Karthik Garimella

19 papers A 1Journal 13Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors. WAHC@CCS Karthik Garimella, Austin Ebel, Brandon Reagen
2025	J	`jnl`	EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors. CoRR Karthik Garimella, Austin Ebel, Brandon Reagen
2025	J	`jnl`	EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors. IACR Cryptol. ePrint Arch. Karthik Garimella, Austin Ebel, Brandon Reagen
2025	J	`jnl`	HE-LRM: Encrypted Deep Learning Recommendation Models using Fully Homomorphic Encryption. CoRR Karthik Garimella, Austin Ebel, Gabrielle De Micheli, Brandon Reagen
2025	A	`conf`	Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference (Invited Paper). ICCAD Karthik Garimella, Negar Neda, Austin Ebel, Nandan Kumar Jha, Brandon Reagen
2025	J	`jnl`	Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference. CoRR Karthik Garimella, Negar Neda, Austin Ebel, Nandan Kumar Jha, Brandon Reagen
2025	—	`conf`	Orion: A Fully Homomorphic Encryption Framework for Deep Learning. ASPLOS (2) Austin Ebel, Karthik Garimella, Brandon Reagen
2024	J	`jnl`	TruncFormer: Private LLM Inference Using Only Truncations. CoRR Patrick Yubeaton, Jianqiao Mo, Karthik Garimella, Nandan Kumar Jha, Brandon Reagen, Chinmay Hegde, Siddharth Garg
2023	—	`conf`	Characterizing and Optimizing End-to-End Systems for Private Inference. ASPLOS (3) Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen
2023	J	`jnl`	F-LEMMA: Fast Learning-Based Energy Management for Multi-/Many-Core Processors. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. An Zou, Yehan Ma, Karthik Garimella, Benjamin Lee, Christopher D. Gill, Xuan Zhang
2023	J	`jnl`	Orion: A Fully Homomorphic Encryption Compiler for Private Deep Neural Network Inference. CoRR Austin Ebel, Karthik Garimella, Brandon Reagen
2023	—	`conf`	Towards Fast and Scalable Private Inference. CF Jianqiao Mo, Karthik Garimella, Negar Neda, Austin Ebel, Brandon Reagen
2023	J	`jnl`	Towards Fast and Scalable Private Inference. CoRR Jianqiao Mo, Karthik Garimella, Negar Neda, Austin Ebel, Brandon Reagen
2022	J	`jnl`	Characterizing and Optimizing End-to-End Systems for Private Inference. CoRR Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen
2021	J	`jnl`	CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale. CoRR Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
2021	J	`jnl`	Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning. CoRR Karthik Garimella, Nandan Kumar Jha, Brandon Reagen
2020	J	`jnl`	Attacking vision-based perception in end-to-end autonomous driving models. J. Syst. Archit. Adith Boloor, Karthik Garimella, Xin He, Christopher D. Gill, Yevgeniy Vorobeychik, Xuan Zhang
2020	—	`conf`	F-LEMMA: Fast Learning-based Energy Management for Multi-/Many-core Processors. MLCAD An Zou, Karthik Garimella, Benjamin Lee, Christopher D. Gill, Xuan Zhang
2019	J	`jnl`	Attacking Vision-based Perception in End-to-End Autonomous Driving Models. CoRR Adith Boloor, Karthik Garimella, Xin He, Christopher D. Gill, Yevgeniy Vorobeychik, Xuan Zhang