Posts by Yuhua Zhu

Scaling MiniMax-M3 Inference with Distributed Serving and Operator Co-Design on AMD Instinct MI355X GPUs

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.

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SGLang-ATOM: Bring ROCm-Native Acceleration to SGLang Serving

Large language model serving teams often face two competing goals: keeping the flexibility and developer velocity of an ecosystem serving framework, while also reaching strong throughput, latency, and cost efficiency on production accelerators. In this blog, you will explore how SGLang-ATOM bridges these needs for AMD Instinct GPUs by connecting the SGLang serving experience with ATOM’s ROCm-native execution path.

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