Repository Analysis

NVIDIA/cutlass

CUDA Templates and Python DSLs for High-Performance Linear Algebra

9.2 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of NVIDIA/cutlass, a C++ project with 10,338 GitHub stars. SynthScan v2.0 examined 1,852,802 lines of code across 4836 source files, recording 9759 pattern matches distributed across 20 syntactic categories. The overall adjusted score of 9.2 places this repository in the Low AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

9.2
Adjusted Score
9.2
Raw Score
100%
Time Factor
2026-08-28
Last Push
10.3K
Stars
C++
Language
1.9M
Lines of Code
4.8K
Files
9.8K
Pattern Hits
2026-08-29
Scan Date
0.16
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 766MEDIUM 2241LOW 6752

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 9759 distinct pattern matches across 20 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Decorative Section Separators1989 hits · 6236 pts
SeverityFileLineSnippetContext
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py60# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py62# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py69# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py71# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py161# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py163# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py181# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py183# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py205# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py207# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py224# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py226# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py243# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py245# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py264# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py266# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py289# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py291# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py309# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py311# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py329# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py331# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py349# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py351# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py368# ---------------------------------------------------------------------------COMMENT
MEDIUM…t/examples/CuTeDSL/hopper/test_dense_gemm_fp8_2xacc.py371# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py65# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py67# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py194# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py196# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py215# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py217# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py241# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py243# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py293# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py295# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py332# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py334# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py365# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py367# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py392# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py394# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py410# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py412# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py434# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py436# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py457# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py459# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py531# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py533# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py567# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py569# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py592# ---------------------------------------------------------------------------COMMENT
MEDIUMtest/examples/CuTeDSL/hopper/test_grouped_gemm.py594# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py90# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py92# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py182# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py184# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py226# ---------------------------------------------------------------------------COMMENT
MEDIUM…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py228# ---------------------------------------------------------------------------COMMENT
1929 more matches not shown…
Cross-File Repetition718 hits · 3590 pts
SeverityFileLineSnippetContext
HIGHtest/python/cutlass/conv2d/conv2d_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_mixed_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f16_sm90.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f64_sm90.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f64_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f16_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_s8_sm90.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f32_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_s8_sm80.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGHtest/python/cutlass/gemm/gemm_f8_sm90.py0wrapper class to which tests will be added dynamically in __main__STRING
HIGH…kernels/rubin/gemm/dense_blockscaled_gemm_universal.py0this example provides an implementation of the sm107 batched dense blockscaled gemm kernel, please note that the apis anSTRING
HIGH…s/rubin/gemm/base/dense_blockscaled_gemm_persistent.py0this example provides an implementation of the sm107 batched dense blockscaled gemm kernel, please note that the apis anSTRING
HIGH…/blockscaled_gemm/dense_blockscaled_gemm_persistent.py0this example provides an implementation of the sm107 batched dense blockscaled gemm kernel, please note that the apis anSTRING
HIGH…mm/dense_blockscaled_gemm_persistent_mixed_clusters.py0this example provides an implementation of the sm107 batched dense blockscaled gemm kernel, please note that the apis anSTRING
