Previous PyTorch Versions
Access and install previous PyTorch versions, including binaries and instructions for all platforms.| PyTorch
Intel announces a major enhancement for distributed training in PyTorch 2.8: the native integration of the XCCL backend for Intel® GPUs (Intel® XPU devices). This provides support for Intel® oneAPI Collective Communications Library (oneCCL) directly into PyTorch, giving developers a seamless, out-of-the-box experience to scale AI workloads on Intel hardware. | pytorch.org
Key takeaways:| pytorch.org
As training jobs become larger, the likelihood of failures such as preemptions, crashes, or infrastructure instability rises. This can lead to significant inefficiencies in training and delays in time-to-market. At these large scales, efficient distributed checkpointing is crucial to mitigate the negative impact of failures and to optimize overall training efficiency (training goodput).| pytorch.org
Access and install previous PyTorch versions, including binaries and instructions for all platforms.| PyTorch
