tag: LLMs

Formal Verification’s Value Grows
By Brian Bailey - 05 Nov, 2025 - Comments: 0

Experts at the table: Semiconductor Engineering sat down to discuss why formal verification is becoming more important, with Ashish Darbari, CEO for Axiomise; Jin Zhang, product management group director for the Verification Group at Cadence; Sean Safarpour, executive director for R&D at Synopsys; and Jeremy Levitt, principal engineer for Digital Verification Technology at Siemens EDA. Wha... » read more

Small Vs. Large Language Models
By Ed Sperling - 03 Nov, 2025 - Comments: 0

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal for small language models (SLMs) — roughly 10 billion parameters or less, compared to more than a trillion parameters in the biggest LLMs — was to leverage them exclusively for inferencing. In... » read more

Multimodal LLM Assistant for Chip Physical Design (National Taiwan Univ., UCLA, NVIDIA)
By Technical Paper Link - 28 Oct, 2025 - Comments: 0

A new technical paper titled "Multimodal Chip Physical Design Engineer Assistant" was published by researchers at National Taiwan University, University of California, Los Angeles and NVIDIA Research. Abstract "Modern chip physical design relies heavily on Electronic Design Automation (EDA) tools, which often struggle to provide interpretable feedback or actionable guidance for improving ro... » read more

Unlocking Clarity: Keyphrase Trees Bring Structure To AI Text Analysis
By Mohamed Abdelkarim - 27 Oct, 2025 - Comments: 0

By Amr Hegazy, Mohamed Abdelkarim, and Reem El Adawi In the vast digital landscape of information, from intricate design specifications to extensive patent literature and complex verification reports, extracting meaningful insights often feels like searching for a needle in a haystack. This challenge is particularly acute in the semiconductor industry, where critical details are buried with... » read more

GDDR7 Tackles Massive-Context AI Inference
By Nidish Kamath - 16 Oct, 2025 - Comments: 0

The AI hardware landscape is evolving at breakneck speed, and memory technology is at the heart of this transformation. NVIDIA’s recent announcement of Rubin CPX, a new class of GPU purpose-built for massive-context inference, underscores this trend. Rubin CPX is designed to tackle workloads that require reasoning across millions of tokens. Use cases include long-form generative video, comple... » read more

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

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