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CUDA 13.2

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  1. PyTorch 2.15 ships new distributed backend and low-precision inference updates

    PyTorch Blog announced PyTorch 2.15, making the rewritten NCCL backend the default for every NCCL process group while retaining legacy rollback options. The release also adds one-sided torch.distributed transports, FSDP2 and pipelining controls, faster NVFP4 decoding on NVIDIA Blackwell, and FP8 and decode optimizations for Apple Silicon. Platform support expands to Python 3.11–3.15, CUDA 13.2 and 13.4, ROCm 10.0, AMD, and Intel GPUs.

    PyTorch Blog · 🔥 0

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