Posts by Liying Li
Introducing AMD ROCm™ Infera: Scaling Goodput for Agentic AI with Distributed Inference Orchestration
- 23 July 2026
Today we are introducing AMD ROCm™ Infera, a distributed inference reference solution for large-scale deployments. Infera is a conductor for your inference GPU orchestra. Initial internal testing shows that Infera can improve goodput per GPU for realistic agentic workloads by up to 2.6×, as detailed below. Built for AMD Instinct™ GPUs, Infera is open source from day one, and the code is available at github.com/AMD-AGI/Infera.
Dropless MoE Training in JAX with Primus-Turbo
- 10 June 2026
Mixture-of-Experts (MoE) models have become a standard way to scale a transformer’s parameter count without paying the full compute bill — but training them efficiently on GPUs forces an uncomfortable trade-off. The default path in JAX/MaxText keeps every expert’s tensors at a fixed shape and simply drops the tokens that overflow each expert’s capacity, trading model quality for speed. The fully dropless alternative keeps every token, but in pure JAX it hits a memory wall that makes it impractical at production scale.
MoE Training Best Practices on AMD GPUs
- 16 December 2025
This blog covers best practices for training Mixture-of-Experts (MoE) models on AMD Instinct™ MI300/MI355-series[a] GPUs with the ROCm ecosystem. Whether you’re new to MoE distributed architectures or optimizing trillion-parameter models, this guide will help you identify bottlenecks and maximize efficiency on AMD hardware.