136 citations · 202 across the 13 of their papers we have counts for
11 papers · 1 filter
AMAX: Accuracy-Aware Multi-Loop Asymmetric Perforation for Heterogeneous Architectures
Amna Hassan, Paul Danielse, Anuj Pathania +2
Thermal constraints in heterogeneous multi-core systems can significantly degrade performance, as conventional techniques such as dynamic voltage and frequency scaling (DVFS) and t…
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 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…
Para-Pipe: Exploiting Hierarchical Operator Parallelism of ML Computational Graphs on SoCs
Yujie Zhang, Huiying Lan, Ehsan Aghapour +5
As edge-based deep learning applications become more complex, optimizing performance on heterogeneous System-on-Chips (SoCs) presents unique challenges. Traditional pipelining tech…
Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning
Yixian Shen, Zhiheng Yang, Qi Bi +6
Multimodal spatial reasoning often relies on long chains of intermediate textual and visual thoughts, where accumulating visual tokens and dense cross-modal attention incur substan…
Fast Transformer Inference on ARM-Based HMPSoCs
Hang Xu, Yixian Shen, Thanassis Giannetsos +1
Transformer models have set new performance standards for machine learning (ML) tasks. However, their resource-intensive deployment on resource-constrained edge devices for cloud-f…
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…
TCL: Enabling Fast and Efficient Cross-Hardware Tensor Program Optimization via Continual Learning
Chaoyao Shen, Linfeng Jiang, Yixian Shen +5
Deep learning (DL) compilers rely on cost models and auto-tuning to optimize tensor programs for target hardware. However, existing approaches depend on large offline datasets, inc…
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…