FROST SDPA fp8: block-scaled O epilogues (NVFP4 / MXFP8) with an sf_o output - #1088
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Included review availability: Your plan provides up to 12 included reviews per hour; 5 remain after this review. 📝 WalkthroughWalkthroughThe change adds forward-only NVFP4 and MXFP8 block-scaled O outputs for FP8 SDPA. It updates graph contracts, validation, FROST kernels, scale-factor handling, tests, and attention benchmarks. ChangesBlock-scaled FP8 output support
Priority: ➖ Normal Estimated code review effort: 5 (Critical) | ~90 minutes Change: Feature Sequence Diagram(s)sequenceDiagram
participant Caller
participant SdpaGraph
participant FP8Engine
participant FROSTKernel
participant OutputBuffers
Caller->>SdpaGraph: Request FP8 output with sf_o
SdpaGraph->>FP8Engine: Validate output dtype and block scale
FP8Engine->>OutputBuffers: Bind packed O and sf_o
FP8Engine->>FROSTKernel: Launch with scale geometry
FROSTKernel->>OutputBuffers: Write quantized O and scale factors
OutputBuffers-->>Caller: Return block-scaled outputs
Suggested reviewers: Merge Risk: ⚪ Minimal · up to The added block-scaled output path includes validation and coverage for the updated SM120 padding behavior. No actionable merge risk remains from the supplied evidence. 🚥 Pre-merge checks | ✅ 3 | ❌ 2❌ Failed checks (2 warnings)
✅ Passed checks (3 passed)
Full details: Description checkExplanation The description provides a detailed summary and testing information, but it omits required template sections for repository checkboxes, affected area, Why, Related issues, and API and compatibility impact. The Test plan is also left unchecked despite reported validation results. Resolution Add all required template sections. Complete the repository checkboxes, select the affected area, explain why the change is needed, list related issues or state that none apply, document API and compatibility impact, and update the Test plan with completed commands and results. ✨ Finishing Touches 💡 1🛠️ Fix failing CI checks 💡
🧪 Generate unit tests (beta)
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Actionable comments posted: 3
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Inline comments:
In `@python/cudnn/sdpa/fwd/api_dsl.py`:
- Around line 3535-3540: Update the SM120 O dtype validation in
SdpaFwdDslSm120.check_support() to accept torch.float4_e2m1fn_x2 when the FP4
block scale is 16, while preserving existing FP8 validation and rejecting
unsupported O dtypes.
In `@python/cudnn/sdpa/fwd/config_sm107.py`:
- Around line 304-305: Update the block-scaled O validation in _validate_params
to require the supported d128 per-tensor FP8 specialization, rejecting d192
configurations and d128 MXFP8 configurations instead of relying only on the
flavor substring check. Preserve acceptance only for configurations handled by
the per-tensor FP8 kernel’s block-scaled O epilogue.
In `@test/python/sdpa/fp8.py`:
- Line 739: Update the `o_block_scale` condition to use the repository’s
range-based compute-capability support contract, disabling block-scaled output
for architectures below SM100 while allowing the full supported 10.0–12.9 range.
Ensure SM90 configurations clear or avoid `o_block_scale` so they run plain FP8
instead of being skipped by `check_support()`.
