Hermes: A Unified High-Performance NTT Architecture with Hybrid Dataflow

Hermes addresses a specific technical bottleneck in the emerging field of Hybrid Homomorphic Encryption (HHE). While standard FHE accelerators focus on fixed, large-scale NTT operations, HHE requires switching between arithmetic and logic domains, necessitating support for multiple NTT lengths. The project's defensibility (5/10) stems from deep domain expertise in cryptographic hardware design rather than network effects or data gravity. The high fork-to-star ratio (9 forks on 0 stars) within just 44 days suggests significant interest from the research community or peer reviewers, marking it as a credible academic contribution. It competes with existing NTT accelerators like those from Zama (software-side), Intel's HEXL, and specialized hardware startups like Cornami or Optalysys. The risk from frontier labs like OpenAI or Google is low because they are more likely to be consumers of such hardware (for private inference) than designers of low-level NTT primitives. However, platform risk from NVIDIA or Intel is medium, as they could integrate similar 'hybrid dataflow' NTT logic into future crypto-accelerated SKUs.