8 citations · 9 across the 8 of their papers we have counts for
16 papers
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…
A Fast Semi-Analytical Approach for Transient Electromigration Analysis of Interconnect Trees using Matrix Exponential
Pavlos Stoikos, George Floros, Dimitrios Garyfallou +2
As integrated circuit technologies are moving to smaller technology nodes, Electromigration (EM) has become one of the most challenging problems facing the EDA industry. While nume…
The Extended and Asymmetric Extended Krylov Subspace in Moment-Matching-Based Order Reduction of Large Circuit Models
Pavlos Stoikos, Dimitrios Garyfallou, George Floros +2
The rapid growth of circuit complexity has rendered Model Order Reduction (MOR) a key enabler for the efficient simulation of large circuit models. MOR techniques based on moment-m…
Exploiting Extended Krylov Subspace for the Reduction of Regular and Singular Circuit Models
Chrysostomos Chatzigeorgiou, Dimitrios Garyfallou, George Floros +2
During the past decade, Model Order Reduction (MOR) has become key enabler for the efficient simulation of large circuit models. MOR techniques based on moment-matching are well es…