AI Design Reshapes Data Management


Key takeaways: Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and inference workloads grow, data movement, congestion, and energy efficiency become the dominant challenges, often surpassing raw compute capability. Proprietary and comple... » read more

Performance And Energy Characterization Of A Commercial Compute-in-SRAM Device (Cornell, USC, MIT, GSI)


A new technical paper titled "Characterizing and Optimizing Realistic Workloads on a Commercial Compute-in-SRAM Device" was published by researchers at Cornell University, USC, MIT and GSI Technology Inc. Abstract "Compute-in-SRAM architectures offer a promising approach to achieving higher performance and energy efficiency across a range of data-intensive applications. However, prior evalu... » read more

LLM-Powered Automatic VLSI Design Flow Tuning Framework


A new technical paper titled "CROP: Circuit Retrieval and Optimization with Parameter Guidance using LLMs" was published by researchers at Duke University and Synopsys. Abstract "Modern very large-scale integration (VLSI) design requires the implementation of integrated circuits using electronic design automation (EDA) tools. Due to the complexity of EDA algorithms, the vast parameter space... » read more

HW Security: Multi-Agent AI Assistant Leveraging LLMs To Automate Key Stages of SoC Security Verification (U. of Florida)


A new technical paper titled "SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models" was published by researchers at University of Florida. Abstract "Ensuring the security of complex system-on-chips (SoCs) designs is a critical imperative, yet traditional verification techniques struggle to keep pace due to significant challenges in automation, scalability, c... » read more

LLM-based Agentic Framework Automating HW Security Threat Modeling And Test Plan Generation (U. of Florida)


A new technical paper titled "ThreatLens: LLM-guided Threat Modeling and Test Plan Generation for Hardware Security Verification" was published by researchers at University of Florida. Abstract "Current hardware security verification processes predominantly rely on manual threat modeling and test plan generation, which are labor-intensive, error-prone, and struggle to scale with increasing ... » read more