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Fix all unresolved CodeRabbit comments on this PR:
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benchmark/attention_training/README.mdbenchmark/attention_training/benchmark_single_sdpa.pybenchmark/attention_training/charts.pybenchmark/attention_training/config_types.pybenchmark/attention_training/configs/wan22.pybenchmark/attention_training/runner.pypython/cudnn/_pygraph.pypython/cudnn/_sdpa_validate.pypython/cudnn/frost/tile_dsl/constants.pypython/cudnn/frost/tile_dsl/pointwise.pypython/cudnn/sdpa/frost/SUPPORT_MATRIX_TRACKER.mdpython/cudnn/sdpa/fwd/api_dsl.pypython/cudnn/sdpa/fwd/config_sm100.pypython/cudnn/sdpa/fwd/config_sm107.pypython/cudnn/sdpa/fwd/engines.pypython/cudnn/sdpa/fwd/kernels/sm100/prefill_d128_fp8.pypython/cudnn/sdpa/fwd/kernels/sm107/prefill_d128_fp8.pypython/cudnn/sdpa/fwd/kernels/sm120/prefill_fp8.pypython/cudnn/sdpa/graph_analyzer.pytest/python/sdpa/block_scale_o_ref.pytest/python/sdpa/fp8.pytest/python/sdpa/frost/test_sdpa_fwd_fp8_sm100.pytest/python/sdpa/helpers.pytest/python/sdpa/random_config.pytest/python/test_mhas_v2.py
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CI status (GitLab mirror pipeline for
GitHub Review round: CodeRabbit's three findings are fixed in b38dbd2 — the SM120 O dtype domain now admits the FP4 container (the SM120 FP4 path was declining itself), the block-scaled gate in the SM100-line config keys on the kernel that carries the epilogue rather than on a flavor-name substring, and the fuzz harness folds |
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SM120 lane finding, fixed in 3db46d6. The Reproduced and verified from an SM100 box — the DSL trace runs before arch codegen, so |
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Codex bot review · model: gpt-6-astra
Reviewed 3db46d694d31 against base 2659560300cb.
The block-scaled epilogue design and the SM100/Rubin results look sound. The follow-ups fix the earlier whitelist/configuration findings and the SM120 closure compile failure. Three issues remain: one approval-blocking compatibility regression affecting ordinary SDPA, plus two localized SM120 integration gaps.
[P1 · blocks approval] Keep optional FP4 dtype lookup off ordinary SDPA paths (source)
With sf_o absent, this comparison still reads torch.float4_e2m1fn_x2 for ordinary BF16 output. The new FP8 whitelist and SM80/SM120 checks do likewise. PyTorch versions without that dtype, such as 2.7, now raise AttributeError on existing FROST paths. The package does not declare a newer Torch floor, and datatypes.py already treats FP4 as optional. Resolve the symbol with getattr and include/use it only when available. This blocks approval because an optional new output mode breaks normal pre-existing execution across architectures; the engine's build_plan decline handler also does not catch AttributeError.
Evidence: Scoped missing-attribute injection in api_dsl.torch: base accepts A100 BF16 and SM100 BF16/FP8; current head raises AttributeError at lines 4815, 1528 and 1399. All three current-head controls pass when the attribute is present. This is a symbol-availability probe, not a run with an old Torch binary. Attribution: Introduced by this PR; these ordinary paths do not perform the lookup on base.
[P1] Wire sf_o through SM120's public execute method (source)
engines.py passes sf_o to impl.execute for block-scaled output, but SdpaFwdDslSm120.execute still ends at sf_v. Adding sf_o to the private _execute_fp8 helper does not connect this public call: both output modes fail with an unexpected-keyword TypeError. Append sf_o to the public signature, check the compiled presence contract, and forward it to _execute_fp8. This remains after b38dbd2's whitelist fix. The failure is visible and confined to the new output modes, so this P1 is nonblocking.
Evidence: Current-head inspect.signature(api.execute).bind(..., sf_o=...) rejects both modes. Exact-head SM120 CI job 442655256 independently reports this TypeError in all nine new block-scaled tests and ten randomized cases. Attribution: Missing connection in the new SM120 output path.
[P2] Give SM120 scale-factor padding rows an executing owner (source)
The sf_o padding store is inside row_q < q.shape[1]. For supported dense untrimmed Q, this excludes exactly the rows whose scales must be zeroed, so the row_valid=False branch cannot clear per-plane padding. With the supported q_tile=64, S_q=300 also leaves rows 320..383 without a CTA although sf_o rounds to 384 rows. Give the last tile responsibility for all kernel-owned 128-rounded padding rows independently of O stores; moving the predicate alone does not cover the 64-row-tile case. The newly added poisoned-padding tests should exercise both tile sizes once execute is wired.
