Posts by Xiaobing Zhang
Optimizing ATOM and vLLM-ATOM for High-Interactivity Inference
- 01 September 2026
When you type a question into a chat assistant, ask a coding agent to make an edit, or watch tokens stream back from a model, what you feel is not throughput. You feel responsiveness. The pause before the first word appears, and the pace at which each following word arrives, decide whether an assistant feels instant or sluggish. As LLMs move into interactive assistants, coding agents, and multi-step tool-calling loops, this responsiveness — how quickly the system reacts to a single user — has become a first-class product requirement.
Scaling MiniMax-M3 Inference with Distributed Serving and Operator Co-Design on AMD Instinct MI355X GPUs
- 21 July 2026
This blog walks you through a set of MiniMax-M3 inference optimizations on AMD Instinct™ MI355X GPUs using ATOM, AITER, and ATOMesh. For broader background on the inference engine and distributed serving layers used here, see the ROCm blogs on ATOM and ATOMesh.
Accelerating LLM Inference on AMD GPUs with Low-Latency GEMMs
- 29 June 2026
Large language model inference is becoming increasingly interactive. Users expect chatbots, coding assistants, agents, and real-time copilots to respond quickly, stream tokens smoothly, and stay responsive under concurrent load. In that setting, decode-time latency is not just a backend metric. It directly affects perceived quality.