Posts by Yajie Zhang
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.
ATOMesh: Unlocking AMD Hardware for Scalable LLM Serving
- 16 June 2026
Large language model serving is moving from single-engine optimization to full-stack distributed inference. Production deployments must handle high concurrency, long-context prefill, latency-sensitive decode, KV cache store pressure, and multi-node GPU utilization at the same time. On AMD Instinct GPUs, the key opportunity is to connect ROCm-native kernels, communication libraries, inference engines, and distributed orchestration into one scalable serving stack.