fix(kda): accept SM107 (Rubin) in the FlashKDA family guards - #4710
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top_k_varlen declared no support for compute capability 107 on any of its
three backends, so every call on Rubin failed:
BackendSupportedError: top_k_varlen does not support backend
'radix_cutlass' with capability 107
BackendSupportedError: No suitable auto backends found for top_k_varlen
The second is a consequence of the first: with every backend declining 107,
backend="auto" has nothing to route to.
radix_cutlass is the architecture-independent masked-radix fallback and its
checker already returns True unconditionally -- 107 was simply missing from
_ALL_CCS. Compare _HASH_TOPK_SUPPORTED_CC in fused_moe/hash_topk.py, which
lists the same tiers *including* 107.
The CuTe DSL radix backend is likewise family-portable, so 107 is added to
_BLACKWELL_PLUS_CCS. Enabling it needs one extra guard: DSL releases before
4.8 have no sm_107a member in cutlass.base_dsl.arch.Arch, so compiling on
Rubin raises KeyError: 'sm_107a' unless CUTE_DSL_ARCH=sm_100f was exported
before cutlass was first imported. _radix_top_k_varlen_check now consults
is_cute_dsl_arch_supported() so that configuration declines cleanly and auto
falls back to radix_cutlass instead of crashing.
_GVR_CCS is deliberately left at [100, 103]: GVR is documented as B200-class
only and enabling it on Rubin needs hardware validation, not a list edit.
Validated on SM107 hardware. With CuTe DSL 4.8, tests/topk_varlen passes
48 tests. With public CuTe DSL 4.7.0 and no CUTE_DSL_ARCH the radix backend
declines and radix_cutlass serves the call; with CUTE_DSL_ARCH=sm_100f the
sm_100f family kernel compiles and runs.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The family build of the FlashKDA bindings is compiled for sm_100f
(_FLASH_KDA_NVCC_FLAGS["sm100f"] -> -gencode=arch=compute_100f,code=sm_100f),
a family-conditional target valid across the whole SM100 line -- including
SM107 (Rubin). The runtime guard, however, admitted only 10.0 and 10.3, so
Rubin aborted with
RuntimeError: Check failed: (major == 10 && (minor == 0 || minor == 3))
is false: this FlashKDA module was compiled for the SM100 family
(compute capability 10.0 or 10.3), got 10.7
The check was therefore stricter than the binary it guards: a sm_100f cubin
loads and runs on 10.7, but the ICHECK rejected the device before launch.
Widen the family predicate to 10.0/10.3/10.7 at all four binding sites and
update the diagnostic text accordingly.
The exact-target branch (FLASHINFER_FLASH_KDA_TARGET_MINOR, sm100a builds) is
deliberately untouched -- an sm_100a cubin genuinely is not runnable on 10.7.
Verified on SM107 hardware: with the widened header the freshly JIT-compiled
sm_100f module builds and loads on a 10.7 device, and the rebuilt binary
carries the new predicate. Note this widens the C++ guard only; the Python
entry points still restrict KDA to 10.0/10.3, so enabling KDA on Rubin
end-to-end remains separate work.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
… (Rubin)
tinygemm_bf16 restricted its generated (tinygemm2_sm100) bias path to compute
capability 10.0 and 10.3, so Rubin silently fell back to the reference kernel
and the dispatch test failed:
assert False + where False = <function _use_tinygemm2_sm100>
The restriction was conservative rather than technical. csrc/tinygemm2_sm100.cu
contains no SM100-exclusive ISA -- no tcgen05, no __CUDA_ARCH__ specialisation;
the variants are Loom schedules of the same TMA + mma.sync kernel with
bit-identical outputs. They are family-portable across the SM100 line.
Three coordinated changes are needed, since the capability tuple alone would
have dispatched Rubin into a module built without a compatible cubin:
* jit: build from current_compilation_context.get_nvcc_flags_list() with
map_sm107_to_100f=True instead of hardcoding 100a+103a gencode. SM107 then
targets sm_100f while the bundled CUTLASS lacks native compute_107a, and
picks up sm_107a automatically once it does -- the same idiom the rest of
the tree already uses.
* csrc: widen the runtime ICHECK to 10.0/10.3/10.7 so the guard matches the
binary it protects.
* python: add (10, 7) to _TINYGEMM2_SM100_SUPPORTED_COMPUTE_CAPABILITIES.
The tuple stays explicit rather than testing major==10, because other 10.x
devices still must use the reference kernel.
Verified on SM107 hardware: the spec resolves to
-gencode=arch=compute_100f,code=sm_100f, the generated path is selected, and
tinygemm_bf16 matches torch.nn.functional.linear exactly (max abs err 0).