HIGH…kernels/rubin/gemm/dense_blockscaled_gemm_universal.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…mm/base/blackwell_blockscaled_dense_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…s/rubin/gemm/base/dense_blockscaled_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…ions/sm100_dense_blockscaled_static_persistent_impl.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…mm/dense_blockscaled_gemm_persistent_mixed_clusters.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…/blockscaled_gemm/dense_blockscaled_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…led_gemm/dense_blockscaled_gemm_persistent_prefetch.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…/blockscaled_gemm/dense_blockscaled_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…kscaled_gemm/dense_blockscaled_gemm_persistent_amax.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…ors/cutlass/kernels/rubin/gemm/dense_gemm_universal.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…bin/kernel/grouped_gemm/grouped_gemm_mixed_clusters.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…tlass/kernels/rubin/gemm/base/dense_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…els/rubin/gemm/base/blackwell_dense_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…/cutedsl/gemm/implementations/sm100_persistent_impl.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…/cute/rubin/kernel/dense_gemm/dense_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…ell/kernel/dense_gemm/dense_gemm_persistent_dynamic.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…well/kernel/dense_gemm/dense_gemm_software_pipeline.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…e/blackwell/kernel/dense_gemm/dense_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…CuTeDSL/cute/blackwell/kernel/dense_gemm/dense_gemm.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…ll/kernel/dense_gemm/dense_gemm_persistent_prefetch.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…buted/distributed_gemm_all_reduce_ldxstmc_blackwell.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…l/distributed/distributed_all_gather_gemm_blackwell.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…stributed/distributed_gemm_reduce_scatter_blackwell.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…buted/distributed_gemm_all_reduce_lamport_blackwell.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…cute/blackwell/kernel/blockwise_gemm/blockwise_gemm.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…blackwell/kernel/blockwise_gemm/masked_grouped_gemm.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…kwell/kernel/blockwise_gemm/contiguous_grouped_gemm.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…CuTeDSL/cute_ext/blackwell/dense_gemm_cute_pipeline.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…on/CuTeDSL/cute/blackwell/efc/common_dense_gemm_efc.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…/kernel/dense_gemm/dense_gemm_alpha_beta_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…sl/gemm/implementations/sm90_static_persistent_impl.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…er/kernel/dense_gemm/dense_gemm_fp8_gelu_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…cute/hopper/kernel/dense_gemm/dense_gemm_persistent.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…on/CuTeDSL/cute/hopper/kernel/dense_gemm/dense_gemm.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…uTeDSL/cute/hopper/kernel/grouped_gemm/grouped_gemm.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…DSL/cute/rubin/kernel/blockwise_gemm/blockwise_gemm.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…rouped_gemm/grouped_blockscaled_gemm_mixed_clusters.py0set up configurations that are dependent on gemm inputs. this method configures various attributes based on the input teSTRING
HIGH…kernels/rubin/gemm/dense_blockscaled_gemm_universal.py0execute the gemm operation in steps: - setup static attributes before smem/grid/tma computation - setup tma load/store aSTRING
HIGH…mm/dense_blockscaled_gemm_persistent_mixed_clusters.py0execute the gemm operation in steps: - setup static attributes before smem/grid/tma computation - setup tma load/store aSTRING
HIGH…mm/base/blackwell_blockscaled_dense_gemm_persistent.py0execute the gemm operation in steps: - setup static attributes before smem/grid/tma computation - setup tma load/store aSTRING
HIGH…s/rubin/gemm/base/dense_blockscaled_gemm_persistent.py0execute the gemm operation in steps: - setup static attributes before smem/grid/tma computation - setup tma load/store aSTRING
HIGH…ions/sm100_dense_blockscaled_static_persistent_impl.py0execute the gemm operation in steps: - setup static attributes before smem/grid/tma computation - setup tma load/store aSTRING
HIGH…/blockscaled_gemm/dense_blockscaled_gemm_persistent.py0execute the gemm operation in steps: - setup static attributes before smem/grid/tma computation - setup tma load/store aSTRING
HIGH…led_gemm/dense_blockscaled_gemm_persistent_prefetch.py0execute the gemm operation in steps: - setup static attributes before smem/grid/tma computation - setup tma load/store aSTRING
658 more matches not shown…
Over-Commented Block2216 hits · 2154 pts
SeverityFileLineSnippetContext
LOWCMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWCMakeLists.txt421list(APPEND CUTLASS_CUDA_NVCC_FLAGS -DCUTLASS_SM100_FAMILY_ARCHS_ENABLED)COMMENT
LOWCMakeLists.txt881# DEPENDS: A list of targets or files on which this test is dependent.COMMENT
LOWtools/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtools/util/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtools/util/include/cutlass/util/print_error.hpp41#include <cute/tensor.hpp>COMMENT
LOWtools/util/include/cutlass/util/cublas_wrappers.hpp41# define BLAM_DEBUG_OUT(msg) std::cerr << "BLAM: " << msg << std::endlCOMMENT
LOW…l/include/cutlass/util/reference/host/rank_k_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…lude/cutlass/util/reference/host/gemm_planar_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…util/include/cutlass/util/reference/host/convolution.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…til/include/cutlass/util/reference/host/symm_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…til/include/cutlass/util/reference/host/gemm_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…/include/cutlass/util/reference/host/tensor_reduce.hpp41COMMENT
LOW…il/include/cutlass/util/reference/host/tensor_fill.hpp41COMMENT
LOW…include/cutlass/util/reference/host/tensor_compare.hpp41COMMENT
LOW…util/include/cutlass/util/reference/host/tensor_fill.h41#include <random>COMMENT
LOW…/include/cutlass/util/reference/host/rank_2k_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOWtools/util/include/cutlass/util/reference/device/gemm.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…il/include/cutlass/util/reference/device/convolution.h41#include "cutlass/matrix_shape.h"COMMENT
LOW…l/include/cutlass/util/reference/device/gemm_complex.h41#include "cutlass/numeric_conversion.h"COMMENT
LOW…il/include/cutlass/util/reference/device/tensor_fill.h41COMMENT
LOWtools/util/scripts/split_test_cmake.py1#################################################################################################COMMENT
LOWtools/util/scripts/split_test_cmake.py21# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THECOMMENT
LOWtools/library/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtools/library/include/cutlass/library/library.h41COMMENT
