A Scalable Hardware/Software Co-design Approach for Efficient Polynomial Multiplication

Polynomial multiplication is a fundamental operation in security and cryptography applications. However, traditional polynomial multiplication algorithms suffer from high computational complexity and memory bandwidth requirements, limiting their scalability and efficiency. In this work, we propose a new approach that leverages hardware acceleration and software optimization techniques to achieve high performance and scalability while minimizing memory requirements. Our approach uses custom lightweight hardware instructions to perform the computationally intensive parts of the multiplication, while the software manages data movement and communication between the hardware and main memory. We demonstrate the effectiveness of our approach on TMVP-based polynomial multiplication algorithm. The proposed design can be easily customized to target different hardware platforms and polynomial sizes, making it a promising solution for a wide range of applications.