March 2026 monthly summary for ROCm/composable_kernel. Focus was on CK Tile depthwise convolution optimizations and feature expansion. Delivered performance optimizations and 5x5 filter support, including updates to tensor descriptor transformations for grouped depthwise convolutions and vectorload enhancements. No major bugs fixed recorded in this scope. Validation included internal benchmarks across DL models, showing significant performance uplift for depthwise 3x3 and 5x5 paths. Business impact: higher model throughput and lower latency for workloads using depthwise convolutions, and expanded 5x5 kernel support bringing CK Tile performance closer to depthwise merged implementations. Technologies demonstrated include CK Tile architecture, tensor descriptor transformations, grouped depthwise conv handling, 5x5 filter specialization, and internal benchmarking aligned with ROCm-libraries workflows (commit d32d515f64a4e55a191087fb299fa99b7140616f).