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The CuTe DSL gather/finalize grouped GEMM kernels raise deliberate NotImplementedErrors on Rubin for three features the kernel does not have yet: * use_a_per_token_scale -- the Rubin wrapper has no a_per_token_scale_ptr * activation_type GegluTanh -- the FC1 fusion is SwiGLU-only * use_fused_finalize=False -- the Rubin kernel always scatter-adds These are documented product limitations, not regressions, so the affected parameterizations should be expected failures rather than errors. Matching on the message in a runtest wrapper -- mirroring the existing OOM/JIT-cache wrapper in tests/conftest.py -- covers every parameterization across all four MoE test files without pinning 100+ node ids that churn on every parameter change. Measured on SM107 hardware: tests/moe/test_cute_dsl_fused_moe.py goes from 93 failed / 294 passed to 27 failed / 293 passed / 67 xfailed. The remaining 27 failures are unrelated and deliberately left failing. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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📝 WalkthroughWalkthroughThe change adds compute capability 10.7 support to SM100-family validation and tinygemm2 dispatch. It updates CUDA compilation flags, diagnostics, documentation, tests, and radix backend capability checks. ChangesSM107 support
Estimated code review effort: 2 (Simple) | ~10 minutes Merge Risk: 🔵 Low · up to The PR’s runtime behavior is bounded to SM107 capability selection and fallback paths. A test helper may still run on unsupported SM10.x hardware instead of skipping, which can cause CI or test failures; this is a minor follow-up issue without an indicated production-path defect. Sequence Diagram(s)sequenceDiagram
participant RadixCheck as _radix_top_k_varlen_check
participant DSLCheck as is_cute_dsl_arch_supported
participant Capability as get_compute_capability
participant Backend as backend="auto"
RadixCheck->>DSLCheck: check DSL support
RadixCheck->>Capability: read device capability
DSLCheck-->>RadixCheck: return support result
Capability-->>RadixCheck: return compute capability
RadixCheck-->>Backend: select radix or radix_cutlass
Suggested reviewers: 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
Full details: Description checkExplanation The description gives detailed scope, rationale, affected files, validation results, cache-key concerns, and known failures. It does not use the template headings for Related Issues or the Pull Request Checklist, but it is otherwise complete and relevant.
✨ Finishing Touches 💡 1🛠️ Fix failing CI checks 💡
🧪 Generate unit tests (beta)
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Inline comments:
In `@flashinfer/gemm/routergemm.py`:
- Around line 493-499: Update the tinygemm_bf16 docstring to document SM107 and
Rubin alongside the existing SM100/SM103 and B200/B300 entries, matching the
dispatch behavior represented by
_TINYGEMM2_SM100_SUPPORTED_COMPUTE_CAPABILITIES.
In `@tests/moe/conftest.py`:
- Around line 45-46: Add pluggy>=1.1.0 to the test dependency declarations so
the pytest_runtest_call hook using wrapper=True has a compatible pluggy version.
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📒 Files selected for processing (11)
csrc/kda/cake_flashkda_packed_t1_binding.cuhcsrc/kda/cake_kda_packed_t1_binding.cuhcsrc/kda/flashkda_binding_common.cuhcsrc/kda/flashkda_decode_binding_common.cuhcsrc/tinygemm2_sm100.cuflashinfer/gemm/routergemm.pyflashinfer/jit/tinygemm2.pyflashinfer/topk_varlen/topk_varlen.pytests/jit/test_flash_kda_decode_jit.pytests/jit/test_flash_kda_packed_t1_jit.pytests/moe/conftest.py
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The previous commit routed SM107 to the generated tinygemm2_sm100 path but left two descriptions behind: the public tinygemm_bf16 docstring and the module-level comment above get_tinygemm2_sm100_module both still claimed the generated path is selected only on SM100/SM103 (B200/B300 class). Documentation only; no behaviour change. The SM100/SM103 wording on mm_M1_16_* is left alone -- those ops do not route through this dispatch. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This PR widens the device check in csrc/kda/flashkda_binding_common.cuh from
(10.0, 10.3) to (10.0, 10.3, 10.7). That header is hashed into the FlashKDA JIT
module identifiers, which are checked-in constants rather than runtime hashes,
so changing it invalidates every cache key that covers it -- 134 CI failures
across B300, GB200, GB300, H100 and RTX Pro 6000, all of the form
AssertionError: assert '80823a852f' == '41828f5029'
Recompute the affected identifiers:
* flash_kda.py -- all 11 variants in _COMMON_HEADER_VARIANT_BODIES, whose keys
hash body + binding + flashkda_binding_common.cuh.
* flash_kda_training.py -- _FLASH_KDA_TRAINING_MODULE_IDENT, which hashes the
seven target sources plus the same header.