LOWtools/library/include/cutlass/library/library.h61#include "cutlass/tensor_coord.h"COMMENT
LOWtools/library/src/conv_operation_3x.hpp501 // Convolutions split the metadata (in Conv2dConfiguration) fromCOMMENT
LOWtools/library/src/conv_operation_3x.hpp741 else {COMMENT
LOWtools/library/src/conv_operation_3x.hpp841 if (num_groups != 1) {COMMENT
LOWtools/library/src/conv2d_operation.h41#include "cutlass/conv/kernel/default_conv2d_dgrad.h"COMMENT
LOWtools/library/src/sparse_gemm_operation_3x.hpp41#include "cutlass/library/library.h"COMMENT
LOWtools/library/src/gemm_operation_3x.hpp41#include "cutlass/library/library.h"COMMENT
LOW…ary/src/reference/blockwise_gemm_reference_operation.h41#include <cstring>COMMENT
LOWtools/profiler/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtools/profiler/include/cutlass/profiler/debug.h41COMMENT
LOW…r/include/cutlass/profiler/conv2d_operation_profiler.h41#include <algorithm>COMMENT
LOWtools/profiler/include/cutlass/profiler/options.h221COMMENT
LOW…lude/cutlass/profiler/sparse_gemm_operation_profiler.h41#include <algorithm>COMMENT
LOW…ler/include/cutlass/profiler/symm_operation_profiler.h41#include <memory>COMMENT
LOW…e/cutlass/profiler/blockwise_gemm_operation_profiler.h41#include <memory>COMMENT
LOW…ler/include/cutlass/profiler/trmm_operation_profiler.h41#include <memory>COMMENT
LOW…nclude/cutlass/profiler/reduction_operation_profiler.h41#include <algorithm>COMMENT
LOW…/include/cutlass/profiler/rank_2k_operation_profiler.h41#include <memory>COMMENT
LOW…utlass/profiler/block_scaled_gemm_operation_profiler.h41#include <string>COMMENT
LOW…profiler/include/cutlass/profiler/operation_profiler.h41COMMENT
LOW…ler/include/cutlass/profiler/gemm_operation_profiler.h41#include <algorithm>COMMENT
LOW…r/include/cutlass/profiler/conv3d_operation_profiler.h41#include <algorithm>COMMENT
LOW…r/include/cutlass/profiler/rank_k_operation_profiler.h41#include <memory>COMMENT
LOW…ude/cutlass/profiler/grouped_gemm_operation_profiler.h41#include <unordered_map>COMMENT
LOWtools/profiler/src/performance_report.cpp41#include "cutlass/library/util.h"COMMENT
LOWtools/profiler/src/cudnn_helpers.cpp241 if(a_tensor.element != b_tensor.element) {COMMENT
LOWtools/profiler/src/cudnn_helpers.cpp381 // where; div_up(a, b) : (a - 1)/b + 1 //COMMENT
LOWtest/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtest/self_contained_includes/CMakeLists.txt1# Copyright (c) 2024 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtest/self_contained_includes/CMakeLists.txt21# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLECOMMENT
LOWtest/self_contained_includes/CMakeLists.txt221 # cutlass/archCOMMENT
LOWtest/unit/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtest/unit/pipeline/CMakeLists.txt1# Copyright (c) 2017 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.COMMENT
LOWtest/unit/pipeline/testbed_cluster_launch_control.h41 #define CUTLASS_UNIT_TEST_PIPELINE trueCOMMENT
LOWtest/unit/pipeline/testbed.h41#include "cutlass/util/command_line.h"COMMENT
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Hyper-Verbose Identifiers1693 hits · 1594 pts
SeverityFileLineSnippetContext
LOWtest/python/pycute/test_right_inverse.py46 def helper_test_right_inverse(self, layout):CODE
LOWtest/python/CuTeDSL/test_export_c_header_shape_type.py115 def test_static_shape_has_no_shape_slots(self):CODE
LOWtest/python/CuTeDSL/test_export_c_header_shape_type.py120 def test_dlpack_tensor_shape_slots(self):CODE
LOWtest/python/CuTeDSL/test_export_c_header_shape_type.py126 def test_mixed_width_shape_dims_rejected(self):CODE
LOWtest/python/CuTeDSL/test_export_c_header_shape_type.py138 def test_tensor_list_shape_slots(self):CODE
LOWtest/python/CuTeDSL/test_export_c_header_shape_type.py152 def test_tensor_list_mismatched_widths_rejected(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py125 def test_in_range_values_are_preserved(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py135 def test_out_of_range_values_still_wrap(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py145 def test_floats_truncate_toward_zero(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py152 def test_bools_fold_to_zero_and_one(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py159 def test_boolean_folds_nonzero_to_one(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py168 def test_nan_and_infinity_are_rejected(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py182 def test_boolean_folds_nan_and_infinity_to_true(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py188 def test_widths_without_a_numpy_dtype_are_rejected(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py202 def test_exact_range_tracks_the_numpy_dtype(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py211 def test_range_follows_the_dtype_not_the_width(self):CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py241 def test_from_other_integer_type(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py48 def test_get_tensor_inside_dynamic_if(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py70 def test_struct_use_outside_if_still_works(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py91 def test_nested_struct_inside_dynamic_if(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py137 def test_if_elif_else_warp_spec_pattern(self):CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py166 def test_struct_captured_in_while_body(self):CODE
LOWtest/python/cutlass/installation.py45 def test_cutlass_source_paths(self):CODE
LOWtest/python/cutlass/interface/evt_interface.py92 def test_too_much_shared_memory(self):CODE
LOWtest/python/cutlass/interface/evt_interface.py96 def evt_too_much_shared_memory(accum, C1, C2, C3, C4, C5, C6, C7, C8):CODE
LOWtest/python/cutlass/interface/evt_interface.py175 def test_missing_example_tensor(self):CODE
LOWtest/python/cutlass/interface/evt_interface.py179 def evt_missing_example_tensor(accum, C):CODE
LOWtest/python/cutlass/interface/gemm_interface.py237 def test_tensorop_availability(self):CODE
LOWtest/python/cutlass/interface/gemm_interface.py272 def test_invalid_tile_description(self):CODE
LOWtest/python/cutlass/interface/conv2d_interface.py268 def test_invalid_tile_description(self):CODE
LOWtest/python/cutlass/evt/evt_mixed_sm80_90.py53 def test_same_variable_used_multiple_times(self):CODE
LOWtest/python/cutlass/evt/evt_mixed_sm80_90.py193 def test_mixed_dag_partition_k(self):CODE
LOWtest/utils/test_sharding.py245def pytest_collection_modifyitems(config, items):CODE
LOWtest/utils/test_sharding.py465def pytest_runtest_makereport(item, call):CODE
LOWtest/utils/test_sharding.py498def pytest_report_collectionfinish(config, start_path, items):CODE
LOWtest/examples/CuTeDSL/test_for_control_flow.py41def _for_loop_carried_reused_target_kernel(out: cute.Tensor, n: cutlass.Int32):CODE
LOWtest/examples/CuTeDSL/test_for_control_flow.py53def _for_loop_carried_reused_target_host(out: cute.Tensor, n: cutlass.Int32):CODE
