June 2026 monthly summary for jd-opensource/xllm: Delivered an NPU ACL graph execution double-buffering optimization to overlap decode preparation with graph replay, reducing device idle time and enabling asynchronous token replacement and input preparation. The feature is configurable via the enable_graph_double_buffer flag. No major bugs fixed this month. Overall impact includes improved throughput and resource utilization for NPU-backed graph workloads, translating to lower end-to-end latency in inference pipelines. Technologies/skills demonstrated include performance optimization, asynchronous processing, feature flag design, and collaboration across contributors (co-authored commits).

March 2026 focused on reliability and correctness improvements in vllm-ascend integration, delivering a critical bug fix for Multi-Token Prediction (MTP) models and stabilizing resource calculations for draft models. The change ensures correct layer counting across MTP variants, enabling accurate draft resource allocation and preventing overly conservative max_batch_sizes. This work enhances deployment stability and supports broader MTP use in production environments.