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Share actual elementwise map kernels through dedicated lower host dispatch instantiations, with declarations in launcher headers and CUDA definitions in ordinary owners.
The existing generate_inst_matrix expands normal JSON matrices directly into 171 independently compiled CUDA translation units, one concrete instantiation per TU. Raw map dispatch has its own matrix and CUDA template; generated extern declarations let view, pointer and scalar wrappers share the same device kernels. No singleton matrix, grouped/unity build, .cu inclusion, ownership/implementation header, RDC or new CMake module is used.
Missing Hamming-label, binary-IVF and multi-GPU k-means variants are included. Map/add declarations and explicit instantiations export the host symbols used by external test consumers.
CUDA
Frozen parent MB
Head MB
Saved MB
12.9
558.411504
563.748152
−5.336648
13.3
285.125768
290.139792
−5.014024
Negative savings mean real standalone growth. Compared with the prior grouped owner, the new layout adds 8.226464 MB / 6.375072 MB (CUDA 12.9 / 13.3). Compressed fatbin containers and repeated host text/metadata account for that increase. This prerequisite still establishes shared device ownership for dependent groups; its standalone delta must not be added to other PR deltas.
Validation: real repository CMake registers 171 independent compile rules, each with one explicit instantiation. The final SM90 census preserves all 313 device kernels with zero duplicates and no unresolved lower-map host references. All applicable pre-commit hooks pass with the actual RAPIDS CMake formatting/lint policy. All 342 owner references compile freshly across the supported native profiles and PTX on CUDA 12.9/13.3; 315 unchanged caller references have compiler-dependency reuse proofs. Both complete libraries are freshly linked, ABI-checked and stripped. The prior current-main library/test links and 17 targeted GPU cases remain recorded in the tracker.
Measurement uses the accepted frozen paired-library basis, Release/GCC13 and unchanged compression flags; CUDA 12.9 covers SM70/75/80/86/90a/100f/120a/120 plus compute_120 PTX, while 13.3 excludes SM70. Of 171 owners, 170 use the frozen stock dependency/header context. One newer-main bitwise_decode_op owner uses its exact signed current source/header/dependency context because that type does not exist in the older frozen dependency snapshot; this real owner is included in both measured head libraries, with its provenance and host-closure checks recorded. These are frozen-baseline measurements, not fresh current-main package sizes or a uniform stock-dependency build.
Tracked in NVIDIA/cuvs#2888. Whole-swarm totals are being remeasured for the per-instantiation layout; older grouped-owner totals do not describe this revision.
Reviewing files that changed from the base of the PR and between 1f63855 and fa49f22.
Files selected for processing: 17
cpp/CMakeLists.txt
cpp/src/core/add.cu.in
cpp/src/core/addScalar.cu.in
cpp/src/core/addScalar_matrix.json
cpp/src/core/add_matrix.json
cpp/src/core/map.cu.in
cpp/src/core/map_detail.cu.in
cpp/src/core/map_detail_matrix.json
cpp/src/core/map_matrix.json
cpp/src/core/map_offset.cu.in
cpp/src/core/map_offset_matrix.json
cpp/src/core/multiply_scalar.cu.in
cpp/src/core/multiply_scalar_matrix.json
cpp/src/core/power_scalar.cu.in
cpp/src/core/power_scalar_matrix.json
cpp/src/core/unaryOp.cu.in
cpp/src/core/unaryOp_matrix.json
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📝 Summary
Summary by CodeRabbit
Performance
Improved the consistency of GPU operations across clustering, distance, neighbor search, preprocessing, and sparse-neighbor workflows.
Bug Fixes
Improved CAGRA search handling for queries with padded dimensions, including processing queries individually when needed.
The PR adds cuVS elementwise launchers with generated CUDA instantiations, then migrates selected RAFT elementwise calls across clustering, distance, neighbor search, quantization, and sparse-neighbor code.
Changes: Elementwise launcher migration
Layer / File(s)
Summary
Launcher contracts, implementations, and build cpp/src/core/map_launchers.hpp, cpp/src/core/*.cu.in, cpp/src/core/*_matrix.json, cpp/src/core/bitset.cu, cpp/CMakeLists.txt
Declares cuVS map, offset-map, arithmetic, and unary-operation launchers. Adds forwarding implementations and explicit-instantiation metadata. CMake generates and compiles the CUDA sources.
No actionable issue is established that would prevent merging after normal checks.
Pre-merge checks: 4 · 1
Failed checks: 1 warning
Check name
Status
Explanation
Resolution
Docstring Coverage
Docstring coverage is 16.67% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Documentation-only edits and deletions within surv…
Write docstrings for the functions missing them to satisfy the coverage threshold.
Passed checks: 4 passed
Check name
Status
Explanation
Title check
The title clearly summarizes the primary change: sharing RAFT elementwise-map kernel instantiations.
Description check
The description directly explains the dedicated CUDA instantiations, launcher declarations, generated extern declarations, included variants, validation, and measured impact.
Linked Issues check
Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check
Check skipped because no linked issues were found for this pull request.
Full details: Docstring Coverage
Explanation
Docstring coverage is 16.67% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Documentation-only edits and deletions within surviving functions are included; unchanged diff context and fully deleted functions are excluded. Analyzed 6 functions across 6 files. (17 skipped: 17 unsupported.)
