
FlashKDA
Ultra-fast attention kernels for Kimi models, optimized for peak performance.
Cuda
FlashKDA is a library of high-performance CUDA kernels implementing the Kimi Delta Attention (KDA) mechanism. It solves the computational bottleneck of attention layers in large language models by providing highly optimized, low-level primitives that dramatically accelerate training and inference. This library is designed for ML engineers and researchers working with Kimi-based architectures who require maximum throughput and efficiency from their hardware.