LOWtest/examples/CuTeDSL/test_for_control_flow.py60def test_for_loop_carried_var_with_reused_loop_target():CODE
LOWtest/examples/CuTeDSL/test_dataclasses.py50def _test_empty_dataclass_kernel(out: cute.Tensor, tag: A | B):CODE
LOWtest/examples/CuTeDSL/test_dataclasses.py61def _test_empty_dataclass_host(out: cute.Tensor, tag: A | B):CODE
LOWtest/examples/CuTeDSL/test_dataclasses.py66def test_empty_dataclass_union(tag, expected):CODE
LOWtest/examples/CuTeDSL/test_tvm_ffi_env_stream.py53def test_env_stream_detected_from_nested_tuple():CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py129def test_grouped_blockscaled_gemm(CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py166def test_grouped_blockscaled_gemm_large_persistent_repro():CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py199def test_invalid_dtypes_and_sf_vec_size(CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py283def test_invalid_mma_tiler_and_cluster_shape(CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py319def test_invalid_tensor_alignment(problem_sizes_mnkl: List[Tuple[int, int, int, int]]):CODE
LOW…amples/CuTeDSL/sm_103/test_grouped_blockscaled_gemm.py364def test_batch_dimension_not_one():CODE
LOWtest/examples/CuTeDSL/sm_100a/test_rmsnorm.py89 def test_rmsnorm_without_weight(self, N):CODE
LOWtest/examples/CuTeDSL/sm_100a/test_rmsnorm.py110 def test_cluster_path_correctness(self, N):CODE
LOW…CuTeDSL/sm_100a/test_dense_gemm_persistent_prefetch.py222def test_prefetch_dist_configurations(prefetch_dist: Optional[int]):CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py169def test_dense_blockscaled_gemm_prefetch(CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py290def test_prefetch_dist_configurations(prefetch_dist: Optional[int]):CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py352def test_invalid_dtypes_and_scale_factor_vec_size(CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py427def test_invalid_mma_tiler_and_cluster_shape(CODE
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py481def test_invalid_tensor_alignment(CODE
LOWoperators/test/conftest.py69def save_restore_global_options():CODE
LOWoperators/test/unit/test_reference_check.py129 def test_multiple_tensors_different_dtypes(self):CODE
LOWoperators/test/unit/test_reference_check.py163 def test_rtols_atols_expansion(self):CODE
LOWoperators/test/unit/test_reference_check.py178 def test_mismatched_dtype_raises(self):CODE
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Unused Imports1515 hits · 1238 pts
SeverityFileLineSnippetContext
LOWtest/python/pycute/test_coalesce.py40CODE
LOWtest/python/pycute/test_left_inverse.py40CODE
LOWtest/python/pycute/test_complement.py40CODE
LOWtest/python/pycute/test_int_tuple.py39CODE
LOWtest/python/pycute/test_typing.py39CODE
LOWtest/python/pycute/test_composition.py40CODE
LOWtest/python/pycute/test_right_inverse.py40CODE
LOWtest/python/CuTeDSL/test_export_c_header_shape_type.py30CODE
LOWtest/python/CuTeDSL/test_struct_in_if.py24CODE
LOWtest/python/cutlass/interface/gemm_interface.py37CODE
LOWtest/python/cutlass/interface/conv2d_interface.py37CODE
LOWtest/python/cutlass/evt/evt_layout_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_layout_sm80_90.py42CODE
LOWtest/python/cutlass/evt/evt_mixed_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_mixed_sm80_90.py42CODE
LOWtest/python/cutlass/evt/evt_compute_sm80_90.py40CODE
LOWtest/python/cutlass/evt/evt_compute_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_compute_sm80_90.py42CODE
LOWtest/python/cutlass/evt/evt_load_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_load_sm80_90.py42CODE
LOWtest/python/cutlass/evt/evt_store_sm80_90.py41CODE
LOWtest/python/cutlass/evt/evt_store_sm80_90.py42CODE
LOWtest/python/cutlass/conv2d/conv2d_sm80.py43CODE
LOWtest/python/cutlass/conv2d/conv2d_problem_sizes.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py41CODE
LOWtest/python/cutlass/conv2d/conv2d_test_utils.py55CODE
LOWtest/python/cutlass/gemm/gemm_batched.py37CODE
LOWtest/python/cutlass/gemm/gemm_batched.py43CODE
LOWtest/python/cutlass/gemm/gemm_batched.py46CODE
LOWtest/python/cutlass/gemm/utils.py36CODE
LOWtest/python/cutlass/gemm/utils.py45CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py34CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py35CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py36CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py40CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py51CODE
LOWtest/examples/CuTeDSL/conftest.py53CODE
LOWtest/examples/CuTeDSL/test_dataclasses.py34CODE
LOWtest/examples/CuTeDSL/test_math.py29CODE
LOWtest/examples/CuTeDSL/test_math.py32CODE
LOWoperators/test/conftest.py32CODE
LOWoperators/test/unit/test_manifest.py33CODE
LOWoperators/test/test_utils/__init__.py29CODE
LOWoperators/test/test_utils/__init__.py29CODE
LOWoperators/test/test_utils/__init__.py30CODE
LOWoperators/test/test_utils/__init__.py30CODE
LOWoperators/test/test_utils/__init__.py30CODE
LOWoperators/test/test_utils/__init__.py31CODE
LOWoperators/test/test_utils/common.py29CODE
LOWoperators/test/test_utils/reference_check.py29CODE
LOW…kernels/rubin/gemm/dense_blockscaled_gemm_universal.py31CODE
LOW…ors/cutlass/kernels/rubin/gemm/dense_gemm_universal.py29CODE
LOW…s/rubin/gemm/base/dense_blockscaled_gemm_persistent.py31CODE
LOWoperators/cutlass/operators/artifact.py29CODE
LOWoperators/cutlass/operators/manifest.py29CODE
LOWoperators/cutlass/operators/arch.py29CODE
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Deep Nesting541 hits · 430 pts
SeverityFileLineSnippetContext
LOWtest/python/CuTeDSL/test_numeric_construction.py104CODE
LOWtest/python/CuTeDSL/test_numeric_construction.py188CODE
LOWtest/python/cutlass/interface/gemm_interface.py272CODE
LOWtest/python/cutlass/evt/utils/evt_testbed.py140CODE
LOWtest/python/cutlass/gemm/gemm_testbed.py319CODE
LOWtest/utils/test_sharding.py245CODE
LOWtest/utils/test_sharding.py465CODE
LOWtest/examples/CuTeDSL/conftest.py126CODE
LOWoperators/test/test_utils/reference_check.py334CODE
LOW…mm/base/blackwell_blockscaled_dense_gemm_persistent.py717CODE
LOW…tlass/kernels/rubin/gemm/base/dense_gemm_persistent.py358CODE
LOW…els/rubin/gemm/base/blackwell_dense_gemm_persistent.py552CODE
LOW…s/rubin/gemm/base/dense_blockscaled_gemm_persistent.py1119CODE
LOWoperators/cutlass/operators/mma.py105CODE
LOWoperators/cutlass/operators/fusion/library.py343CODE
LOWoperators/cutlass/operators/fusion/library.py360CODE
LOWoperators/cutlass/operators/fusion/pycute/layout.py135CODE
LOWoperators/cutlass/operators/fusion/pycute/layout.py196CODE
LOWoperators/cutlass/operators/fusion/ir/store_nodes.py129CODE
LOWoperators/cutlass/operators/fusion/ir/c_types.py115CODE
LOW…rators/cutlass/operators/fusion/ir/layout_algorithm.py87CODE
LOW…rators/cutlass/operators/fusion/ir/layout_algorithm.py146CODE
LOWoperators/cutlass/operators/fusion/ir/layout_nodes.py259CODE
LOWoperators/cutlass/operators/fusion/ir/tensor.py58CODE
