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ORCIDPrashanthi S. K
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2020 – today
- 2024
[j2]Prashanthi S. K
, Saisamarth Taluri, Beautlin S, Lakshya Karwa, Yogesh Simmhan:
PowerTrain: Fast, generalizable time and power prediction models to optimize DNN training on accelerated edges. Future Gener. Comput. Syst. 161: 329-344 (2024)- [i2]Prashanthi S. K, Saisamarth Taluri, Beautlin S, Lakshya Karwa, Yogesh Simmhan:
PowerTrain: Fast, Generalizable Time and Power Prediction Models to Optimize DNN Training on Accelerated Edges. CoRR abs/2407.13944 (2024) - 2023
- [c4]Prashanthi S. K, Vinayaka Hegde, Yogesh Simmhan:
Towards Efficient Scheduling of Concurrent DNN Training and Inferencing on Accelerated Edges. CCGridW 2023: 357-359 - [c3]Prashanthi S. K, Vinayaka Hegde, Keerthana Patchava, Ankita Das, Yogesh Simmhan:
Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators. HiPC 2023: 127-131 - [c2]Prashanthi S. K, Sai Anuroop Kesanapalli, Yogesh Simmhan:
Characterizing the Performance of Accelerated Jetson Edge Devices for Training Deep Learning Models. SIGMETRICS (Abstracts) 2023: 37-38 - [i1]Prashanthi S. K, Vinayaka Hegde, Keerthana Patchava, Ankita Das, Yogesh Simmhan:
Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators. CoRR abs/2312.07220 (2023) - 2022
- [c1]Prashanthi S. K, Aakash Khochare, Sai Anuroop Kesanapalli, Rahul Atul Bhope, Yogesh Simmhan:
Don't Miss the Train: A Case for Systems Research into Training on the Edge. IPDPS Workshops 2022: 985-986 - 2021
- [j1]Prashanthi S. K, Sai Anuroop Kesanapalli, Yogesh Simmhan:
Characterizing the Performance of Accelerated Jetson Edge Devices for Training Deep Learning Models. Proc. ACM Meas. Anal. Comput. Syst. 6(3): 44:1-44:26 (2021)
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