Posts by Indira Vats
DeepSeek-V4 Flash RL on AMD Instinct MI308X GPUs with an AITER-Backed RL Stack
- 28 October 2026
We demonstrate end-to-end DeepSeek-V4 Flash reinforcement learning with an AITER-backed AMD RL stack on 24 AMD Instinct MI308X GPUs. Our test covers the complete workflow on three MI308X OAM nodes—not only inference or an isolated training step, but long-context FP8 rollout, BF16 MoE actor training, online RDMA weight updates, evaluation, and checkpoint recovery. Training and inference run as disaggregated services: two MI308X nodes host a BF16 actor that preserves the numerical stability required by gradient computation and optimizer updates, while a dedicated third MI308X node hosts an FP8 rollout engine whose smaller per-parameter footprint leaves more GPU memory available for KV cache and longer generated sequences. Ray places and coordinates both GPU groups. This experiment demonstrates one tested three-node configuration for running both rollout inference and RL training on MI308X GPUs.
OpenXLA and JAX - ROCm Support and the State of CI
- 29 June 2026
The OpenXLA compiler stack — XLA at the foundation, JAX as the front end — now runs upstream on AMD ROCm. XLA gates every pull request on real AMD Instinct silicon through its GitHub Actions workflow, side by side with the CUDA path; JAX runs the same hardware on every ROCm PR through its own workflows, with the merge gate rolling out next. pip install "jax[rocm7-local]" is a first-class entry point. This post documents how that backend is structured, what landed in the last twelve months, and how the CI pipeline that keeps it healthy is wired together. Part 1 covers OpenXLA on AMD — the XLA backend, what landed this year, and CI. Part 2 covers JAX on AMD — the plugin architecture, JAX-side changes, and the four-workflow test matrix.