18 citations · 31 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…
A Spatial Array for Spectrally Agile Wireless Processing
Ali Rasteh, Andrew Hennessee, Ishaan Shivhare +3
Massive MIMO is a cornerstone of next-generation wireless communication, offering significant gains in capacity, reliability, and energy efficiency. However, to meet emerging deman…
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…
Huff-LLM: End-to-End Lossless Compression for Efficient LLM Inference
Patrick Yubeaton, Tareq Mahmoud, Shehab Naga +8
As they become more capable, large language models (LLMs) have continued to rapidly increase in size. This has exacerbated the difficulty in running state of the art LLMs on small,…
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…
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…
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…