| A NICE Way to Test OpenFlow Applications M Canini, D Venzano, P Perešíni, D Kostić, J Rexford 9th USENIX Symposium on Networked Systems Design and Implementation (NSDI 12 …, 2012 | 762 | 2012 |
| Scaling distributed machine learning with in-network aggregation A Sapio, M Canini, CY Ho, J Nelson, P Kalnis, C Kim, A Krishnamurthy, ... NSDI, 2021 | 495 | 2021 |
| Sonata: Query-driven streaming network telemetry A Gupta, R Harrison, M Canini, N Feamster, J Rexford, W Willinger Proceedings of the 2018 conference of the ACM special interest group on data …, 2018 | 405 | 2018 |
| In-network computation is a dumb idea whose time has come A Sapio, I Abdelaziz, A Aldilaijan, M Canini, P Kalnis Proceedings of the 16th ACM Workshop on Hot Topics in Networks, 150-156, 2017 | 341 | 2017 |
| Fattire: Declarative fault tolerance for software-defined networks M Reitblatt, M Canini, A Guha, N Foster Proceedings of the second ACM SIGCOMM workshop on Hot topics in software …, 2013 | 279 | 2013 |
| C3: Cutting tail latency in cloud data stores via adaptive replica selection L Suresh, M Canini, S Schmid, A Feldmann 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2015 | 278 | 2015 |
| Efficient application identification and the temporal and spatial stability of classification schema W Li, M Canini, AW Moore, R Bolla Computer Networks 53 (6), 790-809, 2009 | 254 | 2009 |
| Netpaxos: Consensus at network speed HT Dang, D Sciascia, M Canini, F Pedone, R Soulé Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking …, 2015 | 229 | 2015 |
| Panopticon: Reaping the Benefits of Incremental SDN Deployment in Enterprise Networks D Levin, M Canini, S Schmid, F Schaffert, A Feldmann 2014 USENIX Annual Technical Conference (USENIX ATC 14), 333-345, 2014 | 217 | 2014 |
| Natural compression for distributed deep learning S Horvóth, CY Ho, L Horvath, AN Sahu, M Canini, P Richtárik Mathematical and Scientific Machine Learning, 129-141, 2022 | 183 | 2022 |
| Paxos made switch-y HT Dang, M Canini, F Pedone, R Soulé ACM SIGCOMM Computer Communication Review 46 (2), 18-24, 2016 | 161 | 2016 |
| A distributed and robust SDN control plane for transactional network updates M Canini, P Kuznetsov, D Levin, S Schmid 2015 IEEE conference on computer communications (INFOCOM), 190-198, 2015 | 156 | 2015 |
| A soft way for openflow switch interoperability testing M Kuzniar, P Peresini, M Canini, D Venzano, D Kostic Proceedings of the 8th international conference on Emerging networking …, 2012 | 147 | 2012 |
| An {Industrial-Scale} Software Defined Internet Exchange Point A Gupta, R MacDavid, R Birkner, M Canini, N Feamster, J Rexford, ... 13th USENIX symposium on networked systems design and implementation (NSDI …, 2016 | 134 | 2016 |
| Identifying and using energy-critical paths N Vasić, P Bhurat, D Novaković, M Canini, S Shekhar, D Kostić Proceedings of the seventh conference on emerging networking experiments and …, 2011 | 125 | 2011 |
| P4xos: Consensus as a network service HT Dang, P Bressana, H Wang, KS Lee, N Zilberman, H Weatherspoon, ... IEEE/ACM Transactions on Networking 28 (4), 1726-1738, 2020 | 109 | 2020 |
| Incremental SDN deployment in enterprise networks D Levin, M Canini, S Schmid, A Feldmann ACM SIGCOMM Computer Communication Review 43 (4), 473-474, 2013 | 105 | 2013 |
| Efficient sparse collective communication and its application to accelerate distributed deep learning J Fei, CY Ho, AN Sahu, M Canini, A Sapio Proceedings of the 2021 ACM SIGCOMM 2021 Conference, 676-691, 2021 | 103 | 2021 |
| Grace: A compressed communication framework for distributed machine learning H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ... 2021 IEEE 41st international conference on distributed computing systems …, 2021 | 102 | 2021 |
| On the discrepancy between the theoretical analysis and practical implementations of compressed communication for distributed deep learning A Dutta, EH Bergou, AM Abdelmoniem, CY Ho, AN Sahu, M Canini, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3817-3824, 2020 | 100 | 2020 |
Dejan KosticProfessor, KTH Royal Institute of TechnologyZweryfikowany adres z kth.se