RaMP: Runtime-Aware Megakernel Polymorphism for Mixture-of-Experts

1. 1Analyze hardware constants to determine optimal kernel configuration
2. 2Implement RaMP, a routing-aware dispatch framework, to adapt to runtime conditions
3. 3Configure RaMP to derive performance-region analysis for optimal optimization
4. 4Test and evaluate RaMP on various architectures to predict performance gains
5. 5Apply RaMP to production systems to realize kernel throughput improvements

Machine learning engineers and researchers working on Mixture-of-Experts models can benefit from this technique to improve inference performance

💡 RaMP adapts kernel configuration to runtime conditions, overcoming limitations of batch-size-only dispatch

🚀 Boost MoE inference performance by 10-70% with RaMP, a runtime-aware dispatch framework!