Dimitrios Stamoulis
Dimitrios Stamoulis
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Single-path nas: Designing hardware-efficient convnets in less than 4 hours
D Stamoulis, R Ding, D Wang, D Lymberopoulos, B Priyantha, J Liu, ...
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019
NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks
E Cai, DC Juan, D Stamoulis, D Marculescu
Asian Conference on Machine Learning, 622-637, 2017
Hyperpower: Power-and memory-constrained hyper-parameter optimization for neural networks
D Stamoulis, E Cai, DC Juan, D Marculescu
2018 Design, Automation & Test in Europe Conference & Exhibition (DATE), 19-24, 2018
Designing adaptive neural networks for energy-constrained image classification
D Stamoulis, TW Chin, AK Prakash, H Fang, S Sajja, M Bognar, ...
Proceedings of the International Conference on Computer-Aided Design, 1-8, 2018
Hardware-aware machine learning: modeling and optimization
D Marculescu, D Stamoulis, E Cai
Proceedings of the International Conference on Computer-Aided Design, 1-8, 2018
Exploring aging deceleration in FinFET-based multi-core systems
E Cai, D Stamoulis, D Marculescu
2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-8, 2016
Can we guarantee performance requirements under workload and process variations?
D Stamoulis, D Marculescu
Proceedings of the 2016 International Symposium on Low Power Electronics and …, 2016
Capturing true workload dependency of bti-induced degradation in cpu components
D Stamoulis, S Corbetta, D Rodopoulos, P Weckx, P Debacker, BH Meyer, ...
2016 International Great Lakes Symposium on VLSI (GLSVLSI), 373-376, 2016
Efficient reliability analysis of processor datapath using atomistic bti variability models
D Stamoulis, D Rodopoulos, BH Meyer, D Soudris, F Catthoor, Z Zilic
Proceedings of the 25th edition on Great Lakes Symposium on VLSI, 57-62, 2015
Profit:Priority and Power/Performance Optimization for Many-Core Systems
Z Chen, D Stamoulis, D Marculescu
IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2017
Understanding timing impact of BTI/RTN with massively threaded atomistic transient simulations
D Rodopoulos, D Stamoulis, G Lyras, D Soudris, F Catthoor
2014 IEEE International Conference on IC Design & Technology, 1-4, 2014
Single-path mobile automl: Efficient convnet design and nas hyperparameter optimization
D Stamoulis, R Ding, D Wang, D Lymberopoulos, NB Priyantha, J Liu, ...
IEEE Journal of Selected Topics in Signal Processing, 2020
Single-Path NAS: Device-Aware Efficient ConvNet Design
D Stamoulis, R Ding, D Wang, D Lymberopoulos, B Priyantha, J Liu, ...
arXiv preprint arXiv:1905.04159, 2019
Enhancing precipitation models by capturing multivariate and multiscale climate dynamics
R Ding, D Stamoulis, K Bhardwaj, D Marculescu, R Marculescu
Proceedings of the 3rd International Workshop on Cyber-Physical Systems for …, 2017
Linear regression techniques for efficient analysis of transistor variability
D Stamoulis, D Rodopoulos, BH Meyer, D Soudris, Z Zilic
2014 21st IEEE international conference on electronics, circuits and systems …, 2014
Towards Latency-aware DNN Optimization with GPU Runtime Analysis and Tail Effect Elimination
F Yu, Z Xu, T Shen, D Stamoulis, L Shangguan, D Wang, R Madhok, ...
arXiv preprint arXiv:2011.03897, 2020
Hardware-Aware AutoML for Efficient Deep Learning Applications
D Stamoulis
Carnegie Mellon University, 2020
Time-efficient modeling and simulation of true workload dependency for bti-induced degradation in processor-level platform specifications
S Corbetta, P Weckx, D Rodopoulos, D Stamoulis, F Catthoor
Harnessing Performance Variability in Embedded and High-performance Many …, 2019
Computational Approaches for Incorporating Short-and Long-Term Dynamics in Smart Water Networks
K Bhardwaj, D Stamoulis, R Ding, D Marculescu, R Marculescu
Smart Water Grids, 297-323, 2018
Efficient variability analysis of arithmetic units using linear regression techniques
D Stamoulis, K Tsoumanis, D Rodopoulos, BH Meyer, K Pekmestzi, ...
Analog Integrated Circuits and Signal Processing 87 (2), 249-261, 2016
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