Artikelen met mandaten voor openbare toegang - Gagan SomashekarMeer informatie
Ergens beschikbaar: 8
Ensure: Efficient scheduling and autonomous resource management in serverless environments
A Suresh, G Somashekar, A Varadarajan, VR Kakarla, H Upadhyay, ...
2020 IEEE International Conference on Autonomic Computing and Self …, 2020
Mandaten: US National Science Foundation
Towards optimal configuration of microservices
G Somashekar, A Gandhi
Proceedings of the 1st Workshop on Machine Learning and Systems, 7-14, 2021
Mandaten: US National Science Foundation
B-MEG: Bottlenecked-Microservices Extraction Using Graph Neural Networks
G Somashekar, A Dutt, R Vaddavalli, S Bhargav Varanasi, A Gandhi
ICPE '22: Companion of the 2022 ACM/SPEC International Conference on …, 2022
Mandaten: US National Science Foundation
Enhancing the configuration tuning pipeline of large-scale distributed applications using large language models (idea paper)
G Somashekar, R Kumar
Companion of the 2023 ACM/SPEC International Conference on Performance …, 2023
Mandaten: US National Science Foundation
Reducing the tail latency of microservices applications via optimal configuration tuning
G Somashekar, A Suresh, S Tyagi, V Dhyani, K Donkada, A Pradhan, ...
2022 IEEE International Conference on Autonomic Computing and Self …, 2022
Mandaten: US National Science Foundation
Truncating multi-dimensional Markov chains with accuracy guarantee
G Somashekar, M Delasay, A Gandhi
2022 30th International Symposium on Modeling, Analysis, and Simulation of …, 2022
Mandaten: US National Science Foundation
Tighter Lyapunov truncation for multi-dimensional continuous time markov chains with known moments
G Somashekar, M Delasay, A Gandhi
ACM SIGMETRICS Performance Evaluation Review 47 (2), 33-35, 2019
Mandaten: US National Science Foundation
Efficient and accurate Lyapunov function-based truncation technique for multi-dimensional Markov chains with applications to discriminatory processor sharing and priority queues
G Somashekar, M Delasay, A Gandhi
Performance Evaluation 162, 102356, 2023
Mandaten: US National Science Foundation
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