4 citations · 7 across the 8 of their papers we have counts for
3 papers · 1 filter
Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference
Karthik Garimella, Negar Neda, Austin Ebel +2
Large language model (LLM) based services are primarily structured as client-server interactions, with clients sending queries directly to cloud providers that host LLMs. This appr…
EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors
Karthik Garimella, Austin Ebel, Brandon Reagen
Fully Homomorphic Encryption (FHE) is an encryption scheme that allows for computation to be performed directly on encrypted data, effectively closing the loop on secure and outsou…
HE-LRM: Encrypted Deep Learning Recommendation Models using Fully Homomorphic Encryption
Karthik Garimella, Austin Ebel, Gabrielle De Micheli +1
Fully Homomorphic Encryption (FHE) enables computation directly on encrypted data and privacy-preserving neural inference in the cloud. Existing solutions focus on models with dens…