Pritish Parida, Timothy Chainer, et al.
ARPA-E Summit 2023
With the rising popularity of post-quantum cryptographic schemes, realizing practical implementations for real-world applications is still a major challenge. A major bottleneck in such schemes is the fetching and processing of large polynomials in the Number Theoretic Transform (NTT), which makes non Von Neumann paradigms, such as near-memory processing, a viable option. We, therefore, propose a novel near-DRAM NTT accelerator design, called Dramaton. Additionally, we introduce a conflict-free mapping algorithm that enables Dramaton to process large NTTs with minimal hardware overhead using a fixed-permutation network. Dramaton achieves 5-207× speedup in latency over the state-of-the-art and 97× improvement in EDP over a recent near-memory NTT accelerator.
Pritish Parida, Timothy Chainer, et al.
ARPA-E Summit 2023
Myeongsoo Kim, Qi Xin, et al.
ISSTA 2022
Runyu Jin, Paul Muench, et al.
ICPE 2024
Michele Gazzetti
KubeCon EU 2024