Resolution
Write docstrings for the functions missing them to satisfy the coverage threshold.
Finishing Touches
🧪 Generate unit tests (beta)
Commit to this branch
Create a new PR
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Actionable comments posted: 6
🪄 Fix comments: Fix CodeRabbit comments on this PR
Prompt to fix review comments
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Inline comments:
Review comments at @cpp/src/cluster/detail/kmeans_balanced.cuh:
- Line 644: Update the half-precision balanced prediction conversion at
cuvs::detail::map so its NativeIdxT=int and LabelT=int or uint32_t variants are
available at link time; add the required map instantiations or retain the
existing RAFT call.
- Line 244: Update the map call in predict_bitwise_hamming to use RAFT’s linalg
map implementation, avoiding the missing generated cuvs::detail::map variant
while preserving the existing input and composed operation.
Review comments at @cpp/src/cluster/detail/kmeans_mg_distributed_init.cuh:
- Line 437: Update the mdspan sum in init_centroids_for_mg_batched to use RAFT’s
raft::linalg::add overload instead of cuvs::detail::add, preserving the existing
arguments and behavior for float and double.
Review comments at @cpp/src/core/addScalar.cu:
- Around line 13-17: Update the `addScalar` template in this file so the
multi-GPU tree-merge callers have a linkable definition: explicitly instantiate
it for the index and length types used by generated search entrypoints,
including `int64_t`, or place its definition where those callers can instantiate
it.
Review comments at @cpp/src/neighbors/ivf_binary/ivf_binary_search.cuh:
- Line 109: Add the missing instantiation variant to map_matrix.json for the
cuvs::detail::map call in ivf_binary_search.cuh: a float output matrix,
raft::cast_op<float>, and a const uint32_t input matrix indexed by int64_t.
Ensure the generated instantiations define this argument combination.
Review comments at @cpp/src/sparse/neighbors/detail/cross_component_nn.cuh:
- Line 418: Update the generated launcher coverage for cross_component_nn so
every supported value_idx and value_t combination, including
cross_component_nn<long, double>, has a matching definition. Add the missing
variants to map_matrix.json, or constrain the template to the supported
combinations and document that limitation.
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✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 86.93%. Comparing base (bb8251f) to head (fa49f22). ⚠️ Report is 1 commits behind head on main.
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Just had 2 questions, the inline one and for my own curiosity: whether you could clarify what the “313 kernels, zero duplicates” result covers? The raft::matrix::fill calls in kmeans.cuh:995 and knn_brute_force.cuh:166 still go through RAFT’s header-only map implementation, and I don’t see matching extern declarations along those paths.
Does the census include those emissions in the full library, or is it checking the new owner TUs? If those callers are being migrated in the dependent PRs, could we make that scope explicit next to the result?
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Could we generate these externs from the same matrix used by map.cu.in, with the relevant subset for each owner? The add, offset, and scalar owners currently maintain these lists by hand. It seems easy for the matrix and the extern lists to drift as we add variants, which could quietly bring back duplicate kernels. What do you think?
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Share actual elementwise map kernels through dedicated lower host dispatch instantiations, with declarations in launcher headers and CUDA definitions in ordinary owners.
The existing
generate_inst_matrixexpands normal JSON matrices directly into 171 independently compiled CUDA translation units, one concrete instantiation per TU. Raw map dispatch has its own matrix and CUDA template; generated extern declarations let view, pointer and scalar wrappers share the same device kernels. No singleton matrix, grouped/unity build,.cuinclusion, ownership/implementation header, RDC or new CMake module is used.Missing Hamming-label, binary-IVF and multi-GPU k-means variants are included. Map/add declarations and explicit instantiations export the host symbols used by external test consumers.
Negative savings mean real standalone growth. Compared with the prior grouped owner, the new layout adds 8.226464 MB / 6.375072 MB (CUDA 12.9 / 13.3). Compressed fatbin containers and repeated host text/metadata account for that increase. This prerequisite still establishes shared device ownership for dependent groups; its standalone delta must not be added to other PR deltas.
Validation: real repository CMake registers 171 independent compile rules, each with one explicit instantiation. The final SM90 census preserves all 313 device kernels with zero duplicates and no unresolved lower-map host references. All applicable pre-commit hooks pass with the actual RAPIDS CMake formatting/lint policy. All 342 owner references compile freshly across the supported native profiles and PTX on CUDA 12.9/13.3; 315 unchanged caller references have compiler-dependency reuse proofs. Both complete libraries are freshly linked, ABI-checked and stripped. The prior current-main library/test links and 17 targeted GPU cases remain recorded in the tracker.
Measurement uses the accepted frozen paired-library basis, Release/GCC13 and unchanged compression flags; CUDA 12.9 covers SM70/75/80/86/90a/100f/120a/120 plus compute_120 PTX, while 13.3 excludes SM70. Of 171 owners, 170 use the frozen stock dependency/header context. One newer-main
bitwise_decode_opowner uses its exact signed current source/header/dependency context because that type does not exist in the older frozen dependency snapshot; this real owner is included in both measured head libraries, with its provenance and host-closure checks recorded. These are frozen-baseline measurements, not fresh current-main package sizes or a uniform stock-dependency build.Tracked in NVIDIA/cuvs#2888. Whole-swarm totals are being remeasured for the per-instantiation layout; older grouped-owner totals do not describe this revision.