21 citations · 64 across the 16 of their papers we have counts for
16 papers
When Proofs Meet Hardware: Comparing NTT and SumCheck in Zero-Knowledge Systems
Jianqiao Mo, Alhad Daftardar, Barath GaneshKumar +5
In the ZKP community, it has long been discussed that the SumCheck protocol is asymptotically more efficient than the Number Theoretic Transform (NTT), requiring only arithm…
zkPHIRE: A Programmable Accelerator for ZKPs over HIgh-degRee, Expressive Gates
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow +3
Zero-Knowledge Proofs (ZKPs) have emerged as a powerful tool for secure and privacy-preserving computation. ZKPs enable one party to convince another of a statement's validity with…
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…
MTU: The Multifunction Tree Unit for Accelerating Zero-Knowledge Proofs
Jianqiao Mo, Alhad Daftardar, Joey Ah-Kiow +4
Zero-Knowledge Proofs (ZKPs) are critical for privacy-preserving techniques and verifiable computation. Many ZKP protocols rely on key kernels such as the SumCheck protocol and Mer…
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…
Need for zkSpeed: Accelerating HyperPlonk for Zero-Knowledge Proofs
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow +4
Zero-Knowledge Proofs (ZKPs) are rapidly gaining importance in privacy-preserving and verifiable computing. ZKPs enable a proving party to prove the truth of a statement to a verif…
Osiris: A Systolic Approach to Accelerating Fully Homomorphic Encryption
Austin Ebel, Brandon Reagen
In this paper we show how fully homomorphic encryption (FHE) can be accelerated using a systolic architecture. We begin by analyzing FHE algorithms and then develop systolic or sys…
SZKP: A Scalable Accelerator Architecture for Zero-Knowledge Proofs
Alhad Daftardar, Brandon Reagen, Siddharth Garg
Zero-Knowledge Proofs (ZKPs) are an emergent paradigm in verifiable computing. In the context of applications like cloud computing, ZKPs can be used by a client (called the verifie…
NTTSuite: Number Theoretic Transform Benchmarks for Accelerating Encrypted Computation
Juran Ding, Yuanzhe Liu, Lingbin Sun +1
Privacy concerns have thrust privacy-preserving computation into the spotlight. Homomorphic encryption (HE) is a cryptographic system that enables computation to occur directly on…
Orion: A Fully Homomorphic Encryption Framework for Deep Learning
Austin Ebel, Karthik Garimella, Brandon Reagen
Fully Homomorphic Encryption (FHE) has the potential to substantially improve privacy and security by enabling computation directly on encrypted data. This is especially true with…
CiFlow: Dataflow Analysis and Optimization of Key Switching for Homomorphic Encryption
Negar Neda, Austin Ebel, Benedict Reynwar +1
Homomorphic encryption (HE) is a privacy-preserving computation technique that enables computation on encrypted data. Today, the potential of HE remains largely unrealized as it is…
Privacy Preserving In-memory Computing Engine
Haoran Geng, Jianqiao Mo, Dayane Reis +5
Privacy has rapidly become a major concern/design consideration. Homomorphic Encryption (HE) and Garbled Circuits (GC) are privacy-preserving techniques that support computations o…
Towards Fast and Scalable Private Inference
Jianqiao Mo, Karthik Garimella, Negar Neda +2
Privacy and security have rapidly emerged as first order design constraints. Users now demand more protection over who can see their data (confidentiality) as well as how it is use…
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation
David Bruce Cousins, Yuriy Polyakov, Ahmad Al Badawi +21
Secure computation is of critical importance to not only the DoD, but across financial institutions, healthcare, and anywhere personally identifiable information (PII) is accessed.…
RPU: The Ring Processing Unit
Deepraj Soni, Negar Neda, Naifeng Zhang +14
Ring-Learning-with-Errors (RLWE) has emerged as the foundation of many important techniques for improving security and privacy, including homomorphic encryption and post-quantum cr…
HAAC: A Hardware-Software Co-Design to Accelerate Garbled Circuits
Jianqiao Mo, Jayanth Gopinath, Brandon Reagen
Privacy and security have rapidly emerged as priorities in system design. One powerful solution for providing both is privacy-preserving computation, where functions are computed d…