Karthik Garimella

According to our database, Karthik Garimella authored at least 8 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

F-LEMMA: Fast Learning-Based Energy Management for Multi-/Many-Core Processors.

An Zou, Yehan Ma, Karthik Garimella, Benjamin Lee, Christopher D. Gill, Xuan Zhang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2023

Orion: A Fully Homomorphic Encryption Compiler for Private Deep Neural Network Inference.

Austin Ebel, Karthik Garimella, Brandon Reagen

CoRR, 2023

Towards Fast and Scalable Private Inference.

Jianqiao Mo, Karthik Garimella, Negar Neda, Austin Ebel, Brandon Reagen

Proceedings of the 20th ACM International Conference on Computing Frontiers, 2023

Characterizing and Optimizing End-to-End Systems for Private Inference.

Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2021

CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale.

Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen

CoRR, 2021

Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning.

Karthik Garimella, Nandan Kumar Jha, Brandon Reagen

CoRR, 2021

2020

Attacking vision-based perception in end-to-end autonomous driving models.

Adith Boloor, Karthik Garimella, Xin He, Christopher D. Gill, Yevgeniy Vorobeychik, Xuan Zhang

J. Syst. Archit., 2020

F-LEMMA: Fast Learning-based Energy Management for Multi-/Many-core Processors.

An Zou, Karthik Garimella, Benjamin Lee, Christopher D. Gill, Xuan Zhang

Proceedings of the MLCAD '20: 2020 ACM/IEEE Workshop on Machine Learning for CAD, 2020