Bambu: an open-source research framework for the high-level synthesis of complex applications F Ferrandi, VG Castellana, S Curzel, P Fezzardi, M Fiorito, M Lattuada, ... 2021 58th ACM/IEEE Design Automation Conference (DAC), 1327-1330, 2021 | 73 | 2021 |
Hartes: Hardware-software codesign for heterogeneous multicore platforms K Bertels, VM Sima, Y Yankova, G Kuzmanov, W Luk, G Coutinho, ... IEEE micro 30 (5), 88-97, 2010 | 38 | 2010 |
Machine learning for performance prediction of spark cloud applications A Maros, F Murai, APC da Silva, JM Almeida, M Lattuada, E Gianniti, ... 2019 IEEE 12th International Conference on Cloud Computing (CLOUD), 99-106, 2019 | 32 | 2019 |
BIGSEA: A Big Data analytics platform for public transportation information AS Alic, J Almeida, G Aloisio, N Andrade, N Antunes, D Ardagna, ... Future generation computer systems 96, 243-269, 2019 | 31 | 2019 |
The role of internet of things and digital twin in healthcare digitalization process C Patrone, M Lattuada, G Galli, R Revetria Transactions on Engineering Technologies: World Congress on Engineering and …, 2020 | 23 | 2020 |
Performance modeling of embedded applications with zero architectural knowledge M Lattuada, F Ferrandi Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware …, 2010 | 21 | 2010 |
Svelto: High-level synthesis of multi-threaded accelerators for graph analytics M Minutoli, VG Castellana, N Saporetti, S Devecchi, M Lattuada, ... IEEE Transactions on Computers 71 (3), 520-533, 2021 | 19 | 2021 |
High level synthesis of RDF queries for graph analytics VG Castellana, M Minutoli, A Morari, A Tumeo, M Lattuada, F Ferrandi 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 323-330, 2015 | 18 | 2015 |
Performance prediction of deep learning applications training in GPU as a service systems M Lattuada, E Gianniti, D Ardagna, L Zhang Cluster Computing 25 (2), 1279-1302, 2022 | 16 | 2022 |
Code transformations based on speculative SDC scheduling M Lattuada, F Ferrandi 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 71-77, 2015 | 15 | 2015 |
Using efficient path profiling to optimize memory consumption of on-chip debugging for high-level synthesis P Fezzardi, M Lattuada, F Ferrandi ACM Transactions on Embedded Computing Systems (TECS) 16 (5s), 1-19, 2017 | 14 | 2017 |
Comparing industry frameworks with deeply quantized neural networks on microcontrollers D Pau, M Lattuada, F Loro, A De Vita, GD Licciardo 2021 IEEE International Conference on Consumer Electronics (ICCE), 1-6, 2021 | 13 | 2021 |
Automatic parallelization of sequential specifications for symmetric mpsocs F Ferrandi, L Fossati, M Lattuada, G Palermo, D Sciuto, A Tumeo Embedded System Design: Topics, Techniques and Trends, 179-192, 2007 | 13 | 2007 |
Optimizing on-demand gpus in the cloud for deep learning applications training A Jahani, M Lattuada, M Ciavotta, D Ardagna, E Amaldi, L Zhang 2019 4th International Conference on Computing, Communications and Security …, 2019 | 12 | 2019 |
Exploiting outer loops vectorization in high level synthesis M Lattuada, F Ferrandi Architecture of Computing Systems–ARCS 2015: 28th International Conference …, 2015 | 12 | 2015 |
Performance modeling of parallel applications on MPSoCs M Lattuada, C Pilato, A Tumeo, F Ferrandi 2009 International Symposium on System-on-Chip, 064-067, 2009 | 11 | 2009 |
Online learning of oil leak anomalies in wind turbines with block-based binary reservoir M Cardoni, DP Pau, L Falaschetti, C Turchetti, M Lattuada Electronics 10 (22), 2836, 2021 | 10 | 2021 |
Architectural design of cloud applications: A performance-aware cost minimization approach M Ciavotta, GP Gibilisco, D Ardagna, E Di Nitto, M Lattuada, MAA da Silva IEEE Transactions on Cloud Computing 10 (3), 1571-1591, 2020 | 10 | 2020 |
Optimal resource allocation of cloud-based spark applications M Lattuada, E Barbierato, E Gianniti, D Ardagna IEEE Transactions on Cloud Computing 10 (2), 1301-1316, 2020 | 10 | 2020 |
Non-invAsive VentIlation for early General wArd respiraTory failurE (NAVIGATE): A multicenter randomized controlled study. Protocol and statistical analysis plan L Cabrini, C Brusasco, A Roasio, F Corradi, P Nardelli, M Filippini, ... Contemporary clinical trials 78, 126-132, 2019 | 10 | 2019 |