Week 0: Introduction!

Currently, I am working with Dr. Arafin at George Mason University (GMU), and my research project focuses on optimizing encryption programs for use on GPUSs in order to allow for encryption that can withstand quantum computing without requiring too much processing power. More specifically, by optimizing memory access patterns and exploiting the parallelism of GPUs, this project aims to answer the following research question: Can hardware-aware optimizations on GPUs significantly speed up the state-of-the-art implementation of the ANTT?

The scalability and privacy of modern blockchain technologies rely on Zero-Knowledge Proofs (ZKPs). However, these ECC-based proofs face an existential threat with the rapid advancement of quantum computing. Anticipating the threat of quantum computers, cryptographers have come up with different protocols that do not rely on ECC. One such protocol is BINIUS, a proof system that operates over binary fields rather than the large prime fields used in ECC. BINIUS offers the advantages of being post-quantum secure and also leveraging the native binary architecture of modern CPUs and GPUs, theoretically offering faster proof generation in comparison to ECC. However, the practical speed of BINIUS is currently constrained by the Polynomial Commitment Scheme (PCS), which relies on the Additive Number Theoretic Transform (ANTT), the most computationally expensive part of the BINIUS proof system. By accelerating the ANTT, this research directly contributes to post-quantum cryptographic protocols. By optimizing these kernels for a wider range of hardware, the hardware barrier to entry can be lowered, making it less expensive for people to join the blockchain and contribute computation for proofs.