> ## Documentation Index > Fetch the complete documentation index at: https://docs.sglang.io/llms.txt > Use this file to discover all available pages before exploring further. # Parallelism Overview SGLang Diffusion ships several parallelism strategies. Each one splits a different dimension of the DiT forward pass, which is exactly why they can be combined: the total GPU count is the product of the degrees, ```text theme={null} num_gpus = cfg_parallel_degree × tp_size × sp_degree sp_degree = ulysses_degree × ring_degree ``` This page is the map — what each axis does, which combinations are legal, and how to pick one. Per-axis depth lives in [Sequence Parallelism](./ring_sp_performance), [Encoder Parallelism](./encoder_parallel) (text/image encoders are a separate axis with their own knob), and the [CLI reference](./api/cli). ## The axes | Strategy | Splits | Communication | Flag | | -------------------- | -------------------------------------------- | --------------------------------------------------- | --------------------- | | CFG parallel | guidance branches | one combine per denoise step | `--cfg-parallel-size` | | Tensor parallel (TP) | weights and attention heads | all-reduce per transformer block | `--tp-size` | | Ulysses SP | sequence outside attention ↔ heads inside it | two all-to-alls per attention | `--ulysses-degree` | | Ring SP | sequence rows inside attention | neighbor-only K/V rotation, overlapped with compute | `--ring-degree` | | K/V-gather CP | sequence rows inside attention | one K/V all-gather per attention | `--kv-gather-degree` | | Data parallel | requests | none between replicas | `--dp-size` | Two strategies compose when they split different dimensions. TP and Ulysses both touch heads but compose serially — TP splits the projection weights, then Ulysses splits the activations of the TP-local heads. Ring and Ulysses compose because ring splits rows while Ulysses splits heads. Ring has no composition with a K/V-all-gather style of attention parallelism: both answer the same question (how a rank's query rows see remote K/V), so they are alternatives for one slot, not complements. ## What happens to the shapes For `tp_size = T`, `ulysses_degree = U`, `ring_degree = R`, one attention runs: ```text theme={null} [B, S/(U·R), H/T, D] sequence-sharded activations │ Ulysses input all-to-all (inside each Ulysses group) ▼ [B, S/R, H/(T·U), D] full sequence of this ring block, few heads │ ring attention (R−1 neighbor hops; Q never moves, K/V rotate) ▼ [B, S/R, H/(T·U), D] │ Ulysses output all-to-all (inverse) ▼ [B, S/(U·R), H/T, D] ``` The ring merge (online softmax) requires every rank in a ring group to hold the *same heads* over *different rows*; the group construction guarantees this. A K/V-gather (CP-style) variant fills the same slot differently: instead of R−1 overlapped hops it all-gathers K/V once and computes the local Q rows against the full sequence in one shot — fewer, larger transfers, paid for by holding the whole K/V per rank. Like ring it splits rows, so it adds no head constraint. When no SP degree is set explicitly, `sp_degree=2` defaults to `kv_gather_degree=2` — its measured-win zone — and higher degrees default to Ulysses. Ulysses groups are laid out on contiguous ranks and ring groups on strided ranks, so with a node-major rank mapping, Ulysses traffic stays on intra-node NVLink (all-to-all needs full-bisection bandwidth) while ring hops cross the slower interconnect where neighbor-only transfers overlap with compute. A mis-mapped layout stays numerically correct and silently loses the performance — worth checking when a sharded run is unexpectedly slow. ## Constraints * `num_attention_heads % tp_size == 0` — TP splits heads at the projections. * `(num_attention_heads / tp_size) % ulysses_degree == 0` — Ulysses splits the **TP-local** heads. `H % U == 0` alone is not sufficient: 56 heads pass with `tp=2, ulysses=4` (28 % 4) and fail with `tp=4, ulysses=4` (14 % 4). * Ring adds no head constraint (it splits rows), but the sequence — including any model-specific packing alignment — must divide by `ulysses × ring`, since ring adds an outer row split on top of Ulysses's inner one. * Ring requires an attention backend that declares `supports_ring_rotation()` — the per-hop merge needs the kernel's softmax LSE. `fa` and `sage_attn` declare it; the launcher auto-selects `fa` when unset. * `USPAttention`'s masked/tail-padded text path and its replicated-prefix, -suffix, and -kv-prefix paths all support ring: the sharded K/V rotates through the ring while the tail-pad or replicated portion is attended locally once and combined into the ring result with the same online-softmax merge. This covers the joint text+image attention most models use (flux, flux\_2, qwen\_image, zimage, glm\_image, ernie\_image, and others). * What still raises `NotImplementedError` under ring: `USPAttention`'s generic varlen path (multiple packed segments per row, as used by HunyuanVideo — no ring-aware rotation for it yet), and the legacy stacked-QKV `UlyssesAttention` layer, now down to one user (Wan's VSA sparse-attention variant) that has no softmax LSE to merge and can't gain ring support without a different kernel. * The launcher validates `num_gpus` against the product of the degrees and fails fast on any mismatch. ## The Ulysses transport The all-to-alls normally run over NCCL. On exactly 2 GPUs with peer-to-peer access, a CUDA-IPC transport replaces them by default: each rank writes its half directly into the peer's