Giuseppe Maria Sarda

According to our database, Giuseppe Maria Sarda authored at least 7 papers between 2022 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

DIANA: An End-to-End Hybrid DIgital and ANAlog Neural Network SoC for the Edge.

Pouya Houshmand, Giuseppe Maria Sarda, Vikram Jain, Kodai Ueyoshi, Ioannis A. Papistas, Man Shi, Qilin Zheng, Debjyoti Bhattacharjee, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst

IEEE J. Solid State Circuits, 2023

AIMC Modeling and Parameter Tuning for Layer-Wise Optimal Operating Point in DNN Inference.

Iman Dadras, Giuseppe Maria Sarda, Nathan Laubeuf, Debjyoti Bhattacharjee, Arindam Mallik

IEEE Access, 2023

Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference.

Matteo Risso, Alessio Burrello, Giuseppe Maria Sarda, Luca Benini, Enrico Macii, Massimo Poncino, Marian Verhelst, Daniele Jahier Pagliari

Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2023

Optimising GPGPU Execution Through Runtime Micro-Architecture Parameter Analysis.

Giuseppe Maria Sarda, Nimish Shah, Debjyoti Bhattacharjee, Peter Debacker, Marian Verhelst

Proceedings of the IEEE International Symposium on Workload Characterization, 2023

HTVM: Efficient Neural Network Deployment On Heterogeneous TinyML Platforms.

Josse Van Delm, Maarten Vandersteegen, Alessio Burrello, Giuseppe Maria Sarda, Francesco Conti, Daniele Jahier Pagliari, Luca Benini, Marian Verhelst

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

DIANA: An End-to-End Energy-Efficient Digital and ANAlog Hybrid Neural Network SoC.

Kodai Ueyoshi, Ioannis A. Papistas, Pouya Houshmand, Giuseppe Maria Sarda, Vikram Jain, Man Shi, Qilin Zheng, Juan Sebastian Piedrahita Giraldo, Peter Vrancx, Jonas Doevenspeck, Debjyoti Bhattacharjee, Stefan Cosemans, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst

Proceedings of the IEEE International Solid-State Circuits Conference, 2022

CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for Energy-Efficient Low-precision Deep Convolutional Neural Networks.

Muhammad Abdullah Hanif, Giuseppe Maria Sarda, Alberto Marchisio, Guido Masera, Maurizio Martina, Muhammad Shafique

Proceedings of the International Joint Conference on Neural Networks, 2022