| {EC-Cache}:{Load-Balanced},{Low-Latency} Cluster Caching with Online Erasure Coding KV Rashmi, M Chowdhury, J Kosaian, I Stoica, K Ramchandran 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2016 | 205 | 2016 |
| Parity models: erasure-coded resilience for prediction serving systems J Kosaian, KV Rashmi, S Venkataraman Proceedings of the 27th ACM Symposium on Operating Systems Principles, 30-46, 2019 | 61 | 2019 |
| Learning a code: Machine learning for approximate non-linear coded computation J Kosaian, KV Rashmi, S Venkataraman arXiv preprint arXiv:1806.01259, 2018 | 52 | 2018 |
| Vantage: optimizing video upload for time-shifted viewing of social live streams D Ray, J Kosaian, KV Rashmi, S Seshan Proceedings of the ACM Special Interest Group on Data Communication, 380-393, 2019 | 51 | 2019 |
| Arithmetic-intensity-guided fault tolerance for neural network inference on GPUs J Kosaian, KV Rashmi Proceedings of the International Conference for High Performance Computing …, 2021 | 37 | 2021 |
| Learning-based coded computation J Kosaian, KV Rashmi, S Venkataraman IEEE Journal on Selected Areas in Information Theory 1 (1), 227-236, 2020 | 31 | 2020 |
| Boosting the throughput and accelerator utilization of specialized cnn inference beyond increasing batch size J Kosaian, A Phanishayee, M Philipose, D Dey, R Vinayak International Conference on Machine Learning, 5731-5741, 2021 | 30 | 2021 |
| Cutlass V Thakkar, P Ramani, C Cecka, A Shivam, H Lu, E Yan, J Kosaian, ... github, 2023 | 24 | 2023 |
| Parity models: A general framework for coding-based resilience in ML inference J Kosaian, KV Rashmi, S Venkataraman arXiv preprint arXiv:1905.00863, 2019 | 15 | 2019 |
| CUTLASS, January 2023 V Thakkar, P Ramani, C Cecka, A Shivam, H Lu, E Yan, J Kosaian, ... URL https://github. com/NVIDIA/cutlass, 0 | 8 | |
| CUTLASS, 2023 V Thakkar, P Ramani, C Cecka, A Shivam, H Lu, E Yan, J Kosaian, ... URL https://github. com/NVIDIA/cutlass/tree/v3. 0.0, 0 | 6 | |
| A study on the intersection of gpu utilization and cnn inference J Kosaian, A Phanishayee arXiv preprint arXiv:2212.07936, 2022 | 5 | 2022 |
| Evt: Accelerating deep learning training with epilogue visitor tree Z Chen, A Kerr, R Cai, J Kosaian, H Wu, Y Ding, Y Xie Proceedings of the 29th ACM International Conference on Architectural …, 2024 | 3 | 2024 |
| Efficient Fault Tolerance for Recommendation Model Training via Erasure Coding T Zhang, K Liu, J Kosaian, J Yang, R Vinayak Proceedings of the VLDB Endowment 16 (11), 3137-3150, 2023 | 3 | 2023 |
| ECRM: Efficient fault tolerance for recommendation model training via erasure coding K Liu, J Kosaian, KV Rashmi arXiv preprint arXiv:2104.01981, 2021 | 3 | 2021 |
| Rethinking Erasure-Coding Libraries in the Age of Optimized Machine Learning J Hu, J Kosaian, KV Rashmi Proceedings of the 16th ACM Workshop on Hot Topics in Storage and File …, 2024 | | 2024 |
| Practical Coding-Theoretic Tools for Machine Learning Systems and by Machine Learning Systems J Kosaian Carnegie Mellon University, 2023 | | 2023 |
| AGARWAL, Anup CMU-CS-23-100 ANDERSON, Daniel CMU-CS-23-120 BEVERIDGE, Daniel CMU-CS-23-101 BLAKLEY, James CMU-CS-23-101, CMU-CS-23-138 EL BROWN, II CMU-CS, E CHU, Y DAI, Q DONG, T EISZLER, G FARINA, ... | | |
| 2023 Theses by Author D ANDERSON, E CHU, Y DAI, G FARINA, SA GEORGE, I GROSOF, ... | | |
| Parity Models J Kosaian, R Vinayak, S Venkataraman | | |
