الباحثون

Athanasios Tziouvaras

المنشورات 2

نسخة أولية وصول مفتوح

Reinforcement Learning-Based Optimization of Workload-Aware Power Delivery Networks

Power Delivery Networks (PDNs) are critical components of modern VLSI chips, providing stable voltage levels while satisfying electromigration (EM) and IR-drop constraints. Conventional PDN design methodologies typically rely on worst-case assumptions, often resulting in over-provisioned networks and inefficient use of …

نسخة أولية وصول مفتوح

GPlaceRL: An Open-Source Graph Reinforcement Learning Framework for Detailed Placement

Reinforcement learning (RL) has emerged as a promising approach for placement optimization, particularly when combined with graph neural networks (GNNs) that capture circuit connectivity. However, most learning-based placement approaches focus on floorplanning, macro placement, or global placement, while detailed place …

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