21 citations · 39 across the 9 of their papers we have counts for
9 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…
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…
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…
TruncFormer: Private LLM Inference Using Only Truncations
Patrick Yubeaton, Jianqiao Cambridge Mo, Karthik Garimella +4
Private inference (PI) serves an important role in guaranteeing the privacy of user data when interfacing with proprietary machine learning models such as LLMs. However, PI remains…
PriViT: Vision Transformers for Fast Private Inference
Naren Dhyani, Jianqiao Mo, Minsu Cho +4
The Vision Transformer (ViT) architecture has emerged as the backbone of choice for state-of-the-art deep models for computer vision applications. However, ViTs are ill-suited for…
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…
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…