LOWoperators/cutlass/operators/fusion/ir/node.py213CODE
LOW…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py55CODE
LOW…rators/cutlass/operators/fusion/passes/pass_manager.py159CODE
LOW…rators/cutlass/operators/fusion/passes/graph_drawer.py76CODE
LOW…s/cutlass/operators/providers/cutedsl/evt/converter.py297CODE
LOW…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py544CODE
LOW…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py1734CODE
LOW…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py552CODE
LOW…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py599CODE
LOW…ers/cutedsl/gemm/sm100_persistent_preferred_cluster.py238CODE
LOW…ers/cutedsl/gemm/sm100_persistent_preferred_cluster.py374CODE
LOW…ers/cutedsl/gemm/sm100_persistent_preferred_cluster.py544CODE
LOW…/providers/cutedsl/gemm/sm100_static_persistent_efc.py303CODE
LOW…ators/providers/cutedsl/gemm/sm90_static_persistent.py151CODE
LOW…ators/providers/cutedsl/gemm/sm90_static_persistent.py264CODE
LOW…s/operators/providers/cutedsl/gemm/sm100_persistent.py169CODE
LOW…s/operators/providers/cutedsl/gemm/sm100_persistent.py299CODE
LOW…operators/providers/cutedsl/gemm/sm80_tensorop_gemm.py201CODE
LOW…/operators/providers/cutedsl/gemm/sm100_mixed_input.py691CODE
LOW…rs/cutedsl/gemm/implementations/sm100_tgv_gemm_impl.py276CODE
LOW…utedsl/gemm/implementations/sm80_tensorop_gemm_impl.py254CODE
LOW…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py655CODE
LOW…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py1828CODE
LOW…ions/sm100_dense_blockscaled_static_persistent_impl.py720CODE
LOW…sl/gemm/implementations/sm90_static_persistent_impl.py357CODE
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py1053CODE
LOW…ementations/sm100_persistent_preferred_cluster_impl.py437CODE
LOW…/cutedsl/gemm/implementations/sm100_persistent_impl.py557CODE
LOWoperators/cutlass/operators/utils/tensor.py347CODE
LOWoperators/cutlass/operators/utils/tensor.py528CODE
LOWoperators/cutlass/operators/arguments/base.py99CODE
LOWpython/cutlass_cppgen/library_defaults.py109CODE
LOWpython/cutlass_cppgen/library_defaults.py236CODE
LOWpython/cutlass_cppgen/op/conv.py479CODE
LOWpython/cutlass_cppgen/op/conv.py506CODE
LOWpython/cutlass_cppgen/utils/datatypes.py84CODE
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Self-Referential Comments169 hits · 390 pts
SeverityFileLineSnippetContext
MEDIUMtest/python/cutlass/evt/utils/evt_testbed.py108 # Create the Gemm planCOMMENT
MEDIUMtest/python/cutlass/conv2d/conv2d_test_utils.py347 # Create the planCOMMENT
MEDIUMoperators/test/integration/test_cuda_graph.py91 # Create a CUDA Graph to run our compiled Operator N timesCOMMENT
MEDIUM…ors/cutlass/kernels/rubin/gemm/dense_gemm_universal.py466 # Create a temporary kernel object to check base implementationCOMMENT
MEDIUM…mm/base/blackwell_blockscaled_dense_gemm_persistent.py125 """This class implements batched matrix multiplication (C = A x SFA x B x SFB) with support for various data typesSTRING
MEDIUM…els/rubin/gemm/base/blackwell_dense_gemm_persistent.py191 """This class implements batched matrix multiplication (C = A x B) with support for various data typesSTRING
MEDIUMoperators/cutlass/operators/fusion/__init__.py69 # Define the example tensorsSTRING
MEDIUM…rators/cutlass/operators/fusion/frontend/python_ast.py153 # Create the assign nodeCOMMENT
MEDIUMoperators/cutlass/operators/fusion/ir/c_types.py159 # Create the ctype tupleCOMMENT
MEDIUM…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py136 # Create the subgraphCOMMENT
MEDIUM…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py149 # Create the fused nodeCOMMENT
MEDIUM…utlass/operators/providers/cutedsl/evt/efc/_helpers.py164 # Create a new signature with the custom parameter namesCOMMENT
MEDIUM…utlass/operators/providers/cutedsl/evt/efc/_helpers.py167 # Create a wrapper function that accepts arguments according to the new signatureCOMMENT
MEDIUM…ors/providers/cutedsl/evt/efc/dense_gemm/_operation.py122 # The following functions are executed by the specialized warps forCOMMENT
MEDIUM…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py1136 # The following functions are executed by the specialized warp for theCOMMENT
MEDIUM…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py1950 # Create the local_tile gX_mnl for all the EFC supplemental tensors.COMMENT
MEDIUM…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py2455 # Create the tiled tensors to be loaded in the epilogue.COMMENT
MEDIUM…s/operators/providers/cutedsl/gemm/sm100_persistent.py80 """This class implements batched matrix multiplication (C = A @ B) with support for various data typesSTRING
MEDIUM…operators/providers/cutedsl/gemm/sm80_tensorop_gemm.py68 """This class implements batched matrix multiplication (C = A @ B)STRING
MEDIUM…rs/cutedsl/gemm/implementations/sm100_tgv_gemm_impl.py1023 # Create the local tile of coordC, same tiling as gCCOMMENT
MEDIUM…utedsl/gemm/implementations/sm80_tensorop_gemm_impl.py161 # Create a copy atom for a global to shared memory asynchronous copyCOMMENT
MEDIUM…utedsl/gemm/implementations/sm80_tensorop_gemm_impl.py519 # Create the copy atoms for the copy from shared memory to registerCOMMENT
MEDIUM…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py223 """This class implements batched matrix multiplication (C = A * B) with support for fp8 (e4m3fn, e5m2)STRING
MEDIUM…ions/sm100_dense_blockscaled_static_persistent_impl.py120 """This class implements batched matrix multiplication (C = A x SFA x B x SFB) with support for various data typesSTRING
MEDIUMpython/cutlass_cppgen/backend/c_types.py538 # Create the ctype tupleCOMMENT
MEDIUMpython/cutlass_cppgen/backend/compiler.py143 # Create the table if it does not already existSTRING
MEDIUMpython/cutlass_cppgen/backend/library.py52# The following block implements enum.auto() for Python 3.5 variants that don't include it suchCOMMENT
MEDIUM…thon/cutlass_cppgen/backend/evt/frontend/python_ast.py146 # Create the assign nodeCOMMENT
MEDIUM…n/cutlass_cppgen/backend/evt/passes/pass_dag_2_tree.py134 # Create the subgraphCOMMENT
MEDIUM…n/cutlass_cppgen/backend/evt/passes/pass_dag_2_tree.py146 # Create the fused nodeCOMMENT
MEDIUMpython/cutlass_cppgen/epilogue/epilogue.py134 # Define the example tensorsSTRING
MEDIUM…L/cutlass/experimental/task_scheduling/task_manager.py1042 # Create a unique list of resources from all tasks and their src and dstCOMMENT
MEDIUMpython/CuTeDSL/cutlass/cute/core.py6005 # Create a dictionary to store the offsetsCOMMENT
MEDIUMpython/CuTeDSL/cutlass/cute/core.py6219 # Create a dictionary to store the offsets (all zeros for union)COMMENT