Evidence: Source-level predicate and launch-coverage proof. The zero store is nested under the logical-Q bound; grid coverage is rounded to q_tile while the scale plane is rounded to 128. Attribution: Introduced by the new SM120 block-scaled epilogue.
Validation: Reused scoped evidence from preceding heads: b38dbd2 passed all 10 focused SM100 output/decline/configuration cases; a89b542 passed 68 unique selected SM100 cases and eight SM107 GPU cases across both output modes, masks and scale layouts. The latest commit changes only the SM120 kernel and review guidance; these SM100/SM107 lowerings are unchanged. Baseline/head performance on a 68-SM SM100, DSL 4.8, Torch 2.13 and cuDNN 9.25.1: ordinary FP8 GPU times were stable at about 17.64 and 284.7 microseconds for the two samples. The 2100-token case showed a modest 4–10 microsecond CPU-call increase. New-output GPU overhead there was approximately 6.3 percent for NVFP4 and 3.5 percent for MXFP8. These are scoped spot checks, not end-to-end model timings. Earlier-head correctness also passed after CUDA Graph capture with changed Q and poisoned O/scale buffers. The benchmark dry-run succeeded. Exact-current-head probes reproduced the two adapter findings; cross-target compilation of the SM120 kernel passed for ordinary E4M3, NVFP4 and MXFP8 output. No SM120 kernel was executed locally. Reused owner-started OSS/FROST pipeline 68220224 and verified its exact head. Its SM120 job 442655256 has 3232 passes and 23 failures: 19 new sf_o TypeErrors matching the second finding, plus the four existing ragged-Stats failures. Other lanes are still pending/running; the SM80 Stats and SM90 BSA failures retain their previous signatures.
Limitations: SM120 numerical execution was unavailable locally. CI confirms the adapter failure; the separate padding finding remains a source-level control-flow/launch-coverage proof, downstream of that failure. Python tests used a compatible existing native binding, not a newly built wheel. Performance and Rubin GPU measurements were taken on a89b542, before the unchanged-kernel follow-up.
The P0/high-risk P1 findings marked above need fixes and re-review before approval.
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SM120 lane, second finding, fixed in 36dfb8d. With the compile fixed (3db46d6) the SM120 lane got one step further and failed every block-scaled draw at execute: For the record, on 3db46d6 the SM120 lane was otherwise 3232 passed; the sm103 lane on b38dbd2 ran the block-scaled tests 9/9 plus the config-gate test, and the SM107 lanes of the first two pipelines never ran (Slurm "Required node not available" → revoked). |
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CI status for the current head 9e407a1 (pipeline 68457574):
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Codex bot review · model: gpt-6-astra
Reviewed 9e407a148ead against base d34a6909c9d1.
The remaining signature/dtype test-integration comment is addressed. The updated pins preserve append-only API order, exercise the supported gated output dtypes, and reject the unsupported block-scaled-output/gate combination. The additional bare-FP4 eligibility check is consistent with the implemented epilogue. No new finding in this two-file follow-up; my earlier approval remains in place, so I am not posting another approval. The owner already started current-head CI and I reused that evidence rather than requesting another run.
Validation: Exact-head local check: both previously failing contract tests passed, with L0/L1 explicitly enabled (2 passed, 132 deselected). The numerical kernels and execute implementations are unchanged since the preceding reviewed head 5cde52f. Verified pipeline 68457574's mirrored commit records the full GitHub head 9e407a1. OSS SM80/SM90/SM100/SM107, FROST SDPA SM80/SM100/SM120, FROST GEMM/linear, builds and C++ sanitizer jobs have passed. Inspected the remaining failed-job summaries: Rubin has 3230 passed, 1831 skipped and the same 12 native ragged-decode Stats NVRTC compilation failures recorded in earlier base-related runs; api_index reports the existing missing SdpaFwdDslSm100.template_params entry. These are separate from the resolved two contract assertions. The retried SM103 job was still running when checked.
