thank you for the fast reply -
reading the link you sent - emphasis added:
It supports full all-to-all communication with direct GPU peer-to-peer memory addressing. These 16 GPUs can be used as a single high-performance accelerator with unified memory space and up to 10 petaFLOPS of deep learning compute power.
I guess I’m just wondering if that is possible for DL workloads with PyTorch…? Sounds like no? thank you!