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Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference
In corso di stampa Risso, Matteo; Burrello, Alessio; Maria Sarda, Giuseppe; Benini, Luca; Macii, Enrico; Poncino, Massimo; Verhelst, Marian; JAHIER PAGLIARI, Daniele
Deep Neural Network Architecture Search for Accurate Visual Pose Estimation aboard Nano-UAVs
2023 Cereda, Elia; Crupi, Luca; Risso, Matteo; Burrello, Alessio; Benini, Luca; Giusti, Alessandro; Jahier Pagliari, Daniele; Palossi, Daniele
Energy-efficient Wearable-to-Mobile Offload of ML Inference for PPG-based Heart-Rate Estimation
2023 Burrello, Alessio; Risso, Matteo; Tomasello, Noemi; Chen, Yukai; Benini, Luca; Macii, Enrico; Poncino, Massimo; JAHIER PAGLIARI, Daniele
EEGformer: Transformer-Based Epilepsy Detection on Raw EEG Traces for Low-Channel-Count Wearable Continuous Monitoring Devices
2022 Busia, Paola; Cossettini, Andrea; Ingolfsson, Thorir Mar; Benatti, Simone; Burrello, Alessio; Scherer, Moritz; Scrugli, Matteo Antonio; Meloni, Paolo; Benini, Luca
Low-Overhead Early-Stopping Policies for Efficient Random Forests Inference on Microcontrollers
2022 Daghero, F; Burrello, A; Xie, C; Benini, L; Calimera, A; Macii, E; Poncino, M; Jahier Pagliari, D
Multi-Complexity-Loss DNAS for Energy-Efficient and Memory-Constrained Deep Neural Networks
2022 Risso, Matteo; Burrello, Alessio; Benini, Luca; Macii, Enrico; Poncino, Massimo; Jahier Pagliari, Daniele
PULP-TrainLib: Enabling On-Device Training for RISC-V Multi-core MCUs Through Performance-Driven Autotuning
2022 Nadalini, Davide; Rusci, Manuele; Tagliavini, Giuseppe; Ravaglia, Leonardo; Benini, Luca; Conti, Francesco
Adaptive Random Forests for Energy-Efficient Inference on Microcontrollers
2021 Daghero, Francesco; Burrello, Alessio; Xie, Chen; Benini, Luca; Calimera, Andrea; Macii, Enrico; Poncino, Massimo; Jahier Pagliari, Daniele
An Open-Source Verification Framework for Open-Source Cores: A RISC-V Case Study
2019 Schiavone, P. D.; Sanchez, E.; Ruospo, A.; Minervini, F.; Zaruba, F.; Haugou, G.; Benini, L.
On-line Testing for Autonomous Systems driven by RISC-V Processor Design Verification
2019 Ruospo, Annachiara; Cantoro, Riccardo; Ernesto, Sanchez; Pasquale Davide Schiavone, ; Angelo, Garofalo; Benini, Luca
| Citazione | Data di pubblicazione | Autori | File |
|---|---|---|---|
| Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference / Risso, Matteo; Burrello, Alessio; Maria Sarda, Giuseppe; Benini, Luca; Macii, Enrico; Poncino, Massimo; Verhelst, Marian; JAHIER PAGLIARI, Daniele. - ELETTRONICO. - (In corso di stampa). (Intervento presentato al convegno ACM/IEEE International Symposium on Low Power Electronics and Design). | In corso di stampa | Matteo RissoAlessio BurrelloLuca BeniniEnrico MaciiMassimo PoncinoDaniele Jahier Pagliari + | ISLPED23___ODiMO__arXiv_.pdf; 135_Final_Manuscript (1).pdf |
| Deep Neural Network Architecture Search for Accurate Visual Pose Estimation aboard Nano-UAVs / Cereda, Elia; Crupi, Luca; Risso, Matteo; Burrello, Alessio; Benini, Luca; Giusti, Alessandro; Jahier Pagliari, Daniele; Palossi, Daniele. - ELETTRONICO. - (2023), pp. 6065-6071. (Intervento presentato al convegno 2023 IEEE International Conference on Robotics and Automation (ICRA) tenutosi a London (UK) nel 29 May 2023 - 02 June 2023) [10.1109/ICRA48891.2023.10160369]. | 1-gen-2023 | Risso, MatteoBurrello, AlessioBenini, LucaJahier Pagliari, Daniele + | 2303.01931.pdf; Deep_Neural_Network_Architecture_Search_for_Accurate_Visual_Pose_Estimation_aboard_Nano-UAVs.pdf |
| Energy-efficient Wearable-to-Mobile Offload of ML Inference for PPG-based Heart-Rate Estimation / Burrello, Alessio; Risso, Matteo; Tomasello, Noemi; Chen, Yukai; Benini, Luca; Macii, Enrico; Poncino, Massimo; JAHIER PAGLIARI, Daniele. - ELETTRONICO. - (2023). (Intervento presentato al convegno Design, Automation & Test in Europe Conference & Exhibition (DATE) tenutosi a Antwerp (Belgium) nel 17-19 April 2023) [10.23919/DATE56975.2023.10137129]. | 1-gen-2023 | Alessio BurrelloMatteo RissoYukai ChenLuca BeniniEnrico MaciiMassimo PoncinoDaniele Jahier Pagliari + | Energy-efficient_Wearable-to-Mobile_Offload_of_ML_Inference_for_PPG-based_Heart-Rate_Estimation.pdf; DATE23___PPGCollaborative__arxiv_.pdf |