* test_flash_kda_prefill_jit.py -- the two _H12_CASES module_idents and the two
identifiers embedded in expected module names.
The computation was validated by reproducing all 11 of main's checked-in
identifiers byte-for-byte from main's tree before applying it to this branch.
Two notes for review:
* _FLASH_KDA_TRAINING_MODULE_IDENT was ALREADY stale on main: main pins
4fdc70e98a while main's own sources hash to 7655067ef9. That is why the bot
reports part of the training failure as pre-existing on H100/CUDA 13.0. This
change sets it to the correct value for this branch and incidentally repairs
that.
* _FLASH_KDA_BACKWARD_MODULE_IDENT is deliberately NOT touched: its documented
basis is the four bodies/bindings only, excluding the shared header, so the
gate change does not affect it. The bt16_* identifiers are also untouched --
they follow neither the with-header nor without-header formula, no test
asserts them, and I could not verify their basis. Worth confirming with the
KDA owner whether either should cover the shared header.
flashinfer-bot
added
op: misc
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/bot run tests/gemm tests/topk_varlen tests/jit |
Collaborator
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[FAILED] Pipeline #65715002 — 6/16 executed test jobs passed Compared with nightly #65618325. Unit Tests
✅ Pass · 🟡 Old failure · ❌ New failure · ⏱ Test timeout · Multi-GPU and Multi-Node Tests — 6/6 passed
Failure detailsNew relative to nightly (attribution uncertain)
Timeouts, infrastructure, or incomplete jobs
|
test_flash_kda_training_jit failed on every GPU in pipeline 65715002 (18
failures):
assert 'flash_kda_training_b230e1a508_sm100a'
== 'flash_kda_training_118da6c1ae_sm100a'
_FLASH_KDA_TRAINING_MODULE_IDENT was refreshed in d0628e6, but the merge in
f4b7986 landed 25 seconds earlier and pulled in flashinfer-ai#4675, which edits
flashkda_binding_common.cuh -- one of the files the digest covers. The constant
was therefore computed against the pre-merge tree and went stale immediately.
Recomputed with the test's own formula (SHA-256 over the target's source list
plus the shared binding header, NUL-separated, first 10 hex digits):
118da6c1ae for both sm100a and sm103a, so one constant still covers both
targets.
The other FlashKDA cache keys in flash_kda.py are unaffected -- the pipeline
ran test_flash_kda_{decode,prefill,packed_t1,backward}_jit and
test_cake_kda_packed_t1_jit and all passed.
Resolution rule: take main where main has changed; otherwise stay aligned with release-v0.6.18. Main has since landed flashinfer-ai#4849 (tinygemm2 on SM107) and flashinfer-ai#4621 (top_k_varlen on SM107), which independently deliver most of what this branch carried. All four conflicts are in files those PRs rewrote, so main wins wholesale -- the four files are now byte-identical to main: * csrc/tinygemm2_sm100.cu -- main gates the SM107 arm on a CUDA 13.4+ toolkit (kSupportsSm107). Strictly better than this branch's unconditional `minor == 7`; taking our side would have regressed it. * flashinfer/jit/tinygemm2.py -- main emits native compute_107a when the toolkit allows, replacing release's map_sm107_to_100f. This must stay paired with the csrc guard above. * flashinfer/gemm/routergemm.py -- comment only; same capability tuple. * flashinfer/topk_varlen/topk_varlen.py -- main refactored the probe into _cute_dsl_ready(). What remains is the FlashKDA work, which main does not have and which stays aligned with release-v0.6.18: all four csrc/kda guards read `minor == 0 || minor == 3 || minor == 7`, matching release exactly. Verified after merging: * _FLASH_KDA_TRAINING_MODULE_IDENT still matches the recomputed digest (118da6c1ae, both targets) -- main did not touch the KDA training sources. * tests/model_optimizations/test_tinygemm2_sm100.py is untouched by main, so the CodeRabbit-requested capability gate is kept, extended to mirror flashinfer-ai#4849's CUDA 13.4 condition: without it an SM107 device on an older toolkit would reach the kernel's TVM_FFI_ICHECK instead of skipping.
