composed of two phases with distinct characteristics: a compute-boun... » read more

Analog IMC Attention Mechanism For Fast And Energy-Efficient LLMs (FZJ, RWTH Aachen)
By Technical Paper Link - 15 Sep, 2025 - Comments: 0

A new technical paper titled "Analog in-memory computing attention mechanism for fast and energy-efficient large language models" was published by researchers at Forschungszentrum Jülich and RWTH Aachen. Abstract "Transformer networks, driven by self-attention, are central to large language models. In generative transformers, self-attention uses cache memory to store token projec... » read more

What Do LLMs Want from Hardware
By Geoff Tate - 08 Sep, 2025 - Comments: 0

Figure 1: Noam Shazeer, Google Gemini vice president, presented this in his Hot Chips 2025 talk. Noam Shazeer is Google’s vice president of engineering for Gemini, their LLM competitor to ChatGPT. He talked recently at Hot Chips: “Predictions for the Next Phase of AI." He has worked on LLMs for a decade since inventing the transformer model in 2017. As his slide says, LLMs can take adv... » read more

An LLM-based Agentic Framework For Photonic IC Design Automation (U. of Toronto, Max Planck, MIT Et Al.)
By Technical Paper Link - 26 Aug, 2025 - Comments: 0

A new technical paper titled "AI Agents for Photonic Integrated Circuit Design Automation" was published by researchers at the University of Toronto, Max Planck Institute of Microstructure Physics, GDSFactory, MIT and Axiomatic_AI Inc. Abstract "We present Photonics Intelligent Design and Optimization (PhIDO), a multi-agent framework that converts natural-language photonic integrated circui... » read more

Microservice-Based LLM Agents Enable EDA Flow Automation (Duke Univ. and Univ. of Maryland)
By Technical Paper Link - 15 Aug, 2025 - Comments: 0

A new technical paper titled "AutoEDA: Enabling EDA Flow Automation through Microservice-Based LLM Agents" was published by researchers at Duke University and University of Maryland. Abstract "Modern Electronic Design Automation (EDA) workflows, especially the RTL-to-GDSII flow, require heavily manual scripting and demonstrate a multitude of tool-specific interactions which limits scalabili... » read more

AI, From A To Z
By Ed Sperling - 15 Aug, 2025 - Comments: 0

First in a seven-part series: What's the difference between AI, ML, DL, LLMs, and agentic AI? Is it truly revolutionary, or is it an evolutionary series of steps that have enabled machines to do much more than in the past? Jon Herlocker, vice president and general manager of software analytics at Cohu, talks about the evolution of AI over nearly 70 years, the chain of innovation that has enable... » read more

Reliable Training Data Paramount To AI Model Success
By Ann Mutschler - 14 Aug, 2025 - Comments: 0

AI systems are increasingly being integrated into safety- and mission-critical applications ranging from automotive to health care and industrial IoT, stepping up the need for training data that is reliable, secure, and which is generated from trusted sources. AI activity is growing exponentially, as everybody tries to figure out how to apply it to their domain, application, or workload. In ... » read more

What’s Different About HBM4
By Ed Sperling - 11 Aug, 2025 - Comments: 0

Memory bandwidth is limiting the flow of huge datasets that are needed to train AI models. There is much more data to process, store, and retrieve, but the speed at which that data moves through high-bandwidth memory (HBM) stacks is significantly lower than the speed at which data can be processed. Frank Ferro, group director for product management at Cadence, talks about the new HBM4 standard,... » read more

Security Tradeoffs: A Difficult Balance
By Ann Mutschler - 06 Aug, 2025 - Comments: 0

Experts At The Table: Semiconductor Engineering sat down to discuss hardware security challenges, including new threat models from AI-based attacks, with Nicole Fern, principal security analyst at Keysight; Serge Leef, AI-For-Silicon strategist at Microsoft; Scott Best, senior director for silicon security products at Rambus; Lee Harrison, director of Tessent Automotive IC Solutions at Sieme... » read more

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