Jax Multiple Gpu, distributed. This section will guide you through setting up a single host with multiple GPUs. When executing JAX code on a single machine, particularly with multiple GPUs, certain considerations and configurations are necessary. Introduction to multi-controller JAX (aka multi-process/multi-host JAX) # By reading this tutorial, you’ll learn how to scale JAX computations to more devices than can fit in a single host machine, e. To learn how to run DALI iterator on multiple GPUs please refer to Getting started with JAX and DALI section about multiple GPU support. Feb 3, 2026 · Integrating NVSHMEM with the XLA compiler and JAX enables efficient training of Llama 3 8B on sequences up to 256K tokens, yielding up to 36% speedup over NVIDIA NCCL for long-context workloads, especially when combined with tensor parallelism across multiple nodes. In this tutorial, we show how to benefit from JAX’s multi-gpu sharding when writting data-processing augmentations. This approach offers more control and clarity:. If you grab arrays from the simulation, such as the grid (sim. JAX-Toolbox. kx6c3, ypq, eg, 4hal, q4dvt, rr, ygso, 9javk, oo6orc, zwp1,