| EEGformer: Transformer-Based Epilepsy Detection on Raw EEG Traces for Low-Channel-Count Wearable Continuous Monitoring Devices / Busia, Paola; Cossettini, Andrea; Ingolfsson, Thorir Mar; Benatti, Simone; Burrello, Alessio; Scherer, Moritz; Scrugli, Matteo Antonio; Meloni, Paolo; Benini, Luca. - (2022), pp. 640-644. (Intervento presentato al convegno 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS) tenutosi a Taipei (Taiwan) nel 13-15 October 2022) [10.1109/BioCAS54905.2022.9948637]. | 1-gen-2022 | Burrello, AlessioBenini, Luca + | Transformer_BioCAS_paper-25agosto.pdf; EEGformer_Transformer-Based_Epilepsy_Detection_on_Raw_EEG_Traces_for_Low-Channel-Count_Wearable_Continuous_Monitoring_Devices.pdf |
| Low-Overhead Early-Stopping Policies for Efficient Random Forests Inference on Microcontrollers / Daghero, F; Burrello, A; Xie, C; Benini, L; Calimera, A; Macii, E; Poncino, M; Jahier Pagliari, D. - STAMPA. - 661:(2022), pp. 25-47. (Intervento presentato al convegno 29th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration (VLSI-SoC 2021) tenutosi a Singapore nel October 4-8, 2021) [10.1007/978-3-031-16818-5_2]. | 1-gen-2022 | Daghero, FBurrello, AXie, CBenini, LCalimera, AMacii, EPoncino, MJahier Pagliari, D | postprint.pdf; vlsi-soc-chapter.pdf |
| Multi-Complexity-Loss DNAS for Energy-Efficient and Memory-Constrained Deep Neural Networks / Risso, Matteo; Burrello, Alessio; Benini, Luca; Macii, Enrico; Poncino, Massimo; Jahier Pagliari, Daniele. - ELETTRONICO. - (2022), pp. 1-6. (Intervento presentato al convegno ACM/IEEE International Symposium on Low Power Electronics and Design tenutosi a Boston (USA) nel August 1 - 3, 2022) [10.1145/3531437.3539720]. | 1-gen-2022 | Risso, MatteoBurrello, AlessioBenini, LucaMacii, EnricoPoncino, MassimoJahier Pagliari, Daniele | ispled.pdf; ispled_open.pdf |
| PULP-TrainLib: Enabling On-Device Training for RISC-V Multi-core MCUs Through Performance-Driven Autotuning / Nadalini, Davide; Rusci, Manuele; Tagliavini, Giuseppe; Ravaglia, Leonardo; Benini, Luca; Conti, Francesco. - STAMPA. - (2022), pp. 200-216. (Intervento presentato al convegno 22nd International Conference, SAMOS 2022 tenutosi a Samos, Greece nel July 3–7, 2022) [10.1007/978-3-031-15074-6_13]. | 1-gen-2022 | Nadalini, DavideBenini, Luca + | PULP-TrainLib - Springer Version.pdf; PULP-TrainLib-Editoriale-Compressed.pdf |
| Adaptive Random Forests for Energy-Efficient Inference on Microcontrollers / Daghero, Francesco; Burrello, Alessio; Xie, Chen; Benini, Luca; Calimera, Andrea; Macii, Enrico; Poncino, Massimo; Jahier Pagliari, Daniele. - ELETTRONICO. - (2021), pp. 1-6. (Intervento presentato al convegno 29th IFIP/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2021 tenutosi a Virtual Conference nel 2021) [10.1109/VLSI-SoC53125.2021.9606986]. | 1-gen-2021 | Daghero, FrancescoBurrello, AlessioXie, ChenBenini, LucaCalimera, AndreaMacii, EnricoPoncino, MassimoJahier Pagliari, Daniele | Adaptive_Random_Forests_for_Energy-Efficient_Inference_on_Microcontrollers.pdf; Adaptive_Random_Forests_for_Energy-Efficient_Inference_on_Microcontrollers-POSTPRINT.pdf.pdf |
| An Open-Source Verification Framework for Open-Source Cores: A RISC-V Case Study / Schiavone, P. D.; Sanchez, E.; Ruospo, A.; Minervini, F.; Zaruba, F.; Haugou, G.; Benini, L.. - 2018-:(2019), pp. 43-48. (Intervento presentato al convegno 26th IFIP/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2018 tenutosi a Verona (Italia) nel 2018) [10.1109/VLSI-SoC.2018.8644818]. | 1-gen-2019 | Sanchez E.Ruospo A.Benini L. + | - |
| On-line Testing for Autonomous Systems driven by RISC-V Processor Design Verification / Ruospo, Annachiara; Cantoro, Riccardo; Ernesto, Sanchez; Pasquale Davide Schiavone, ; Angelo, Garofalo; Benini, Luca. - ELETTRONICO. - IEEE The 32nd IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems:(2019). (Intervento presentato al convegno The 32nd IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems tenutosi a Noordwijk, Netherlands, Netherlands nel October 2 – October 4, 2019) [10.1109/DFT.2019.8875345]. | 1-gen-2019 | Annachiara RuospoRiccardo CantoroErnesto SanchezBENINI, LUCA + | 08875345.pdf; DFT2019_postprint.pdf |