Limitations: The overall pipeline is not fully green. This follow-up adds no independent Rubin or SM120 GPU run; those current-head results are from the verified CI jobs. No new timing sweep for a change limited to eligibility checks and contract tests. Previous kernel performance/replay evidence retains its original SHA and hardware scope.
Comment only: this PR already has an active approval; preserving existing approvals.
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Update on the sm103 lane of pipeline 68457574: the retried job (444757917) also died on the runner side (Kerberos ticket acquisition failed, then the 2 h execution timeout revoked it) without running pytest. The sm103 hardware result for this PR's block-scaled tests stands from pipeline 68220224 / 68215392 (9/9 + config gate, and 4823 passed on the SM100-line file); the lane is |
… output
The per-tensor FP8 forward can now emit O as FP4_E2M1 (two per byte, one E4M3
scale per 16 d elements) or as FP8_E4M3 with one UE8M0 scale per 32 d elements,
writing the scale factors to a new optional sdpa_fp8 output ``sf_o`` in the
F8_128x4 atom order (per-(b,h) planes or one token-major matrix a downstream
GEMM consumes). The epilogue reuses the row-owning correction warps on the
d128 SM100/SM107 kernels (thread-local block amax) and a quad butterfly on the
SM120 kernel; ``scale_o`` doubles as the FP4 global scale.
Plumbing: sdpa_fp8 grows a python-only ``sf_o`` out-kwarg (backend-unlowerable
when set), graph_analyzer derives ``o_block_scale``, the fp8 engine rows
declare ``o_block_scales={0,16,32}``, and the adapter validates the declared
sf_o geometry. Tests: torch reference quantizers, frost e2e output-mode
cases, and an ``o_block_scale`` knob in the test_mhas_v2 fp8 forward suite.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…ut rows New forward-only cudnn_oss data types that run the fp8 graph with the block-scaled O epilogue (FP4 O + E4M3/16 scales, E4M3 O + UE8M0/32 scales) and its sf_o output; the runner drops other backend / pass combinations, charts get their own dtype buckets, and the wan22 video-DiT config gains the fp8 and block-scaled rows plus the 2100-token sequence-parallel shard. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…) as raw bytes torch.hash_tensor and the NaN/zero statistics have no kernels for the packed FP4 container, which the fp8 forward suite now emits under o_block_scale=16. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…k too Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…on the kernel, cover the lanes that missed it
Review round on the block-scaled O epilogues:
* SM120 lowering: the O dtype domain lacked the FP4 container, so an FP4 O
graph was declined ("no engine") although the engine row advertises it and
check_support had already derived o_block_scale = 16. The SM100 list had it.
* config for the second SM100-line arch: the block-scaled gate tested
`"d128" in flavor`, which also matches "d192xd128" and the MXFP8 flavors
whose kernels carry no block-scaled epilogue (DTYPE_O 0..3 only), deferring
the rejection to a specialization error. The gate now follows the kernel
the d128 config family builds (per-tensor FP8, tile_k = tile_o = 128), the
same way split_wired does.
* fuzz harness (sdpa/fp8.py): below SM100 no engine serves a block-scaled O,
so a drawn o_block_scale made the case skip on "unsupported forward graph";
fold it to plain fp8 there instead.