Contributor
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/bot run tests/gemm tests/topk_varlen tests/jit |
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@flashinfer-bot run |
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[FAILED] Pipeline #65881169 — 9/16 executed test jobs passed Compared with nightly #65814627 (different CI configuration). Unit Tests
✅ Pass · 🟡 Old failure · ❌ New failure · ⏱ Test timeout · Multi-GPU and Multi-Node Tests — 4/6 passed
Failure detailsCould not compare
Timeouts, infrastructure, or incomplete jobs
|
Vinnie6167
changed the title
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/bot run tests/jit tests/model_optimizations tests/kda |
Collaborator
tests/model_optimizations/test_tinygemm2_sm100.py is restored to main. The change belongs with flashinfer-ai#4849, which enabled tinygemm2 on SM107 but shipped only three files (csrc, routergemm, jit) and left the test untouched. It is also flashinfer-ai#4849 that made the kernel's SM107 arm conditional on a CUDA 13.4+ toolkit, widening the gap between the test's gate (is_sm100a_supported, i.e. major == 10) and the kernel's, so the fix belongs in a follow-up there rather than in a FlashKDA PR. This PR is now FlashKDA only.
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Author
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@flashinfer-bot run |
Collaborator
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/bot run tests/jit tests/kda |
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[FAILED] Pipeline #65937241 — 16/17 executed test jobs passed Compared with nightly #65814627 (different CI configuration). Unit Tests
✅ Pass · 🟡 Old failure · ❌ New failure · ⏱ Test timeout · Multi-GPU and Multi-Node Tests — 6/6 passed
Failure detailsTimeouts, infrastructure, or incomplete jobs
|
bkryu
approved these changes
Sep 3, 2026
This was referenced Sep 3, 2026
[KDA] Unify the public
recurrent_kda API, and settle the unreleased KDA surface before FI v0.7
#4936
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Summary
Accept SM107 (Rubin) in the FlashKDA runtime guards, and refresh the JIT cache
keys that the guard edit invalidates.
1.
fix(kda)— FlashKDA family guardThe family build is compiled for
sm_100f, a family-conditional target validacross the whole SM100 line including 10.7, but the runtime
TVM_FFI_ICHECKadmitted only 10.0/10.3. The check was stricter than the binary it guards.
Widened at all four binding sites:
csrc/kda/flashkda_binding_common.cuhcsrc/kda/flashkda_decode_binding_common.cuhcsrc/kda/cake_kda_packed_t1_binding.cuhcsrc/kda/cake_flashkda_packed_t1_binding.cuhThe exact-target branch (
FLASHINFER_FLASH_KDA_TARGET_MINOR,sm100abuilds)is deliberately untouched — an
sm_100acubin genuinely is not runnable on 10.7.This widens the C++ guard only; the Python entry points still restrict KDA to
10.0/10.3, so enabling KDA on Rubin end-to-end remains separate work.
2.
fix(jit)— refresh the FlashKDA cache keys_FLASH_KDA_MODULE_IDENTSand_FLASH_KDA_TRAINING_MODULE_IDENTare SHA-256digests over each variant's sources plus the shared binding header, so
editing
flashkda_binding_common.cuhinvalidates them by construction. Elevenof the eighteen variant keys change here, along with the training key
(
118da6c1ae) and the threetests/jit/test_flash_kda_*assertions that pinthem.
This is the trap in this PR. The keys went stale twice during review —
once when the guard was first widened, and again when a
mainmerge pulled in#4675, which also edits that header. Both times CI failed identically:
Anyone rebasing or merging
maininto this branch must recompute the digestsafterwards, not just resolve the textual conflict.
tests/jit/recomputes themfrom the files, so a green
test_flash_kda_*_jitrun is the check.Validation
sm_100fmodule builds and loads on 10.7test_flash_kda_training_jit18 failures across B300/GB200/GB300/H100/RTX Pro 6000118da6c1aeNo behaviour change on any non-107 device: every edit either adds 107 to a
predicate that previously excluded it, or refreshes a cache key.
Notes
mainhas been merged in twice (f4b79869d,0e4ed81a3). The secondresolution took
main's side wholesale oncsrc/tinygemm2_sm100.cu,flashinfer/jit/tinygemm2.py,flashinfer/gemm/routergemm.pyandflashinfer/topk_varlen/topk_varlen.py, since feat(gemm): enable tinygemm2_sm100 on SM107 (Rubin) #4849/Enable top_k_varlen on Rubin (SM107) and add the DKG filtered-radix backend (radix_filter) #4621 rewrote them — inparticular
main's tinygemm2 gate is a superset of what this branch had.tests/model_optimizations/test_tinygemm2_sm100.pycapability-gate fix wasdropped from this PR (
1921d560c) as out of scope. It belongs with feat(gemm): enable tinygemm2_sm100 on SM107 (Rubin) #4849,which enabled tinygemm2 on SM107 but shipped only three files and left the
test's gate (
is_sm100a_supported, i.e.major == 10) looser than thekernel's. Still unlanded — needs a follow-up PR.
tests.gemm.test_groupwise_scaled_gemm_fp8,1 failure on GB200 / CUDA 12.9. This PR touches no groupwise or scaled-GEMM code.