Abstract

Number theoretic transform (NTT) is widely utilized to speed up polynomial multiplication, which is the critical computation bottleneck in a lot of cryptographic algorithms like lattice-based post-quantum cryptography (PQC) and homomorphic encryption (HE). One of the tendency for NTT hardware architecture is to support diverse security parameters and meet resource constraints on different computing platforms. Thus flexibility and Area-Time Product (ATP) become two crucial metrics in NTT hardware design. The flexibility of NTT in terms of different vector sizes and moduli can be obtained directly. Whereas the varying strides in memory access of in-place NTT render the design for different radix and number of parallel butterfly units a tough problem. This paper proposes an efficient conflict-free memory mapping scheme that supports the configuration for both multiple parallel butterfly units and arbitrary radix of NTT. Compared to other approaches, this scheme owns broader applicability and facilitates the parallelization of non-radix-2 NTT hardware design. Based on this scheme, we propose a scalable radix-2 and radix-4 NTT multiplication architecture by algorithm-hardware co-design. A dedicated schedule method is leveraged to reduce the number of modular additions/subtractions and modular multiplications in radix-4 butterfly unit by 20% and 33%, respectively. To avoid the bit-reversed cost and save memory footprint in arbitrary radix NTT/INTT, we put forward a general method by rearranging the loop structure and reusing the twiddle factors. The hardware-level optimization is achieved by excavating the symmetric operators in radix-4 butterfly unit, which saves almost 50% hardware resources compared to a straightforward implementation. Through experimental results and theoretical analysis, we point out that the radix-4 NTT with the same number of parallel butterfly units outperforms the radix-2 NTT in terms of area-time performance in the interleaved memory system. This advantage is enlarged when increasing the number of parallel butterfly units. For example, when processing 1024 14-bit points NTT with 8 parallel butterfly units, the ATP of LUT/FF/DSP/BRAM n radix-4 NTT core is approximately 2.2 × /1.2 × /1.1 × /1.9 × less than that of the radix-2 NTT core on a similar FPGA platform.

Highlights

  • In recent years, both industrial and academic community have sparked a boom in the research of post-quantum cryptography and homomorphic encryption

  • The efficient memory access of in-place Number theoretic transform (NTT) is guaranteed by the devised new conflictfree mapping scheme, which supports the configuration for multiple parallel butterfly units and arbitrary radix

  • In every stage of NTT computation, if multiple data points are mapped onto the same bank, we need to perform several read or write operations on a single bank address simultaneously, which results in the so-called spatial conflict. [Joh92] proposes a memory mapping scheme for arbitrary radix in-place Fast Fourier Transform (FFT) hardware, which is described in point out that this scheme is not suitable for the case when placing multiple butterfly units in every stage

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Summary

Introduction

Both industrial and academic community have sparked a boom in the research of post-quantum cryptography and homomorphic encryption. [LSW01] and [WHEW14] design a dedicated radix-2 FFT and radix-16 NTT architecture based on this method, respectively It is identified in [XMX17] and [ZYC+20] that this scheme cannot be applied to the case when placing multiple parallel butterfly units into every stage. [RV08] puts forward an address mapping scheme supporting arbitrary radix in-place FFT and parallel butterfly units. 3. The efficient memory access of in-place NTT is guaranteed by the devised new conflictfree mapping scheme, which supports the configuration for multiple parallel butterfly units and arbitrary radix. The efficient memory access of in-place NTT is guaranteed by the devised new conflictfree mapping scheme, which supports the configuration for multiple parallel butterfly units and arbitrary radix This scheme avoids introducing queues and pipeline stalls, enabling approximately 100% utilization of pipelined NTT architecture. In contrast to other approaches, this scheme covers broader applicability while still maintaining low logic and storage overhead

NTT-based Multiplication Algorithm
Dimensions of Scalability
Temporal and Spatial Conflicts
DIT Radix-4 NTT with Low Complexity
DIF Radix-4 INTT with Low Complexity
G0 1
Improvement with Divide and Schedule Method
Avoiding Bit-reversed Cost and Reducing Memory Footprint
Proposed DIT-NR Radix-4 NTT
11: Perform the radix-4 DIT-NR NTT
Proposed DIF-RN Radix-4 INTT
Conflict-free Memory Mapping Scheme
Scalable Iterative NTT Algorithm
5: Then the old address a can be expressed in radix r as:
Proposed Solution to Conflict Issue
The Overall Scalable Architecture
Compact Radix-4 Butterfly Unit
Implementation Results and Comparisons
Performance Evaluation Between Radix-4 and Radix-2 NTT
Comparisons with Related Work
Conclusion

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