MEDIUMpython/CuTeDSL/cutlass/cute/core.py752 # Create a scaled basis with integer scale and modeSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py755 # Create a scaled basis with a Ratio scaleSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py758 # Create a scaled basis with a list of modesSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py954 # Create a basis element for the first dimension (mode 0)STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py957 # Create a basis element for the second dimension (mode 1)STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py960 # Create a basis element for a hierarchical dimensionSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3716 # Create a 2D compact left-most layout with shape (4,4)STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3719 # Create a left-most layout with custom stridesSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3722 # Create a layout for a 3D tensorSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3725 # Create a layout with custom stridesSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3851 # Create a row-major layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3854 # Create a column-major layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3857 # Create a layout with custom dimension ordering for a 3D tensorSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py1157 # Creating a layout with shape (4,8) and default stride (layout left / "column major")STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py1160 # Creating a layout with explicit shape and strideSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py2881 tensor = make_tensor(...) # Create a 2D tensorSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3807 # Create a 2D identity layout with shape (4,4)STRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3810 # Create a 3D identity layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py3999 # Create a basic layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4003 # Create a composed layout with an offsetSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4350 # Create a layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4607 # Create a layout that maps (i,j) to i*4 + jSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4609 # Create a layout that maps (i,j) to i*3 + jSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4661 # Create a right-major layout for a 4x4 matrixSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py4663 # Create a left-major layout that complements the row layoutSTRING
MEDIUMpython/CuTeDSL/cutlass/cute/core.py6170 # Define a union with scalar int/float elements:STRING
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Redundant / Tautological Comments138 hits · 200 pts
SeverityFileLineSnippetContext
LOWtest/utils/test_sharding.py429 # Assign markers to each subtestCOMMENT
LOW…00a/test_dense_blockscaled_gemm_persistent_prefetch.py310 # Check if this configuration can be implementedCOMMENT
LOW…kernels/rubin/gemm/dense_blockscaled_gemm_universal.py426 # Check if prefetch is enabled (prefetch_dist > 0)COMMENT
LOW…kernels/rubin/gemm/dense_blockscaled_gemm_universal.py1263 # Check if configuration can be implementedCOMMENT
LOW…ors/cutlass/kernels/rubin/gemm/dense_gemm_universal.py823 # Check if configuration can be implementedCOMMENT
LOW…ors/cutlass/kernels/rubin/gemm/dense_gemm_universal.py965 # Check if configuration can be implementedCOMMENT
LOW…mm/base/blackwell_blockscaled_dense_gemm_persistent.py2790 # Check if configuration can be implementedCOMMENT
LOW…mm/base/blackwell_blockscaled_dense_gemm_persistent.py3023 # Check if configuration can be implementedCOMMENT
LOW…tlass/kernels/rubin/gemm/base/dense_gemm_persistent.py733 # Check if we should use Bkeep-Breuse patternCOMMENT
LOW…tlass/kernels/rubin/gemm/base/dense_gemm_persistent.py1320 # Check if configuration can be implementedCOMMENT
LOW…tlass/kernels/rubin/gemm/base/dense_gemm_persistent.py1445 # Check if configuration can be implementedCOMMENT
LOW…els/rubin/gemm/base/blackwell_dense_gemm_persistent.py458 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…els/rubin/gemm/base/blackwell_dense_gemm_persistent.py1532 # Check if configuration can be implementedCOMMENT
LOW…els/rubin/gemm/base/blackwell_dense_gemm_persistent.py1639 # Check if configuration can be implementedCOMMENT
LOW…s/rubin/gemm/base/dense_blockscaled_gemm_persistent.py553 # Check if prefetch is enabled (prefetch_dist > 0)COMMENT
LOW…s/rubin/gemm/base/dense_blockscaled_gemm_persistent.py2064 # Check if the current combination is validCOMMENT
LOW…s/rubin/gemm/base/dense_blockscaled_gemm_persistent.py2603 # Check if configuration can be implementedCOMMENT
LOW…oviders/cutedsl/evt/efc/dense_gemm/sm100/_operation.py1646 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…ations/sm100_contiguous_offset_2d3d_dense_gemm_impl.py503 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…ementations/sm100_persistent_preferred_cluster_impl.py256 # Check if input data types are compatible with MMA instructionCOMMENT
LOW…/cutedsl/gemm/implementations/sm100_persistent_impl.py443 # Check if input data types are compatible with MMA instructionCOMMENT
LOWpython/cutlass_cppgen/op/conv.py473 # Check if the iterator algorithm is validCOMMENT
LOWpython/CuTeDSL/setup.sh81 # Check if CUTLASS_IR_BUILD_DIR is setCOMMENT
LOWpython/CuTeDSL/setup.sh120 # Check if requirements file existsCOMMENT
LOWpython/CuTeDSL/prep_editable_install.py118 # Check if version already has .dev<n> patternCOMMENT
LOWpython/CuTeDSL/_mlir_helpers/vector.py326 # Check if all indices are static (Python ints)COMMENT
LOWpython/CuTeDSL/_mlir_helpers/op.py478 # Check if it's a decorator config error firstCOMMENT
LOWpython/CuTeDSL/cutlass/block.py68 # Check if required arguments are providedCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py172 # Check if test was explicitly selected like ::test_name[param1-param2-...]COMMENT
LOWpython/CuTeDSL/cutlass/pipeline/sm100.py714 # Set mask to None if not using clusters (i.e. 1CTA kernels)COMMENT
LOWpython/CuTeDSL/cutlass/pipeline/sm100.py722 # Set mask to None if not using 2CTA instructionsCOMMENT
LOW…L/cutlass/experimental/task_scheduling/task_manager.py4798 # Check if any of those also have ProducerWork in LOOP.COMMENT
LOWpython/CuTeDSL/cutlass/cute/tuple.py475 # Check if first argument is a tuple to determine behaviorCOMMENT
LOWpython/CuTeDSL/cutlass/cute/arch/nvvm_wrappers.py215 # Check if user passed an enum (should be a string literal instead)COMMENT
LOWpython/CuTeDSL/cutlass/cute/arch/nvvm_wrappers.py3596 # Check if it's a floating-point vector typeCOMMENT
