DCQCN: Quantized Congestion Control for RDMA
DCQCN is how a RoCEv2 fabric stays lossless without living in PFC pause. The switch marks ECN early, the receiver echoes a CNP, and the sender quantizes its rate, so senders slow down before queues overflow. OcNOS-DC ships defaults pre-tuned for xCCL collective workloads (NCCL, RCCL, oneCCL) and exposes every threshold for fabrics that need to deviate.
The DCQCN closed loop
Sender NIC, congested switch, receiver NIC. The switch's WRED ECN marker fires before the queue hits the PFC pause threshold. The receiver generates a Congestion Notification Packet (CNP); the sender's reaction point reduces rate, then ramps back. Lossless, no PFC pressure, fast convergence.
The job DCQCN does in an AI fabric
RoCEv2 has two ways to handle congestion: PFC pause, which is back-pressure that propagates hop by hop, and DCQCN, an end-to-end rate-control loop. PFC alone works, but it pushes congestion upstream and risks pause storms and head-of-line blocking. DCQCN works ahead of PFC, marking packets with ECN before the queue reaches the pause threshold, so the sender slows down before the switch ever has to assert pause.
Done well, you spend most of your fabric life on DCQCN feedback alone, with PFC as a safety backstop. Done badly, ECN thresholds are misaligned with PFC headroom and you get pause storms even with DCQCN configured. Threshold tuning is the whole game, and OcNOS-DC publishes defaults tuned for xCCL collective traffic, while exposing every knob for fabrics that have specific traffic patterns.
Sender NIC quantizes its rate
Receives CNPs and runs the DCQCN α-update, multiplicative-decrease, additive-increase loop to quantize its sending rate.
Switch marks ECN early
Marks ECN-capable packets to CE using a WRED curve when queue depth crosses K-min, with marking probability rising linearly to P-max at K-max.
Receiver echoes a CNP
Generates a CNP back to the sender on each marked flow, rate-limited to roughly one per 50 µs per flow.
PFC pause and DCQCN, side by side
Both keep RoCEv2 lossless, but they act at different points. The tuning goal is to spend the fabric's life on DCQCN feedback and hold PFC in reserve as a backstop.
| Axis | PFC pausebackstop | DCQCNprimary control |
|---|---|---|
| Mechanism | Hop-by-hop back-pressure that propagates upstream. | End-to-end rate-control loop from sender to receiver. |
| Trigger point | Fires when the queue reaches the pause threshold. | Marks ECN before the queue reaches the pause threshold. |
| Failure mode | Risks pause storms and head-of-line blocking. | Sender slows before the switch ever has to assert pause. |
| Role in the fabric | Safety backstop only, for when buffers still fill. | Primary control for most of the fabric's life. |
| Scope | Link-level, one hop at a time. | End-to-end, sender all the way to receiver. |
The OcNOS DCQCN implementation
xCCL-class defaults out of the box, with every threshold exposed as a YANG-modeled path, validated against PFC headroom before it is applied, and streamed back as telemetry during bring-up.
K-min, K-max, P-max
Per-priority-queue WRED ECN marking with configurable K-min and K-max thresholds and a P-max marking probability. xCCL-class defaults out of the box; exposed as YANG paths for tuning.
Independent of PFC
ECN marking is configured independently from PFC pause thresholds. Misalignment is the most common DCQCN configuration error. OcNOS validates the relationship between K-max, headroom, and the pause asserts before applying.
ECN over VXLAN
ECN bits are preserved through VXLAN encap and decap so DCQCN works end-to-end across an EVPN-VXLAN overlay, not just on the underlay.
Per-queue ECN counters
gNMI-streamed counters for ECN-marked packets per egress queue, queue depth distribution, and CNP-trigger rates. Closed-loop tuning during cluster bring-up.
Verify before you commit
CLI sanity-check that K-min, K-max, and PFC headroom are mathematically consistent with the buffer space allocated to the lossless priority. Fail fast on a misconfig.
DC-PLUS license tier
Part of the OcNOS-DC PLUS SKU. Same image, same support; no per-feature add-on required to activate the lossless RDMA stack.
Why this matters more than it sounds
Most "RoCEv2 isn't behaving" support cases land on DCQCN threshold misalignment. The two ends of the mistake look opposite, but both leave the fabric mis-tuned.
- ECN configured but never marks (K-min too high): PFC carries the whole congestion-control burden.
- ECN marks too aggressively (K-min too low): senders cut rate before there is any real congestion.
- OcNOS-DC ships defaults that work on most TH4 and TH5 fabrics; where a fabric needs to deviate, every parameter is YANG-modeled and verifiable.
To size the leaf-spine tiers those defaults run on, try the AI Fabric Sizing Tool, or review the AI fabric topologies the defaults are tuned for.
DCQCN carries the load, PFC stays the backstop
A healthy RoCEv2 fabric runs on ECN feedback and barely touches PFC. OcNOS-DC ships that balance as the default and keeps every threshold in reach when a workload needs a different one.
DCQCN carries the load
ECN marking and CNP feedback slow senders early, so a healthy fabric spends most of its life on DCQCN and rarely reaches PFC pause.
Tuned for xCCL out of the box
OcNOS-DC ships defaults pre-tuned for xCCL collective traffic, so most fabrics run well on TH4 and TH5 without touching a threshold.
Every knob is modeled
K-min, K-max, and P-max are YANG-modeled and verifiable, so fabrics with specific traffic patterns can deviate safely.
DCQCN, answered
What is DCQCN?
How does DCQCN work?
How do DCQCN and PFC work together?
What are the ECN K-min and K-max thresholds in DCQCN?
Does DCQCN require RoCEv2?
Go deeper. Take it with you.
The product datasheet plus short, technical downloads that go further than this page.
OcNOS-DC Datasheet
Full OcNOS-DC specification: the EVPN-VXLAN and Ethernet for AI feature set, software SKUs, supported hardware platforms, and the solution ordering guide.
Get the datasheetOcNOS 800G Lossless AI Fabric
Non-blocking RoCEv2 fabric on Broadcom Tomahawk 4/5 spines: SKU tiers, validated platforms, and deployment architecture.
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Tuning DCQCN for a real workload? Bring us your traces
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