Posts by Jin Pan
Day-0 Support for the SGLang-Native RL Framework - slime on AMD Instinct™ GPUs
- 25 September 2025
AMD is excited to provide Day-0 support for the SGLang-native RL framework, slime. In this post, we will provide more details about our support and optimizations, as well as slime’s benefits for large-scale RL training. First, we describe the engineering efforts behind slime—including codebase modification, kernel-level memory management for ROCm™ software, and modifications to third-party dependencies (Megatron-LM, SGLang, and torch_memory_saver)—as well as Docker images that enable efficient execution on AMD Instinct™ GPUs. Architecturally, slime supports two training modes: synchronous and asynchronous. Across these modes, we additionally present system-level optimizations with the corresponding use cases. Specifically, in the synchronous setting, our rollout optimizations deliver a 40% throughput improvement over the one without it on AMD Instinct™ GPUs. In the asynchronous setting, we develop a multi-turn RL agent framework to train the kernel generation model. You can also read more about this support in the MLsys – SGLang official blog.