LOWpython/CuTeDSL/cutlass/utils/mixed_input_helpers.py753 # Check if scale tensor matches the TMA load 128B alignment requirementCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py2398 # Check if all non-default arguments are providedCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/env_manager.py435 # Check if the environment variable is already set, if so, return it immediately.COMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py1884 # Check if argument is Numeric, if so, call ir_value()COMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py1983 # Check if all keywords are known DSL kwargsCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/ast_preprocessor.py1988 # Check if 'preprocess' is explicitly setCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/common.py151 # Check if show_stacktrace is enabled via registered env managerCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/common.py159 # Check if it's a DSL operation error (by name to avoid circular import issues)COMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/common.py811 # Check if cause is also a DSLOperationErrorCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/array.py678 # Check if printf is already declaredCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/array.py2456 # Check if last element is a sliceCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/array.py2933 # Check if it needs type coercion for vector storeCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/runtime/cuda.py315 # Check if we successfully got the compute capabilityCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/runtime/cuda.py444 # Check if a valid CUDA context already exists (e.g., created by PyTorch orCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py31 # Check if we are at the root directoryCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/leaf_utils.py319 # Check if this is an assignable leafCOMMENT
LOW…TeDSL/cutlass/base_dsl/tvm_ffi_builder/mlir_builder.py228 # Check if align_const is a power of twoCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1324 # Check if type is int or bool (both use v_int64, bool can be converted to int)COMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1363 # Check if type is float, int, or bool (int and bool can be converted to float)COMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1464 # Check if type is opaque pointerCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1468 # Check if type is a nullptrCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1842 # Check if type is int or bool (both use v_int64, bool can be converted to int)COMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1920 # Check if type is ffi.Shape or ffi.ArrayCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py2089 # Check if data pointer is divisible by alignmentCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py2330 # Check if type is kTVMFFIArrayCOMMENT
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Docstring Block Structure39 hits · 195 pts
SeverityFileLineSnippetContext
HIGHoperators/test/test_utils/allocation.py159 Creates a RandomIntInitializationMode from the given datatypes. Range is determined based on the bitwiSTRING
HIGHoperators/test/test_utils/reference_check.py345 Asserts that the result tensor is similar to the reference tensor. This function automatically handles: - CSTRING
HIGHoperators/cutlass/operators/__init__.py87Return Operators that match the given arguments, metadata filter, and target. Args: args (RuntimeArguments STRING
HIGHoperators/cutlass/operators/heuristics/base.py115Return the registered :class:`Heuristic` subclass for ``name``. Args: name (str): The name the heuristic waSTRING
HIGH…ors/cutlass/operators/heuristics/nvmatmul/_provider.py58Return the compute capability nvMMH's ``gpu`` device name represents. Only SM100 devices are mapped -- nvmatmul doeSTRING
HIGH…rators/cutlass/operators/heuristics/nvmatmul/ranker.py175Order ``operators`` best-first for ``args`` using nvMatmulHeuristics. See :meth:`cutlass.operators.heuristics.bSTRING
HIGH…tors/cutlass/operators/heuristics/nvmatmul/_mapping.py93Build a query from dense-GEMM :class:`~cutlass.operators.GemmArguments`. Only plain :class:`~cutlass.operators.STRING
HIGH…tors/cutlass/operators/heuristics/nvmatmul/_mapping.py160Map a CUTLASS ``Numeric`` type to an nvMMH / cuBLAS-style precision letter. Args: numeric (type[Numeric]): STRING
HIGH…tors/cutlass/operators/heuristics/nvmatmul/_mapping.py219Map an operand's major stride to nvMMH ``'t'`` / ``'n'``. A tensor whose last dimension is contiguous is row-major STRING
HIGH…tors/cutlass/operators/heuristics/nvmatmul/_mapping.py300Reorder and prune ``operators`` best-first according to heuristic ``configs``. nvMMH provides configs describing reSTRING
HIGHoperators/cutlass/operators/providers/provider.py124Register an Operator class with this provider. Intended to be used as a class decorator: .. code-blockSTRING
HIGHoperators/cutlass/operators/utils/device.py61Check whether ``result`` contains a CUDA error and raise it, otherwise return the rest. Args: result (list)STRING
HIGHoperators/cutlass/operators/utils/device.py114Return the target SM from environment variable ``env_var`` or device ``device``. The environment variable takes preSTRING
HIGHoperators/cutlass/operators/utils/device.py191Convert the provided stream to a ``cuda.bindings.driver.CUstream``. Args: stream (cuda.bindings.driver.CUstSTRING
HIGHoperators/cutlass/operators/utils/dtype.py94Convert a torch dtype to a cutlass dtype. Args: dtype (torch.dtype): The torch dtype to convert. ReturSTRING
HIGHoperators/cutlass/operators/utils/dtype.py169Return the number of logical elements per PyTorch storage element. The factor is the storage dtype's bit width diviSTRING
HIGHoperators/cutlass/operators/utils/dtype.py207Convert a dtype to a cutlass dtype. Args: dtype (torch.dtype | jnp.dtype | np.dtype): The dtype to convert STRING
HIGHoperators/cutlass/operators/utils/tensor.py96Return ``tensor`` with each contiguous 8-element K group pre-shuffled. This prepares an Int4 A payload for the mixeSTRING
HIGHoperators/cutlass/operators/metadata/base.py117Check if the provided ``args``/``target_sm`` satisfy the properties described by this OperatorMetadata. Args: STRING
HIGHoperators/cutlass/operators/arguments/operand.py179Return the number of elements expected in :attr:`scale` for an operand of ``quantized_shape``. ``quantized_shapSTRING
HIGHoperators/cutlass/operators/arguments/operand.py374If operand is already a ``Operand``, return it. Otherwise, wrap it in a ``DenseTensor``. This is used for convenienSTRING
HIGHpython/CuTeDSL/prep_editable_install.py45 Download the nvidia-cutlass-dsl wheel to a temporary directory. Args: temp_dir: Temporary directory paSTRING
HIGHpython/CuTeDSL/prep_editable_install.py96 Extract version from wheel filename and convert to dev version. Args: wheel_path: Path to the wheel fiSTRING
HIGH…n/CuTeDSL/cutlass/experimental/task_scheduling/task.py306 Normalize and validate schedule_list. - Normalizes 2-element tuples to 3-element with ScheduleStageType.Loop dSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/ast_helpers.py473 Executes comparison operations with a left operand and a list of comparators. Args: left: The leftmostSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/ast_helpers.py818 Decomposes a joined f-string component list into a format string and dynamic arguments. This function takes a STRING
