collaborators

7 papers

cs.ET2026

DTCO of NOR-Type IGZO FeFETs for 3D Heterogeneous AI Memories: A Read-Centric Perspective

Yang Xiang, Zhuo Chen, Nicolò Ronchi +8

InGaZnO (IGZO)-channel FeFETs have attracted notable interest thanks to recent advances in endurance, opening up their application space for read-dominated AI memory tiers. This wo…

cs.AR2026

Technology solutions targeting the performance of gen-AI inference in resource constrained platforms

Joyjit Kundu, Joshua Klein, Aakash Patel +1

The rise of generative AI workloads, particularly language model inference, is intensifying on/off-chip memory pressure. Multimodal inputs such as video streams or images and downs…

cs.ET2025

LIMO: Low-Power In-Memory-Annealer and Matrix-Multiplication Primitive for Edge Computing

Amod Holla, Sumedh Chatterjee, Sutanu Sen +5

Combinatorial optimization (CO) underpins applications in science and engineering, ranging from logistics to electronic design automation. A classic example is the NP-complete Trav…

cs.AR2025

Physical Design Exploration of a Wire-Friendly Domain-Specific Processor for Angstrom-Era Nodes

Lorenzo Ruotolo, Lara Orlandic, Pengbo Yu +8

This paper presents the physical design exploration of a domain-specific processor (DSIP) architecture targeted at machine learning (ML), addressing the challenges of interconnect…

cs.ET2025

Thermal Implications of Non-Uniform Power in BSPDN-Enabled 2.5D/3D Chiplet-based Systems-in-Package using Nanosheet Technology

Yukai Chen, Massimiliano Di Todaro, Bjorn Vermeersch +5

Advances in nanosheet technologies have significantly increased power densities, exacerbating thermal management challenges in 2.5D/3D chiplet-based Systems-in-Package (SiP). While…

cs.DC2025

A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO

Jonas Svedas, Hannah Watson, Nathan Laubeuf +6

Distributed deep neural networks (DNNs) have become a cornerstone for scaling machine learning to meet the demands of increasingly complex applications. However, the rapid growth i…