During April 2025, contributed to the Tencent/ncnn repository by developing a performance optimization for the BNLL (bounded non-linear layer) operation targeting RISC-V architecture. This work focused on enhancing inference speed for both float and half-precision data types through the use of C++ and advanced parallel programming techniques. By implementing vectorized operations that leverage RISC-V-specific features, the optimization improved computational efficiency and broadened hardware support. The changes were validated with targeted benchmarks and integration tests, ensuring robust performance gains. No bug fixes were reported during this period, with efforts concentrated on delivering this feature enhancement using vectorization and architecture-aware programming.