Karthik Garimella

19 papers A 1Journal 13Unranked 5
YearRankTypeTitle / 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