8 citations · 9 across the 8 of their papers we have counts for
13 papers · 1 filter
Design Space Exploration of Reinforcement Learning Configurations for Post-Legalization Placement
Foteini Oikonomou, Maria Pantazi-Kypraiou, George Goudroumanis +5
Graph Neural Networks (GNNs) and Reinforcement Learning (RL) have recently been explored for VLSI placement optimization, but their effectiveness for post-legalization placement re…
On the Impact of Degradation-Balanced Scheduling in Manycore Systems
Maria Pantazi-Kypraiou, George Goudroumanis, George Floros +2
Electromigration degradation in manycore systems depends strongly on how runtime workload is distributed across cores. Task placement affects power, temperature, and current densit…
A Pipelined FPGA Architecture for Banded Sparse Matrix Dense Matrix Multiplication in Longformer
Phillip Pramberger, Athanasios Tziouvaras, Shreejith Shanker +1
Sparse attention mechanisms have become increasingly important for transformer models processing long input sequences due to their lower computational and memory complexity compare…
GPlaceRL: An Open-Source Graph Reinforcement Learning Framework for Detailed Placement
Pavlos Stoikos, Foteini Oikonomou, Christos Poulos +5
Reinforcement learning (RL) has emerged as a promising approach for placement optimization, particularly when combined with graph neural networks (GNNs) that capture circuit connec…
A Physics-Guided Transformer Framework for Electromigration Analysis in Multi-Segment Interconnects
Pavlos Stoikos, Anuj Pathania, George Floros
As technology scales to smaller nodes, increasing current densities make electromigration (EM) one of the dominant reliability challenges in on-chip interconnects. Accurate transie…
Reinforcement Learning-Based Optimization of Workload-Aware Power Delivery Networks
Oran Hayes, Maria Pantazi-Kypraiou, Athanasios Tziouvaras +4
Power Delivery Networks (PDNs) are critical components of modern VLSI chips, providing stable voltage levels while satisfying electromigration (EM) and IR-drop constraints. Convent…
Co-Optimizing Graph Sparsification and Approximate Computing for Energy-Efficient FPGA-Based GCN Inference
Nathaniel Kaye Mellor, Shreejith Shanker, George Floros
Graph Convolutional Networks (GCNs) have emerged as a powerful framework for learning from graph-structured data, yet their deployment on resource-constrained edge platforms remain…
Constrained Bayesian Optimization for Hierarchical Federated Learning in IoT Networks for Plant Disease Classification
Athanasios Papanikolaou, Athanasios Tziouvaras, Apostolos Xenakis +6
The deployment of Hierarchical Federated Learning (HFL) in resource-constrained Internet of Things (IoT) environments requires careful configuration to balance predictive performan…
Design-Oriented Modeling of TSV Substrate Noise Coupling to Ring VCOs
Ilias Exouzidis, Alberto Garcia-Ortiz, George Floros +1
Through-silicon vias (TSVs) enable dense vertical interconnects in 3D-IC and chiplet systems, but their metal-oxide-silicon structure introduces significant parasitic coupling path…
Workload-Aware Early-Stage Power Delivery Network Optimization via Architectural Power Traces
Oran Hayes, Maria Pantazi-Kypraiou, Athanasios Tziouvaras +4
Power Delivery Networks (PDNs) are critical for maintaining voltage integrity in modern multiprocessor systems. Conventional early-stage PDN planning relies on static or worst-case…
Performance and Energy Trade-Off Analysis of Hierarchical Federated Learning for Plant Disease Classification
Athanasios Papanikolaou, Athanasios Tziouvaras, Pavlos Stoikos +6
Early detection of plant diseases is critical for improving crop productivity, while it also facilitates the foundations of precision agriculture. Recent advances in distributed de…
Active Imitation Learning for Thermal- and Kernel-Aware LFM Inference on 3D S-NUCA Many-Cores
Yixian Shen, Chaoyao Shen, Jan Deen +3
Large Foundation Model (LFM) inference is both memory- and compute-intensive, traditionally relying on GPUs. However, the limited availability and high cost have motivated the adop…
Multi-Partner Project: COIN-3D -- Collaborative Innovation in 3D VLSI Reliability
George Rafael Gourdoumanis, Fotoini Oikonomou, Maria Pantazi-Kypraiou +10
As semiconductor manufacturing advances from the 3-nm process toward the sub-nanometer regime and transitions from FinFETs to gate-all-around field-effect transistors (GAAFETs), th…