Author's Latest Posts


A GPU Microarchitecture Optimized for Fully Homomorphic Encryption


Researchers from Boston University, Northeastern University, KAIST, and University of Murcia, et al. have released “FHECore: Rethinking GPU Microarchitecture for Fully Homomorphic Encryption”. Abstract“Fully Homomorphic Encryption (FHE) enables computation directly on encrypted data but incurs massive computational and memory overheads, often exceeding plaintext execution by seve... » read more

An FPGA-based Accelerator Addressing Bottlenecks in GNN Preprocessing (KAIST et al.)


A new technical paper "AutoGNN: End-to-End Hardware-Driven Graph Preprocessing for Enhanced GNN Performance" was published by researchers at KAIST, Panmnesia, Peking University, Hanyang University, and Pennsylvania State University. Abstract "Graph neural network (GNN) inference faces significant bottlenecks in preprocessing, which often dominate overall inference latency. We introduce Au... » read more

CMOS-Compatible Approach to Extending the Spectral Response of Oxide Semiconductors


A new technical paper titled "Sputtering-driven formation of interstitial oxygen for intrinsic NIR detection in IGZO phototransistor" was published by researchers at KICET, Korea University, Yonsei University, and Argonne National Lab. Abstract "Amorphous indium gallium zinc oxide (a-IGZO) is a promising wide-bandgap semiconductor for large-area optoelectronics; however, its intrinsic ins... » read more

Survey of DL-Based LiDAR Super-Resolution For Autonomous Driving (University College London)


University College London researchers published "A Comprehensive Survey on Deep Learning-Based LiDAR Super-Resolution for Autonomous Driving." Abstract "LiDAR sensors are often considered essential for autonomous driving, but high-resolution sensors remain expensive while affordable low-resolution sensors produce sparse point clouds that miss critical details. LiDAR super-resolution addre... » read more

Three New ALD/MLD Processes for Co-organic Thin Films (Aalto University, RUB et al.)


A new technical paper, "Amido-Amine Co(II) Precursor-Based Atomic/Molecular Layer Deposition Processes for Cobalt-Organic Thin Films and Their Thermal Conversion to CoO Thin Films," was published by researchers at Aalto University, Ruhr University Bochum, Tyndall National Institute, ESRF et al. "Atomic/molecular layer deposition (ALD/MLD) offers a comprehensive process and application portfo... » read more

Ultrafast Laser Filamentation Dictates Energy Deposition in Narrow-Gap Semiconductors


A new technical paper, "Extreme optical nonlinearities unveiled by ultrafast laser filamentation in semiconductors," was published by researchers at Abbe Center of Photonics, Laboratoire Hubert Curien et al. Abstract "Sky-high optical nonlinearities make semiconductors ideal platforms for multifunctional photonic devices. The fabrication of such complex devices could greatly benefit from ... » read more

3D Atomic-Scale Metrology of Strain Relaxation And Roughness in GAAFETs Via Electron Ptychography (Cornell, ASM, TSMC)


A new technical paper, "3D atomic-scale metrology of strain relaxation and roughness in Gate-All-Around transistors via electron ptychography," was published by researchers at Cornell University, ASM and TSMC. Abstract "Next-generation semiconductor devices are adopting three-dimensional (3D) architectures with feature sizes in the few-nanometer regime, creating a need for atomic-scale me... » read more

ReRAM-based Neo-Hebbian Synapses For Training Neuromorphic HW (IIT Madras, UCSB)


A new technical paper, "NeoHebbian synapses to accelerate online training of neuromorphic hardware," was published by researchers at IIT Madras and UC Santa Barbara. Abstract "Neuromorphic systems that employ advanced synaptic learning rules, such as the three-factor learning rule, require synaptic devices of increased complexity. Herein, a novel neoHebbian artificial synapse utilizing ReRA... » read more

Survey of GenAI Across the Full Computing Stack, From SW To Silicon (Harvard)


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

Accelerator Architecture: Fusion-Aware Mapper (MIT)


Researchers from MIT published "Fast and Fusiest: An Optimal Fusion-Aware Mapper for Accelerator Modeling and Evaluation." Abstract "The latency and energy of tensor algebra accelerators depend on how data movement and operations are scheduled (i.e., mapped) onto accelerators, so determining the potential of an accelerator architecture requires both a performance model and a mapper to sea... » read more

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