Omega: flexible, scalable schedulers for large compute clusters M Schwarzkopf, A Konwinski, M Abd-El-Malek, J Wilkes Proceedings of the 8th ACM European Conference on Computer Systems, 351-364, 2013 | 999 | 2013 |
Learning scheduling algorithms for data processing clusters H Mao, M Schwarzkopf, SB Venkatakrishnan, Z Meng, M Alizadeh Proceedings of the ACM Special Interest Group on Data Communication, 270-288, 2019 | 797 | 2019 |
CIEL: a universal execution engine for distributed data-flow computing DG Murray, M Schwarzkopf, C Smowton, S Smith, A Madhavapeddy, ... Proceedings of the 8th USENIX Symposium on Networked Systems Design and …, 2011 | 398 | 2011 |
Firmament: Fast, Centralized Cluster Scheduling at Scale I Gog, M Schwarzkopf, A Gleave, RNM Watson, S Hand Proceedings of the 12th USENIX Symposium on Operating Systems Design and …, 2016 | 301 | 2016 |
Queues Don’t Matter When You Can JUMP Them! MP Grosvenor, M Schwarzkopf, I Gog, RNM Watson, AW Moore, S Hand, ... Proceedings of the 12th USENIX Symposium on Networked Systems Design and …, 2015 | 275 | 2015 |
AIFM: High-Performance, Application-Integrated Far Memory Z Ruan, M Schwarzkopf, MK Aguilera, A Belay Proceedings of the 14th USENIX Symposium on Operating Systems Design and …, 2020 | 214 | 2020 |
Weld: A Common Runtime for High Performance Data Analytics S Palkar, JJ Thomas, A Shanbhag, D Narayanan, H Pirk, M Schwarzkopf, ... Proceedings of the 2017 Conference on Innovative Data Systems Research (CIDR), 2017 | 183 | 2017 |
Conclave: secure multi-party computation on big data N Volgushev, M Schwarzkopf, B Getchell, M Varia, A Lapets, A Bestavros Proceedings of the 14th European Conference on Computer Systems (EuroSys), 2019 | 170 | 2019 |
Conclave: secure multi-party computation on big data (extended TR) N Volgushev, M Schwarzkopf, B Getchell, M Varia, A Lapets, A Bestavros arXiv preprint arXiv:1902.06288, 2019 | 170 | 2019 |
Musketeer: all for one, one for all in data processing systems I Gog, M Schwarzkopf, N Crooks, MP Grosvenor, A Clement, S Hand Proceedings of the 10th ACM European Conference on Computer Systems, 2, 2015 | 166 | 2015 |
Broom: sweeping out Garbage Collection from Big Data systems I Gog, J Giceva, M Schwarzkopf, K Vaswani, D Vytiniotis, G Ramalingan, ... Proceedings of the 15th USENIX Workshop on Hot Topics in Operating Systems, 2015 | 130 | 2015 |
Raft Refloated: Do We Have Consensus? H Howard, M Schwarzkopf, A Madhavapeddy, J Crowcroft ACM SIGOPS Operating Systems Review 49 (1), 12-21, 2015 | 115 | 2015 |
Variance Reduction for Reinforcement Learning in Input-Driven Environments H Mao, SB Venkatakrishnan, M Schwarzkopf, M Alizadeh arXiv preprint arXiv:1807.02264, 2018 | 111 | 2018 |
Evaluating end-to-end optimization for data analytics applications in weld S Palkar, J Thomas, D Narayanan, P Thaker, R Palamuttam, P Negi, ... Proceedings of the VLDB Endowment 11 (9), 1002-1015, 2018 | 101 | 2018 |
The Seven Deadly Sins of Cloud Computing Research M Schwarzkopf, DG Murray, S Hand Proceedings of HotCloud, 2012 | 80 | 2012 |
Noria: dynamic, partially-stateful data-flow for high-performance Web applications J Gjengset, M Schwarzkopf, J Behrens, LT Araújo, M Ek, E Kohler, ... Proceedings of the 13th USENIX Conference on Operating Systems Design and …, 2018 | 78 | 2018 |
Position: GDPR Compliance by Construction M Schwarzkopf, E Kohler, M Frans Kaashoek, R Morris Heterogeneous Data Management, Polystores, and Analytics for Healthcare …, 2019 | 46 | 2019 |
Tuplex: Data Science in Python at Native Code Speed L Spiegelberg, R Yesantharao, M Schwarzkopf, T Kraska Proceedings of the 2021 International Conference on Management of Data, 1718 …, 2021 | 40 | 2021 |
Towards safe online reinforcement learning in computer systems H Mao, M Schwarzkopf, H He, M Alizadeh NeurIPS Machine Learning for Systems Workshop, 2019 | 40 | 2019 |
Non-volatile storage M Nanavati, M Schwarzkopf, J Wires, A Warfield Communications of the ACM 59 (1), 56-63, 2015 | 38 | 2015 |