Author's Latest Posts


Causal Inference for AMS Design (U. of Florida)


A new technical paper, "Causal AI For AMS Circuit Design: Interpretable Parameter Effects Analysis," was published by the University of Florida. Abstract "Analog-mixed-signal (AMS) circuits are highly non-linear and operate on continuous real-world signals, making them far more difficult to model with data-driven AI than digital blocks. To close the gap between structured design data (dev... » read more

Status of WBG Device Reliability in Automotive (U. Bremen et al.)


A new technical paper, "Reliability of Wide Bandgap Semiconductors for Automotive Applications," was published by the Universitat Bremen, Technische Universitat Chemnitz, BMW, Robert Bosch GmbH, Infineon, Semikron Danfoss, and FH Dortmund. Abstract "Wide bandgap (WBG) semiconductor devices offer tremendous advantages over their silicon counterparts. Automotive applications benefit particu... » read more

An Exploration of Agent Scaling for HLS Design Space Exploration (IBM)


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

Why Co-Packaged Optics Should be Viewed as an Architectural Commitment (UW-Madison, MIT et al.)


A new technical paper, "3D optoelectronics and co-packaged optics: when solving the wrong problems stalls deployment," by the University of Wisconsin, MIT, and Invictus Innovation EV Technology. Abstract "The rapid growth of AI and accelerator-driven workloads is forcing a fundamental rethinking of optical interconnect architectures in datacenters. Co-packaged optics and three-dimensional... » read more

CP-Based Lot Scheduling Solutions For a Semiconductor Manufacturing (Infineon, U. of Klagenfurt)


A new technical paper, "Quantifying the Global Impact of Constraint Programming Based Local Scheduling in Semiconductor Manufacturing," was published by Infineon and the University of Klagenfurt. Abstract "The efficiency of semiconductor frontend manufacturing highly depends on the optimization of resource allocation. In academic works, scheduling methods, i.e., based on Constraint Progra... » read more

Simulations of Silicon Spin Qubits Based on a GAAFET (Teikyo U., Riken)


A new technical paper, "Device/circuit simulations of silicon spin qubits based on a gate-all-around transistor," was published by Teikyo University and RIKEN. Abstract "We theoretically investigated the readout process of a spin–qubit structure based on a gate-all-around (GAA) transistor. Our study focuses on a logical qubit composed of two physical qubits. Different spin configuration... » read more

Integrating Error Propagation Theory Into the FMEDA Framework (Robert Bosch GmbH)


A new technical paper, "Quantifying Uncertainty in FMEDA Safety Metrics: An Error Propagation Approach for Enhanced ASIC Verification," was published by Robert Bosch GmbH. Abstract "Accurate and reliable safety metrics are paramount for functional safety verification of ASICs in automotive systems. Traditional FMEDA (Failure Modes, Effects, and Diagnostic Analysis) metrics, such as SPFM (... » read more

In-Depth Analysis of 187 Publications on Hardware Reverse Engineering (Ruhr U., MPI)


A new technical paper, "SoK: From Silicon to Netlist and Beyond Two Decades of Hardware Reverse Engineering Research," was published by the Ruhr University Bochum and the Max Planck Institute for Security and Privacy. Abstract "As hardware serves as the root of trust in modern computing systems, Hardware Reverse Engineering (HRE) is foundational for security assurance. In practice, HRE en... » read more

Systematic Analysis of CPU-Induced Slowdowns in Multi-GPU LLM Inference (Georgia Tech)


A new technical paper, "Characterizing CPU-Induced Slowdowns in Multi-GPU LLM Inference," was published by the Georgia Institute of Technology. Abstract "Large-scale machine learning workloads increasingly rely on multi-GPU systems, yet their performance is often limited by an overlooked component: the CPU. Through a detailed study of modern large language model (LLM) inference and servin... » read more

How SW and HW Vulnerabilities Can Complement LLM-Specific Algorithmic Attacks (UT Austin, Intel et al.)


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

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