mapped staging buffer, with GPU-side sequence counters instead of a NCCL rendezvous. An all-to-all is a permutation, never a reduction, so the transport cannot change results — outputs are bitwise identical to the NCCL path. | Environment variable | Default | Meaning | | -------------------------------------- | ------- | ---------------------------------------------------------------------------------------------------------------------------------------------- | | `SGLANG_DIFFUSION_IPC_A2A` | `1` | set `0` to force NCCL | | `SGLANG_DIFFUSION_IPC_A2A_TIMEOUT_MS` | `10000` | deadlock backstop for the peer wait; on expiry the transport retires on every rank and the request fails rather than returning incomplete data | | `SGLANG_DIFFUSION_IPC_A2A_MAX_BUFFERS` | `16` | staging pairs kept alive; raise for many-resolution serving | Independently of the transport, the default path already packs the three Q/K/V input exchanges into one destination-major collective. A handful of models (e.g. LTX-2) instead opt into `enable_packed_qkv_input_a2a`, which pipelines three separate exchanges over a dedicated stream rather than merging them into one payload — a different trade-off, not a strict upgrade over the default. ## Which axes tolerate crossing nodes Each axis has a fixed communication pattern, and the pattern — volume per step, how often it fires, and whether it can hide behind compute — decides whether the axis survives the drop from NVLink to the inter-node fabric. Ordered from most to least cross-node friendly: | Axis | Pattern | Traffic per denoise step | Cross-node verdict | | --------------- | -------------------------------- | ----------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Data parallel | none between replicas | zero on the request path | **Best.** Replicas only share startup init and control-op fan-out; no fast interconnect needed at all. | | CFG parallel | one branch-combine | one latent-sized exchange, once | **Good candidate.** Once per step, small payload, naturally deadline-tolerant. Unmeasured across nodes so far. | | K/V-gather CP | one K/V all-gather per attention | (R−1)/R of K/V, one unoverlapped burst | **Between Ulysses and ring:** only K/V moves (queries never do), but the burst cannot hide behind compute — prefer ring across nodes, gather at small degrees within one. | | Ring SP | neighbor-only K/V rotation | K/V ÷ ring\_degree, (R−1) hops, overlapped with attention tiles | **Designed for it.** The mechanism now covers most models' joint attention (see Constraints). Actually crossing nodes end-to-end is validated for MiniMax H3 (Ulysses intra-node × ring across, net positive and growing with sequence length); other models' ring support is same-node-validated so far. | | Ulysses SP | all-to-all | full q/k/v activations, twice per attention, every layer | **Keep intra-node.** All-to-all needs full-bisection bandwidth; across nodes it becomes R² flows with receiver incast. | | Tensor parallel | all-reduce | hidden-sized reduction per transformer block (×60 blocks for qwen-class DiTs) | **Worst.** Highest frequency, no overlap, already \~70% of sharded kernel time on NVLink. | Two caveats keep this a map rather than a promise. Cross-node launch (`--nnodes`/`--node-rank`/`--dist-init-addr`) is merged, and per-model ring support is broad now (see the constraints above) — but those two facts together still don't add up to "any model, any node count." The only configuration actually run end-to-end across nodes is the H3 recipe; other models' ring support is same-node-validated so far, which means crossing nodes with them is untested, not disallowed. And the data-parallel row describes the design: the current implementation binds each replica's ingress on the local host, so replicas spanning hosts additionally need per-replica host addressing before `--dp-size` can place one replica per node. ## Choosing a configuration Measured guidance rather than rules — the right combination depends on the model's communication profile and the hardware topology, and legal does not mean profitable: * **Multi-branch (true-CFG) models**: CFG parallelism first. Branches run the whole DiT independently and combine once per step, avoiding per-layer communication entirely. * **Single-branch image models on 2 GPUs**: Ulysses and TP trade places by model. Communication-heavy DiTs measured faster with Ulysses; smaller DiTs with TP. Measure both; do not copy a winner across models. * **Long video / packed sequences**: Ulysses up to the head-divisibility limit, then ring for the remaining factor — sequence length scales past the head count where Ulysses alone cannot. * **When Ulysses's head divisibility blocks the degree you need** (`H/T` not divisible by the target `U`): the row-splitting slot sidesteps it — ring today, or `--kv-gather-degree` (it splits rows, so it adds no head constraint either). * **TP beyond 2 ranks** rarely improves image-DiT latency: the per-block all-reduce grows with rank count faster than the GEMM savings. ## Data parallelism `--dp-size N` runs N full engine replicas on `num_gpus / N` GPUs each, every replica with its own ingress. Generation requests round-robin across replicas, realtime sessions stick to the replica holding their state, and control operations (weights, LoRA, memory occupation, shutdown) apply to every replica; replicas exchange nothing on the request path. Monolithic serving only, and the ingress currently binds on the local host — one replica per node needs per-replica host addressing first.