| Apache spark: a unified engine for big data processing M Zaharia, RS Xin, P Wendell, T Das, M Armbrust, A Dave, X Meng, ... Communications of the ACM 59 (11), 56-65, 2016 | 3006 | 2016 |
| Mllib: Machine learning in apache spark X Meng, J Bradley, B Yavuz, E Sparks, S Venkataraman, D Liu, ... Journal of Machine Learning Research 17 (34), 1-7, 2016 | 2384 | 2016 |
| {CherryPick}: Adaptively unearthing the best cloud configurations for big data analytics O Alipourfard, HH Liu, J Chen, S Venkataraman, M Yu, M Zhang 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2017 | 603 | 2017 |
| Ernest: Efficient performance prediction for {Large-Scale} advanced analytics S Venkataraman, Z Yang, M Franklin, B Recht, I Stoica 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2016 | 599 | 2016 |
| Occupy the cloud: Distributed computing for the 99% E Jonas, Q Pu, S Venkataraman, I Stoica, B Recht Proceedings of the 2017 symposium on cloud computing, 445-451, 2017 | 590 | 2017 |
| Consistent and durable data structures for non-volatile byte-addressable memory S Venkataraman, N Tolia, P Ranganathan, RH Campbell Proceedings of the 9th USENIX Conference on File and Storage Technologies …, 2011 | 545 | 2011 |
| Analysis of {Large-Scale}{Multi-Tenant}{GPU} clusters for {DNN} training workloads M Jeon, S Venkataraman, A Phanishayee, J Qian, W Xiao, F Yang 2019 USENIX Annual Technical Conference (USENIX ATC 19), 947-960, 2019 | 351 | 2019 |
| Focus: Querying large video datasets with low latency and low cost K Hsieh, G Ananthanarayanan, P Bodik, S Venkataraman, P Bahl, ... 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2018 | 321 | 2018 |
| Shuffling, fast and slow: Scalable analytics on serverless infrastructure Q Pu, S Venkataraman, I Stoica 16th USENIX symposium on networked systems design and implementation (NSDI …, 2019 | 285 | 2019 |
| Probabilistically Bounded Staleness for Practical Partial Quorums P Bailis, S Venkataraman, JM Hellerstein, M Franklin, I Stoica | 274 | 2012 |
| Drizzle: Fast and adaptable stream processing at scale S Venkataraman, A Panda, K Ousterhout, M Armbrust, A Ghodsi, ... Proceedings of the 26th Symposium on Operating Systems Principles, 374-389, 2017 | 207 | 2017 |
| The power of choice in {Data-Aware} cluster scheduling S Venkataraman, A Panda, G Ananthanarayanan, MJ Franklin, I Stoica 11th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2014 | 206* | 2014 |
| Themis: Fair and efficient {GPU} cluster scheduling K Mahajan, A Balasubramanian, A Singhvi, S Venkataraman, A Akella, ... 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2020 | 200 | 2020 |
| Keystoneml: Optimizing pipelines for large-scale advanced analytics ER Sparks, S Venkataraman, T Kaftan, MJ Franklin, B Recht 2017 IEEE 33rd international conference on data engineering (ICDE), 535-546, 2017 | 174 | 2017 |
| Reactive distillation using ASPEN PLUS. S Venkataraman, WK Chan, JF Boston | 159 | 1990 |
| Presto: distributed machine learning and graph processing with sparse matrices S Venkataraman, E Bodzsar, I Roy, A AuYoung, RS Schreiber Proceedings of the 8th ACM European Conference on Computer Systems, 197-210, 2013 | 145 | 2013 |
| Cake: enabling high-level SLOs on shared storage systems A Wang, S Venkataraman, S Alspaugh, R Katz, I Stoica Proceedings of the Third ACM Symposium on Cloud Computing, 1-14, 2012 | 140 | 2012 |
| Matrix computations and optimization in apache spark R Bosagh Zadeh, X Meng, A Ulanov, B Yavuz, L Pu, S Venkataraman, ... Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 136 | 2016 |
| P3: Distributed deep graph learning at scale S Gandhi, AP Iyer 15th {USENIX} Symposium on Operating Systems Design and Implementation …, 2021 | 131 | 2021 |
| Blink: Fast and generic collectives for distributed ml G Wang, S Venkataraman, A Phanishayee, N Devanur, J Thelin, I Stoica Proceedings of Machine Learning and Systems 2, 172-186, 2020 | 121 | 2020 |
