tag: LLMs

Silent Data Corruption: A Major Reliability Challenge in Large-Scale LLM Training (TU Berlin)
By Technical Paper Link - 12 Apr, 2026 - Comments: 0

A new technical paper, "Exploring Silent Data Corruption as a Reliability Challenge in LLM Training," was published by researchers at Technische Universitat Berlin. Abstract "As Large Language Models (LLMs) scale in size and complexity, the consequences of failures during training become increasingly severe. A major challenge arises from Silent Data Corruption (SDC): hardware-induced faults... » read more

Automated Security Assertion Generation Using LLMs (U. of Florida)
By Technical Paper Link - 03 Apr, 2026 - Comments: 0

A new technical paper, "Assertain: Automated Security Assertion Generation Using Large Language Models," was published by University of Florida. Abstract "The increasing complexity of modern system-on-chip designs amplifies hardware security risks and makes manual security property specification a major bottleneck in formal property verification. This paper presents Assertain, an automated ... » read more

An Exploration of Agent Scaling for HLS Design Space Exploration (IBM)
By Technical Paper Link - 31 Mar, 2026 - Comments: 0

A new technical paper, "Agent Factories for High Level Synthesis: How Far Can General-Purpose Coding Agents Go in Hardware Optimization?" was published by IBM. Abstract "We present an empirical study of how far general-purpose coding agents – without hardware-specific training – can optimize hardware designs from high-level algorithmic specifications. We introduce an agent factory, a ... » read more

How SW and HW Vulnerabilities Can Complement LLM-Specific Algorithmic Attacks (UT Austin, Intel et al.)
By Technical Paper Link - 20 Mar, 2026 - Comments: 0

A new technical paper, "Cascade: Composing Software-Hardware Attack Gadgets for Adversarial Threat Amplification in Compound AI Systems," was published by the University of Texas, Austin, Intel Labs, Symmetry Systems, Microsoft and Georgia Tech. Abstract "Rapid progress in generative AI has given rise to Compound AI systems - pipelines comprised of multiple large language models (LLM), so... » read more

A Framework That Generates Chip Layouts Directly From Natural Language Specifications (U. of Bristol, RAL)
By Technical Paper Link - 09 Mar, 2026 - Comments: 1

A new technical paper, "NL2GDS: LLM-aided interface for Open Source Chip Design," was published by researchers at University of Bristol and Rutherford Appleton Laboratory. Abstract "The growing complexity of hardware design and the widening gap between high-level specifications and register-transfer level (RTL) implementation hinder rapid prototyping and system design. We introduce NL2GDS (... » read more

Limiting AI/ML Tools To Ensure Physical AI Safety, Security
By Liz Allan - 05 Mar, 2026 - Comments: 0

Key Takeaways: AI-based tools can help monitor physical AI systems and LLMs, but human oversight is still needed to avoid false positives, bias, and other anomalies. For autonomous vehicles and robots, edge case scenarios and understanding human values are weak points, especially as moral and social values change over time. AI tools are growing and becoming increasingly helpful for c... » read more

Survey of GenAI Across the Full Computing Stack, From SW To Silicon (Harvard)
By Technical Paper Link - 22 Feb, 2026 - Comments: 0

Harvard University researchers published "GenAI for Systems: Recurring Challenges and Design Principles from Software to Silicon." Abstract "Generative AI is reshaping how computing systems are designed, optimized, and built, yet research remains fragmented across software, architecture, and chip design communities. This paper takes a cross-stack perspective, examining how generative models... » read more

The On-Device LLM Revolution
By Steve Roddy - 20 Feb, 2026 - Comments: 0

The AI world is experiencing a fundamental shift. After years of cloud-centric inference dominated by massive data center GPUs, we're witnessing an accelerating migration of language models to edge devices. These are not the trillion-parameter behemoths that require server farms, but the "Goldilocks zone" models: 3B to 30B parameters — large enough to deliver genuinely useful AI capabilities,... » read more

LLM-Based Learning Platform For Chip Design Education (RPTU)
By Technical Paper Link - 15 Feb, 2026 - Comments: 0

RPTU University of Kaiserslautern-Landau researchers published "From RTL to Prompt Coding: Empowering the Next Generation of Chip Designers through LLMs." Abstract "This paper presents an LLM-based learning platform for chip design education, aiming to make chip design accessible to beginners without overwhelming them with technical complexity. It represents the first educational platform... » read more

Scaling llama.cpp On Neoverse N2: Solving Cross-NUMA Performance Issues
By Bolt Liu - 12 Feb, 2026 - Comments: 0

This blog post explains the cross-NUMA memory access issue that occurs when you run llama.cpp in Neoverse. It also introduces a proof-of-concept patch that addresses this issue and can provide up to a 55% performance increase for text generation when you run the llama3_Q4_0 model on the ZhuFeng Neoverse system. Cross-NUMA memory access problem In llama.cpp, performance drops when the number o... » read more

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