[https://nvbugs/6171743][fix] Set PYTORCH_ALLOC_CONF=expandable_segments:True on MPI workers via `patch_mpi_ - #14152
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📝 WalkthroughWalkthroughThe PR updates the SM120 NVFP4 multi-GPU test to enable MPI environment variable propagation for PyTorch memory allocation expansion, adjusts the KV-cache memory fraction configuration, and removes the test's skip waiver. ChangesSM120 NVFP4 Test Configuration
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The test failed during executor creation with CUDA OOM at the 'executor_extra' stage on RTX PRO 6000 Blackwell (96 GB) when the MoE autotuner forward pass needed a ~14.3 GiB contiguous workspace but the allocator only had ~7 GiB free with ~13 GiB held in fragmented cache. Set PYTORCH_ALLOC_CONF=expandable_segments:True for the MPI workers via the existing patch_mpi_pool_session_for_env helper to let PyTorch satisfy the autotuner allocation across non-contiguous segments. Also lower free_gpu_memory_fraction from 0.70 to 0.5 for additional headroom on this tight 96 GB SKU. Remove the corresponding waiver. Signed-off-by: tensorrt-cicd <90828364+tensorrt-cicd@users.noreply.github.com>
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…ents:True` on MPI workers via `patch_mpi_ (NVIDIA#14152) Signed-off-by: tensorrt-cicd <90828364+tensorrt-cicd@users.noreply.github.com>
…ents:True` on MPI workers via `patch_mpi_ (NVIDIA#14152) Signed-off-by: tensorrt-cicd <90828364+tensorrt-cicd@users.noreply.github.com>
…ents:True` on MPI workers via `patch_mpi_ (NVIDIA#14152) Signed-off-by: tensorrt-cicd <90828364+tensorrt-cicd@users.noreply.github.com>
Summary
PYTORCH_ALLOC_CONF=expandable_segments:Trueon MPI workers viapatch_mpi_pool_session_for_envso the allocator can satisfy the autotuner request from non-contiguous virtual segments; also lowerfree_gpu_memory_fractionfrom 0.70 to 0.5 for more headroom; remove the waiver.Test plan
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