Tests: the block-scaled tests lived only in the sm100 file (gated 100..119)
and carried a copied skip marker for the second SM100-line arch, so neither
the SM120 lane nor that lane ever ran the new epilogue. Drop the marker, add
the same graph-route test (planes / token-major, none / causal, S_q = 300
tail) to the sm120 file plus an "offered" pin for the O dtype domain, share
the dequantizer via sdpa/block_scale_o_ref.dequant_block_scaled_o, and pin
the config gate with a pure-python test that runs on every lane.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…ogue closure (CI compile failure) The SM120 lane failed every o_block_scale=32 draw of test_sdpa_fp8_fwd_L0 at compile: `'NoneType' object has no attribute 'iterator'` on `sf_o.iterator.raw_ptr()` inside `_block_scaled_group`. `sf_o` reaches kernel()/_run_unit as a live tensor; the closure sees None because the DSL's region rewrite of the closure's nested dynamic ifs rebinds the free variable it touches there, which makes `sf_o` an unbound closure-local (`UnboundLocalError: local variable 'sf_o' referenced before assignment` when the name is read at the closure's top). The sm100 kernel is immune: its SF store sits in a function body where sf_o is a parameter. Fix: compute `sfo_base_ptr = sf_o.iterator.raw_ptr()` once in _run_unit's body (like `o_ptr`) and have the closure add its offset only. _run_unit's block-scaled parameters are positional now and the persistent THD call site passes them through as well. Reproduced and verified from the SM100 box: the trace runs before any arch-specific codegen, so `_load_sm120_kernel_module(...).compile( compute_capability=(12, 0), ...)` fails/passes identically here. All three O modes (E4M3, MXFP8, NVFP4) now compile. Rule S5 in python/cudnn/sdpa/AGENTS.md records the per-arch-line test coverage, the cross-arch trace repro, and the closure trap. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…execute on the SM120 lane)
With the compile fixed, the SM120 lane failed every block-scaled draw one
step later: `TypeError: SdpaFwdDslSm120.execute() got an unexpected keyword
argument 'sf_o'`. The lowering hands sf_o to execute() for any graph whose
row advertises a block-scaled O; SdpaFwdDslSm120 had it on _execute_fp8 only.
Append it to execute() (last parameter, public signatures are append-only),
mirror the SM100 presence checks, forward it to _execute_fp8.
test_sdpa_fwd_api_contract gains a tripwire that runs on every lane: both
classes whose FP8 rows advertise o_block_scales {16, 32} must accept sf_o on
execute() and _execute_fp8 (default None, last parameter).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…er entered the valid-row branch) On the SM120 lane the block-scaled O VALUES now match the reference for NVFP4 and MXFP8 output (planes and token-major), and the only remaining failure is the contract check "sf_o pad rows past S_q must be zero": the sm120 epilogue closure kept the SF store, including the pad-row zero store, inside `if row_q < q.shape[1]`, so rows past S_q never reached it. Move the SF store out of that branch (the sm100/sm107 kernels already do it this way); valid rows store the scale, per-plane pad rows inside the 128-row atom store zero, token-major stores nothing for them. The sm120 kernel also runs a 64-row Q tile (SEQ_Q_TILES = (128, 64)), under which the rows between round_up(S_q, 64) and round_up(S_q, 128) belong to no tile: the LAST tile zeroes them as well (its own rows + q_tile, guarded by the plane extent). The atom offset lives in `_sfo_atom_offset` so both stores share it. New test `test_fp8_sm120_block_scaled_output_tile64` pins the 64-row case (S_q = 300: tiles end at 320, the atom at 384). Both tile variants trace-compile for all three O modes from the SM100 box. