← Back to context Comment by FridgeSeal 12 days ago That’s great for AI people, but can we use this for other distributed workloads that aren’t ML? 2 comments FridgeSeal Reply geerlingguy 12 days ago I've been testing HPL and mpirun a little, not yet with this new RDMA capability (it seems like Ring is currently the supported method)... but it was a little rough around the edges.See: https://ml-explore.github.io/mlx/build/html/usage/distribute... dagmx 12 days ago Sure, there’s nothing about it that’s tied to ML. It’s faster interconnect , use it for many kinds of shared compute scenarios.
geerlingguy 12 days ago I've been testing HPL and mpirun a little, not yet with this new RDMA capability (it seems like Ring is currently the supported method)... but it was a little rough around the edges.See: https://ml-explore.github.io/mlx/build/html/usage/distribute...
dagmx 12 days ago Sure, there’s nothing about it that’s tied to ML. It’s faster interconnect , use it for many kinds of shared compute scenarios.
I've been testing HPL and mpirun a little, not yet with this new RDMA capability (it seems like Ring is currently the supported method)... but it was a little rough around the edges.
See: https://ml-explore.github.io/mlx/build/html/usage/distribute...
Sure, there’s nothing about it that’s tied to ML. It’s faster interconnect , use it for many kinds of shared compute scenarios.