Chip Industry Technical Paper Roundup: July 1


New technical papers recently added to Semiconductor Engineering’s library: [table id=426 /] Find more semiconductor research papers here. » read more

Chip Industry Week in Review


AI featured big at this week's Design Automation Conference (DAC) in San Francisco. Dozens of companies featured AI-related tools (see product section below), as well as significant improvements to existing tools and some entirely new approaches for designing chips. Among the highlights: Siemens unveiled an AI-enhanced toolset for the EDA design flow that enables customers to integrate the... » read more

GNN-Based Framework for Hardware Trojan Detection, Including RISC-V Cores


A new technical paper titled "TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs" was published by researchers at University of Connecticut and University of Minnesota. Abstract "hip manufacturing is a complex process, and to achieve a faster time to market, an increasing number of untrusted third-party tools and designs from around the world are being utilized. The use of th... » read more

Chip Industry’s Technical Paper Roundup: October 31


New technical papers added to Semiconductor Engineering’s library this week. [table id=159 /] More Reading Technical Paper Library home » read more

Measurement-Induced Quantum Information Phases On Up To 70 Superconducting Qubits (Google/Stanford)


A technical paper titled “Measurement-induced entanglement and teleportation on a noisy quantum processor” was published by researchers at Google Quantum AI, Google Research, Stanford University, University of Texas at Austin, Cornell University, University of Massachusetts, University of Connecticut, Auburn University, University of Technology Sydney, University of California, and Columbia... » read more

Technical Paper Round-Up: July 26


New technical papers added to Semiconductor Engineering’s library this week. [table id=41 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit f... » read more

HW/SW Co-Design to Configure DNN Models On Energy Harvesting Devices


New technical paper titled "EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System" was published by researchers at UT San Antonio, University of Connecticut, and Lehigh University. According to the abstract: "This paper proposes EVE, an automated machine learning (autoML) co-exploration framework to search for desired multi-models with shared weights for... » read more

Technical Paper Round-Up: March 15


Research is expanding across a variety of semiconductor-related topics, from security to flexible substrates and chiplets. Unlike in the past, when work was confined to some of the largest universities, that research work is now being spread across a much broader spectrum of schools on a global basic, including joint research involving schools whose names rarely appeared together. Among the ... » read more

Mapping Transformation Enabled High-Performance and Low-Energy Memristor-Based DNNs


Abstract: "When deep neural network (DNN) is extensively utilized for edge AI (Artificial Intelligence), for example, the Internet of things (IoT) and autonomous vehicles, it makes CMOS (Complementary Metal Oxide Semiconductor)-based conventional computers suffer from overly large computing loads. Memristor-based devices are emerging as an option to conduct computing in memory for DNNs to make... » read more

FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator


Abstract: "Recent work demonstrated the promise of using resistive random access memory (ReRAM) as an emerging technology to perform inherently parallel analog domain in-situ matrix-vector multiplication—the intensive and key computation in deep neural networks (DNNs). One key problem is the weights that are signed values. However, in a ReRAM crossbar, weights are stored as conductance of... » read more

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