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…t not need the packed FP4 dtype The packed FP4 dtype arrived in torch 2.8 and the torch dependency group is unversioned; the block-scaled O checks compared O's dtype against torch.float4_e2m1fn_x2 eagerly on EVERY forward (SM80/SM100/SM120 check_support, both O dtype lists), so an ordinary BF16 or FP8 graph raised AttributeError on an older torch -- and build_plan's decline handler does not catch AttributeError. Review finding on NVIDIA#1088. * api_dsl: `_torch_fp4()` (getattr with None default) and `_with_fp4()` for the dtype lists; a missing symbol never matches and never enters a list. * graph_analyzer.to_torch_dtype: a cuDNN type whose torch spelling this build lacks DECLINES (NotImplementedError, like a type with no mapping) instead of raising AttributeError at the lowering boundary. * Tests: the fuzz harness folds an NVFP4 draw to plain fp8 and the frost tests skip the FP4 cases when the dtype is absent; the API contract test deletes the symbol and runs a BF16 check_support on all three classes. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…aled O tail; FP4 O and the gate decline each other After merging develop, two of NVIDIA#1102's pure-python pins failed on every frost lane: the constructor tail now ends with `sample_sf_o` (and SM100 execute() with `sf_o`, after `gate`), and the SM107 FP8 row's out_dtypes carries FP4_E2M1 for the block-scaled epilogue. The pins record both. FP4_E2M1 is excluded from the gate x O-dtype matrix on principle rather than by list surgery: mismatch() now declines an FP4 O that is not block-scaled (a bare FP4 O has no store; the analyzer only ever derives it with sf_o) and a block-scaled O combined with the fused epilogue gate (two epilogues, one O store), and the test asserts both declines by name. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…e spin constant; move NVIDIA#1169's ring-wait pin NVIDIA#1169 made every ring wait of the Rubin prefill kernels pass `spin=SPIN_RING_WAITS` and pinned the per-kernel site counts. The block-scaled O epilogue's first `mb_o_empty` wait is one more ring wait on the d128 per-tensor FP8 kernel: give it the same spin constant (its three siblings already have it) and move the pin from 43 to 44 ring sites. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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Rebased onto develop Local on the rebased tree with a freshly built extension: frost fp8 SM100 (block-scaled, output dtypes, log2, masks), the signature/dtype pins, contract, config, analyzer, validate and heuristics suites, the graph-route smokes (planes + token-major) and an mhas fp8 slice — all green. One follow-up commit on top: the sm107 epilogue's O-empty wait now passes like its siblings and #1169's ring-wait pin moves from 43 to 44 sites. CI re-triggered on 7b301f0. |
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…n sf_o output on the d128 MXFP8 kernels (#1180) * FROST SDPA mxfp8: block-scaled O epilogues (NVFP4 / MXFP8 out) with an sf_o output on the SM100 d128 kernel The per-tensor FP8 forward gained NVFP4 / MXFP8-out epilogues in #1088; the MXFP8-input forward gets the same contract: * graph: `graph.sdpa_mxfp8(..., sf_o=<tensor>)` -- FP4_E2M1 O + E4M3 scale per 16 d, or FP8_E4M3 O + UE8M0 scale per 32 d; sf_o is a python-only output (no backend field). sdpa_mxfp8 has no per-tensor O scale otherwise, so it gains a python-only `scale_o` INPUT: the FP4 global scale the epilogue folds into O -- REQUIRED for an FP4 O (the E4M3 block scale alone cannot span O's range), optional with the UE8M0 mode, rejected without sf_o. Validation, analyzer facts (o_block_scale / scale_o_t) and the engine rows (FP4_E2M1 out dtype, o_block_scales {0, 16, 32}) follow. * kernel (sm100/prefill_d128_mxfp8): O_ROW_BYTES / O_PACK_DIV geometry, the E4M3 byte-container storage dtype for codes 4 / 5, `scale_o_t` read on device and folded into inv_sum (exactly 1.0 when the mode is off), and the block-scaled arm of the correction-warp epilogue ported from the fp8 kernel (plain head_idx / plane math: PackGQA is declined row-wide here, amax gated on EMIT_AMAX_O); trailing sf_o parameters + compile fakes. * api: SdpaFwdDslSm100.check_support admits sf_o on both quantized paths; _execute_mxfp8 binds the FP4 byte container, the SF_O geometry and the scale (cached 1.0 when omitted) and divides Amax_O back to pre-scale. * tests: test_sdpa_fwd_mxfp8_sm100 gains the block-scaled knobs and tests (planes / token-major x none / causal x both modes, scale_o on the UE8M0 mode, FP4-needs-scale_o and wide-flavor declines); 11/11 on B200. