May 2026 monthly performance summary for the yhyang201/sglang repository focused on WAN Model NPU performance optimizations and quantized weight loading improvements. Delivered measurable enhancements in end-to-end inference speed and memory efficiency on NPU hardware, and fixed a critical contiguous-loading bug to improve stability.

2026-04 Monthly Summary for repository yhyang201/sglang. Focused on reliability and correctness in the self-attention pipeline affecting video and audio processing. Delivered a critical bug fix to restore cache-dit support for LTX2 by adjusting self-attention indexing to properly handle perturbation masks, preventing regression in diffusion workflows. No new features released this month; the priority was stabilizing core functionality to accelerate downstream work and reduce risk for upcoming releases.

March 2026: Delivered a Hybrid Key-Value Cache for the Ascend backend in the sglang repository, focusing on memory management and performance for neural network operations. Implemented new data structures and control flow to support a hybrid cache and optimized attention processing, aligning with Ascend backend performance objectives. No major bugs reported this month. Overall impact includes improved throughput and reduced latency for attention-heavy workloads, enabling more scalable AI inference deployments. Technologies demonstrated include Ascend NPU backend optimization, hybrid cache design, and performance-focused software engineering. Commit referenced: [NPU] Support Hybrid KV Cache for Ascend backend (#18032); hash: d9e96153de8a1011c3eb4427af4b3c2e9823e4b2; Co-authored-by: gengjinsong.