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 | 827 | 2013 |
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 | 376 | 2011 |
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 | 371 | 2019 |
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 | 228 | 2015 |
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 | 216 | 2016 |
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 | 140 | 2017 |
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 | 131 | 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 | 113 | 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 | 92 | 2015 |
The Seven Deadly Sins of Cloud Computing Research M Schwarzkopf, DG Murray, S Hand Proceedings of HotCloud, 2012 | 68 | 2012 |
Variance Reduction for Reinforcement Learning in Input-Driven Environments H Mao, SB Venkatakrishnan, M Schwarzkopf, M Alizadeh arXiv preprint arXiv:1807.02264, 2018 | 67 | 2018 |
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 | 56 | 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 | 56 | 2019 |
Non-volatile storage M Nanavati, M Schwarzkopf, J Wires, A Warfield Communications of the ACM 59 (1), 56-63, 2015 | 44 | 2015 |
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 | 43 | 2018 |
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 | 40 | 2020 |
Operating system support for warehouse-scale computing M Schwarzkopf University of Cambridge, 2015 | 25 | 2015 |
Position: GDPR Compliance by Construction M Schwarzkopf, E Kohler, MF Kaashoek, R Morris Heterogeneous Data Management, Polystores, and Analytics for Healthcare, 39-53, 2019 | 24 | 2019 |
New wine in old skins: the case for distributed operating systems in the data center M Schwarzkopf, MP Grosvenor, S Hand Proceedings of the 4th Asia-Pacific Systems Workshop (APSYS), 2013 | 24 | 2013 |
Weld: Rethinking the Interface Between Data-Intensive Applications S Palkar, J Thomas, D Narayanan, A Shanbhag, R Palamuttam, H Pirk, ... arXiv preprint arXiv:1709.06416, 2017 | 18 | 2017 |