July 2025 highlights: Delivered TRTLLM-Gen Context Attention support in FlashInfer, enabling trtllm-gen context attention in the inference pipeline. The feature was integrated into BatchPrefillWithPagedKVCacheWrapper and BatchDecodeWithPagedKVCacheWrapper, including updates to kernel dispatching, argument handling, and the addition of new CUDA kernels for context attention. This work enhances support for context-aware LLMs, enabling longer-context inference with potential throughput and latency benefits. The changes improve kernel-level execution paths and set the foundation for further optimizations and broader model compatibility. Commit: 6f3b59ff6de85997471b50648952d91aab30afa1 (feat: add trtlllm-gen context attention).

June 2025 Monthly Summary for bytedance-iaas/vllm: Focused on delivering performance-oriented FP8 support for SM100 and preparing flexible tensor workflows. Key features delivered - Blockwise FP8 Tensor Operations for SM100 with Input Swap: Implemented blockwise FP8 computation path and added support for swapping input tensors A and B to boost performance and flexibility in tensor layouts. Major bugs fixed - No major bugs reported for this repo during June 2025; accompanying the FP8 feature with stability improvements and targeted fixes as needed. Overall impact and accomplishments - The FP8 blockwise path on SM100 unlocks higher throughput and lower latency for FP8-based inference workloads, enhancing cost-efficiency and scalability for customers deploying SM100-based workloads. The input swap capability adds flexibility for model pipelines and memory layouts, improving resilience and performance under varying workloads. Technologies/skills demonstrated - FP8 precision and blockwise tensor operations, SM100 architecture optimization, input swap implementation, performance validation, and code clarity through commit tracing.