| RansomBlocker: A low-overhead ransomware-proof SSD J Park, Y Jung, J Won, M Kang, S Lee, J Kim Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 25 | 2019 |
| Themis: A network bandwidth-aware collective scheduling policy for distributed training of dl models S Rashidi, W Won, S Srinivasan, S Sridharan, T Krishna Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 17 | 2022 |
| Extending sparse tensor accelerators to support multiple compression formats E Qin, G Jeong, W Won, SC Kao, H Kwon, S Srinivasan, D Das, GE Moon, ... 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2021 | 15 | 2021 |
| Astra-sim2. 0: Modeling hierarchical networks and disaggregated systems for large-model training at scale W Won, T Heo, S Rashidi, S Sridharan, S Srinivasan, T Krishna 2023 IEEE International Symposium on Performance Analysis of Systems and …, 2023 | 7 | 2023 |
| Exploring multi-dimensional hierarchical network topologies for efficient distributed training of trillion parameter dl models W Won, S Rashidi, S Srinivasan, T Krishna arXiv preprint arXiv:2109.11762, 2021 | 2 | 2021 |
| TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Training W Won, M Elavazhagan, S Srinivasan, A Durg, S Gupta, T Krishna arXiv preprint arXiv:2304.05301, 2023 | 1 | 2023 |
| MINT: Microarchitecture for Efficient and Interchangeable CompressioN Formats on Tensor Algebra. E Qin, G Jeong, W Won, SC Kao, H Kwon, S Srinivasan, D Das, GE Moon, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2020 | | 2020 |
| Exploring Memory Expansion Designs for Training Mixture-of-Experts Models T Heo, S Rashidi, C Man, DK Kadiyala, W Won, S Srinivasan, ... | | |
Tushar KrishnaAssociate Professor, Georgia TechVerified email at ece.gatech.edu
