HN844: Multipath Reliable Connection (MRC)

So Multipath Reliable Connection is a specialized transport for AI workloads.

And by that, I mean... it's an open extension to the rocky v2 protocol that exists today we add a package spring we add resilience to link and fabric failures we add congestion control while preserving the application interface so that customers can uh can get the benefits of uh of a of a transfer that is engineered for doing well in AI, with AI workloads, but don't have to change their applications or their network stacks.

So where did MRC come from? What's the history? Because there are other efforts going on to address these kinds of issues.

So the MRC Consortium was a collaboration with Microsoft, OpenAI, Intel, AMD, and NVIDIA.

So it was primarily driven initially by Microsoft and by OpenAI.

They wanted to get AIs, as we know, moving very quickly.

So they wanted to get something out as quickly as they could that solved some of the key problems that Rip discussed.

Primarily the packet spring and multi-passing was a key issue.

enabler for them to build some of the scale networks that they're talking about.

They wanted to do it in a rapid way as quickly as possible.

They brought together some of the key NIC vendors to collaborate together to come up with a minimal viable product to meet their primarily training workload needs.

So that's kind of the history.

The announcement's been great.

It's being deployed in actual networks right now.

It's not a theoretical protocol.

So that's kind of the history of where it came from.

Well, let's explain the problem in more detail because you're talking about packet spraying and so on.

I assume we're talking about equal cost multipath and making even distribution across ECMP has been a challenge.

I assume that's the big one we're getting at here is using all those links in some kind of a...

If you look at the way that Rocky is typically deployed today, there's a single path from source to destination files, and it can use ECMP, but ECMP typically will provide reordering behavior in the network unless you nail up the flows to a single path.

So what packet spraying allows you to do is to utilize within a single message, multiple paths in the network efficiently.

So if you look at it from a protocol perspective, a message comes in, it's broken up into packets, very similar to where Rocky is on today, and those packets are delivered across multiple paths in the network.

The out-of-order data placement feature that we added as part of MRC allows you to recover that reordering at the other side.

So really what it allows you to do is to kind of, you know, spray the marbles across a whole bunch of paths to get a more uniform distribution of traffic across the network.

And generally that's driven by the requirements of these AI training workloads where you're trying to minimize things like packet drops, packet retransmission.

So Multipath Reliable Connection is a specialized transport for AI workloads.

And by that, I mean... it's an open extension to the rocky v2 protocol that exists today we add a package spring we add resilience to link and fabric failures we add congestion control while preserving the application interface so that customers can uh can get the benefits of uh of a of a transfer that is engineered for doing well in AI, with AI workloads, but don't have to change their applications or their network stacks.

So where did MRC come from? What's the history? Because there are other efforts going on to address these kinds of issues.

So the MRC Consortium was a collaboration with Microsoft, OpenAI, Intel, AMD, and NVIDIA.

So it was primarily driven initially by Microsoft and by OpenAI.

They wanted to get AIs, as we know, moving very quickly.

So they wanted to get something out as quickly as they could that solved some of the key problems that Rip discussed.

Primarily the packet spring and multi-passing was a key issue.

enabler for them to build some of the scale networks that they're talking about.

They wanted to do it in a rapid way as quickly as possible.

They brought together some of the key NIC vendors to collaborate together to come up with a minimal viable product to meet their primarily training workload needs.

So that's kind of the history.

The announcement's been great.

It's being deployed in actual networks right now.

It's not a theoretical protocol.

So that's kind of the history of where it came from.

Well, let's explain the problem in more detail because you're talking about packet spraying and so on.

I assume we're talking about equal cost multipath and making even distribution across ECMP has been a challenge.

I assume that's the big one we're getting at here is using all those links in some kind of a...

If you look at the way that Rocky is typically deployed today, there's a single path from source to destination files, and it can use ECMP, but ECMP typically will provide reordering behavior in the network unless you nail up the flows to a single path.

So what packet spraying allows you to do is to utilize within a single message, multiple paths in the network efficiently.

So if you look at it from a protocol perspective, a message comes in, it's broken up into packets, very similar to where Rocky is on today, and those packets are delivered across multiple paths in the network.

The out-of-order data placement feature that we added as part of MRC allows you to recover that reordering at the other side.

So really what it allows you to do is to kind of, you know, spray the marbles across a whole bunch of paths to get a more uniform distribution of traffic across the network.

And generally that's driven by the requirements of these AI training workloads where you're trying to minimize things like packet drops, packet retransmission.