🤖 AI Summary
研究使用开源Verilog-to-Routing工具链构建StreamNTT,以解决后量子密码算法硬件加速中的比较难题,但需进一步优化内存使用。
📝 Abstract
As post-quantum cryptography algorithms move toward large-scale data center deployment, hardware acceleration of their computational bottleneck, which is the number theoretic transform (NTT), has gained increasing attention. StreamNTT, a high-level synthesis- and field-programmable gate array-based accelerator, achieves state-of-the-art throughput through various optimization techniques. However, its reliance on a commercial tool and a device makes direct comparisons difficult for researchers without access. We address this by building StreamNTT on an open-source Verilog-to-Routing toolchain, which achieves similar digital signal processing and multiplier usage. Significant differences in internal memory utilization indicate that further memory-level optimization is needed to approach commercial tool performance.