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> * FROST SDPA mxfp8 (Rubin line): block-scaled O epilogues on the sm107 d128 kernel; config gate covers both d128 kernels Port of the previous commit's epilogue to sm107/prefill_d128_mxfp8.py with the Rubin kernel's idioms: `_kv_empty` for the dead-row predicate, `q_row_global < q_row_limit` for the valid-row gate, `fmax_f32` for the amax fold, `spin=SPIN_RING_WAITS` on the O-empty ring wait, no partial-O slot in _host (the SF_O buffer + scale append after the SF-tile counts). `scale_o_t` is read on device and folded into inv_sum (exactly 1.0 when the mode is off). All three O modes trace-compile from the SM100 box. config_sm107: `block_scaled_o_wired` now keys on the d128 tile geometry alone -- both d128 kernels carry the epilogue; the d192xd128 siblings still decline. Pins moved: the config-gate test lists d128 mxfp8 as wired, the MXFP8 d128 ring-wait count goes 35 -> 36 (the epilogue's first O-empty wait), the gate x O-dtype matrix on the sm107 MXFP8 row excludes FP4_E2M1 and asserts the two mutual declines, and the API contract tripwire also requires `sf_o` on `_execute_mxfp8` where the class has one. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> * tests/benchmark: block-scaled O (sf_o) on the mhas_v2 MXFP8 forward suite and the attention benchmarks test_mhas_v2 / sdpa/mxfp8.py: test_sdpa_mxfp8_fwd_L0 draws o_block_scale (0 / 16 / 32) like the fp8 forward suite. The harness builds the sdpa_mxfp8 graph with the sf_o output (per-(b, h) F8_128x4 planes) and, for FP4 O, the python-only scale_o input; lays Q/K/V/O out BSHD-physical for those draws (the FROST MXFP8 engine's layout -- plain draws keep BHSD); dequantizes the block-scaled O against the fp32 reference in scale_o units within the MXFP8 pipeline tolerance plus three times the reference's own block-quantization floor; and checks the per-plane pad rows and the pre-scale Amax_O. The draw folds to 0 where the epilogue cannot run -- d != 128, unfuse_fma (a backend-only attribute the FROST engines decline), a KV tail that is not a whole 128-tile without a covering causal band (mirror of engines._band_covers_kv_tail), FROST engines off -- and an admitted draw that is declined FAILS rather than skips, so a stale mirror or an engine regression stays visible. benchmark/attention_training: mxfp8_nvfp4 / mxfp8_mxfp8 data types (MXFP8 inputs with the block-scaled O epilogue and its sf_o output via sdpa_mxfp8; forward-only, cudnn_oss), the runner's backend/pass filter, chart buckets and labels, the wan22 rows (plus the plain mxfp8 baseline), README example. SUPPORT_MATRIX_TRACKER: the block-scaled O row covers both quantized flavors; the SM107 table gains its own row. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> * review round: an omitted scale_o is compiled out (identity fold); the mhas fold keys on the MXFP8 engine rows' arch range P1 (Codex bot review): sdpa_mxfp8's scale_o is optional, and the lowering bound a cached torch.ones for a missing one -- created on the plan's FIRST execute, so a first execute under CUDA-graph capture allocated it but only captured its fill, and an eager execute before the first replay read garbage (all-zero O, NaN Amax_O). The scale operand is now a compile form of the kernel: `SdpaFwdDsl(sample_scale_o=...)