| P3: Distributed deep graph learning at scale S Gandhi, AP Iyer 15th {USENIX} Symposium on Operating Systems Design and Implementation …, 2021 | 176 | 2021 |
| An Interval-centric Model for Distributed Computing over Temporal Graphs S Gandhi, Y Simmhan 2020 IEEE 36th International Conference on Data Engineering (ICDE), 1129-1140, 2020 | 26 | 2020 |
| ReCycle: Resilient Training of Large DNNs using Pipeline Adaptation S Gandhi, M Zhao, A Skiadopoulos, C Kozyrakis Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles …, 2024 | 3* | 2024 |
| Graphite: An interval-centric model for distributed computing over temporal graphs S Gandhi, Y Simmhan Indian Institute of Science, Technical report, 2019 | 3 | 2019 |
| Improving DNN Inference Throughput Using Practical, Per-Input Compute Adaptation A Padmanabha Iyer, M Guan, Y Dai, R Pan, S Gandhi, R Netravali Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles …, 2024 | 1 | 2024 |
| MoEtion: Efficient and Reliable Checkpointing for Mixture-of-Experts Models at Scale S Gandhi, C Kozyrakis arXiv preprint arXiv:2412.15411, 2024 | | 2024 |
| Deep neural networks (dnn) inference using practical early exit networks AP IYER, SS Gandhi US Patent App. 17/725,825, 2023 | | 2023 |
| Distributed Programming Abstraction for Scalable Processing of Temporal Graphs S Gandhi Indian Institute of Science Bangalore, 2020 | | 2020 |
| Wave: A Substrate for Distributed Incremental Graph Processing on Commodity Clusters S Gandhi | | 2019 |