` (appended, append-only signature) -> `compile(has_scale_o=...)` on both d128 MXFP8 kernels -> the None-specialized operand folds an identity in the kernel. execute() binds scale_o only in the specialization that has it and raises on a mismatch; the lowering derives the form from the graph's scale_o. No device constant exists for the identity at any level (Rule 8). Tests: the frost mxfp8 file gains a first-execute-captured-then-eager regression on the UE8M0 mode, the API contract file a source pin (no cached dummy on the MXFP8 path; sample_scale_o last), and the SM107 constructor-tail pin moves. P2: the mhas MXFP8 harness admitted block-scaled draws on every cc >= 10, so the SM120 lane (no MXFP8 engine) failed its three admitted draws instead of folding them. The fold is now the pure predicate `block_scaled_o_draw`, keyed on the FROST MXFP8 prefill rows' sm_lo..sm_hi (engines.py is the source of truth) plus the existing rules; `test/python/sdpa/test_mxfp8_block_scaled_fold.py` pins it on every lane (SM100/103/107/110 admit; SM80/90/120 fold; unfuse_fma, head dim, KV-tail, engines-off and FP4-dtype cases). Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> --------- Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
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Summary
Block-scaled O epilogues for the FROST per-tensor FP8 SDPA forward, on the d128 flavor of the SM100, SM107 and SM120 kernels:
FP4_E2M1(two per byte) with one E4M3 scale factor per 16 head-dim elements;scale_odoubles as the FP4 global scale.FP8_E4M3with one UE8M0 scale factor per 32 head-dim elements (no global amax needed).Both write their scale factors to a new optional
sdpa_fp8output,sf_o, in the F8_128x4 atom order — declared either as per-(b,h) planes ([B, H, S rounded to 128, d/block rounded to 4], BHRC strides) or as one token-major matrix a downstream block-scaled GEMM consumes directly ([B*S, H*d/block], BRHC strides). The graph route is the existinggraph.sdpa_fp8(O dtypeFP4_E2M1, orFP8_E4M3+sf_o); no new entry point.Kernel side: the SM100/SM107 correction warps already own one O row in 16-column TMEM chunks, so a block's amax is thread-local and the E2M1 pack rides the existing SMEM/TMA store (64 B rows). SM120 uses a 4-lane butterfly over the quad that shares a 16-column fragment. Pad rows inside a plane's 128-row extent are zeroed; token-major tails are caller-owned (zero-initialize the buffer).
Plumbing: python-only
sf_oout-kwarg (a graph that sets it is backend-unlowerable),graph_analyzer.o_block_scale,Capabilities.o_block_scales={0,16,32}on the fp8 rows, adapter validation of the declaredsf_ogeometry,_sdpa_validaterules. Dense, unsplit, unpacked, untrimmed graphs only (declined otherwise).Tests:
test/python/sdpa/block_scale_o_ref.py(torch reference quantizers + swizzle),test_fp8_block_scaled_output(both modes × masks × layouts, GQA, tail tile) and a decline test in the frost fp8 suite, and ano_block_scaleknob (0/16/32) in thetest_mhas_v2fp8 forward suite. Benchmarks:fp8_nvfp4/fp8_mxfp8data types inbenchmark/attention_training(forward-only,cudnn_oss), thewan22config gains fp8 + block-scaled rows and the 2100-token shard.Validated on B200 (SM100):
test_mhas_v2::test_sdpa_fp8_fwd_L0slice with the newo_block_scaledraw: 224 passed, 168 skipped, 0 failed.Amax_Omatches.cudnn_ossfwd, H=40 d=128 no mask (median of 20): S=2100: fp8 0.104 ms / nvfp4-O 0.118 ms / mxfp8-O 0.112 ms; S=7800: fp8 0.846 ms / nvfp4-O 0.869 ms / mxfp8-O 0.858 ms.SM107 and SM120 are line-for-line ports of the SM100 epilogue (CI lanes).
Test plan
pytest test/python/sdpa/frost/test_sdpa_fwd_fp8_sm100.py -k block_scaledon SM100 / SM103 / SM107 / SM120 lanespytest test/python/test_mhas_v2.py -k test_sdpa_fp8_fwd_L0(drawso_block_scalein 1/4 of configs)python -m benchmark.attention_training.runner --config wan22 --dry-run🤖 Generated with Claude Code
Summary by CodeRabbit
New Features
Documentation
Tests