HIGHpython/CuTeDSL/cutlass/base_dsl/array.py804Get the printf format specifier for a given MLIR type. Args: mlir_type: The MLIR type of the value RetSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/array.py3511Load value(s) from the array. Args: idx: Index can be: - int or Int32: Single elemeSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/utils/tree_utils.py639 Flatten a nested structure into a flat list of values and a tree definition. This function recursively traversSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/utils/tree_utils.py735 Internal function to flatten a tree structure. This is the core implementation of tree flattening that handlesSTRING
HIGHpython/CuTeDSL/cutlass/cutlass_dsl/cutlass.py2620 Filter items based on whether corresponding iter_args are frozen dataclasses. This function filters items (whiSTRING
HIGH…CuTeDSL/cute_ext/blackwell/attention/gqa_decode_opt.py1960Run and benchmark the optimized GQA flash-decode kernel on Blackwell. Args: batches/seqlen/heads_q/heads_k/STRING
HIGH…eDSL/cute_ext/blackwell/attention/gqa_decode_simple.py1272Run and benchmark the simple GQA flash-decode kernel on Blackwell. Args: batches/seqlen/heads_q/heads_k/heaSTRING
HIGH…/cute_ext/blackwell/dense_gemm/input_transform_gemm.py1236Run and benchmark the input-transform GEMM D = transform(A, B)[0] @ B. The benchmark uses the identity transform soSTRING
HIGH…thon/CuTeDSL/cute_ext/blackwell/dense_gemm/glu_gemm.py440Run and benchmark the GLU GEMM D = (A @ B0) * gate(A @ B1) on Blackwell. Args: mnkl: Problem size (M, N, K,STRING
HIGH…L/cute_ext/blackwell/dense_gemm/planar_complex_gemm.py496Run and benchmark the planar complex GEMM on Blackwell. Computes D_real = A_real @ B_real - A_imag @ B_imag and STRING
HIGH…eDSL/cute_ext/blackwell/dense_gemm/mixed_input_gemm.py669Run and benchmark the mixed-input GEMM D = ((A - Zeros) * Scale) @ B. Args: mnkl: Problem size (M, N, K, L)STRING
HIGH…/blackwell/dense_gemm/sm103_dense_block_scaled_gemm.py804Run and benchmark the SM103 block-scaled dense GEMM D = (A*SFA) @ (B*SFB). Args: mnkl: Problem size (M, N, STRING
HIGH…thon/CuTeDSL/cute_ext/blackwell/dense_gemm/b2b_gemm.py577Run and benchmark the back-to-back GEMM D = (A @ B0) @ B1 on Blackwell. Args: mnkl: (M, N, K, L); K is the STRING
Excessive Try-Catch Wrapping192 hits · 176 pts
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LOW…ors/cutlass/operators/heuristics/nvmatmul/_provider.py122 except Exception:CODE
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LOWoperators/cutlass/operators/utils/device.py165 except Exception as e:CODE
LOWoperators/cutlass/operators/utils/device.py244 except Exception as e:CODE
LOWpython/CuTeDSL/prep_editable_install.py160 except Exception as e:CODE
LOWpython/CuTeDSL/prep_editable_install.py268 except Exception as e:CODE
LOWpython/CuTeDSL/_mlir_helpers/vector.py159 except Exception:CODE
LOWpython/CuTeDSL/_mlir_helpers/op.py477 except Exception as e:CODE
LOWpython/CuTeDSL/_mlir_helpers/op.py577 except Exception:CODE
LOWpython/CuTeDSL/_mlir_helpers/op.py615 except Exception as e:CODE
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LOWpython/CuTeDSL/cutlass/__init__.py31 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py571 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py575 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py273 except Exception as exc:CODE
LOWpython/CuTeDSL/cutlass/testing.py537 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py541 except Exception:CODE
LOWpython/CuTeDSL/cutlass/testing.py793 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/testing.py906 except Exception as e:CODE
LOW…L/cutlass/experimental/task_scheduling/task_manager.py364 except Exception:CODE
LOW…hon/CuTeDSL/cutlass/experimental/primitives/gpu_ops.py470 except Exception:CODE
LOW…uTeDSL/cutlass/experimental/primitives/nvvm_wrapper.py2952 except Exception:CODE
LOW…uTeDSL/cutlass/experimental/primitives/nvvm_wrapper.py3062 except Exception:CODE
LOW…uTeDSL/cutlass/experimental/primitives/nvvm_wrapper.py3344 except Exception:CODE
LOWpython/CuTeDSL/cutlass/cute/metadata.py555 except Exception:CODE
LOWpython/CuTeDSL/cutlass/cute/runtime.py186 except Exception:CODE
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LOWpython/CuTeDSL/cutlass/memory/tmem.py87 except Exception:CODE
LOWpython/CuTeDSL/cutlass/utils/profiling.py189 except Exception:CODE
MEDIUMpython/CuTeDSL/cutlass/utils/profiling.py186def __del__(self) -> None:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/version_info.py17except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py1477 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py1656 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py1726 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py2275 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/dsl.py2374 except Exception as e:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_entrypoints.py695 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_entrypoints.py1097 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_entrypoints.py1482 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_entrypoints.py1582 except Exception:CODE
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LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py1266 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py1272 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py1281 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py1795 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py1800 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py1808 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py1816 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py1821 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py2335 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py2344 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py2349 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py2359 except Exception:CODE
LOWpython/CuTeDSL/cutlass/base_dsl/pyir_core.py2381 except Exception:CODE
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AI Slop Vocabulary63 hits · 160 pts
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MEDIUM…CuTeDSL/cute/ampere/kernel/attention/hstu_attention.py43The example showcases an implementation of HSTU attention(https://arxiv.org/abs/2402.17152) within generative recommendeSTRING
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MEDIUM…CuTeDSL/cute_ext/blackwell/attention/gqa_decode_opt.py1934# Perf-harness dtype plumbing: Q/K/V/O share one element type in this kernel.COMMENT
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AI Structural Patterns169 hits · 142 pts
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LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/copy.py1730CODE
LOWpython/CuTeDSL/cutlass/cute/nvgpu/cpasync/copy.py1789CODE
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Structural Annotation Overuse88 hits · 139 pts
SeverityFileLineSnippetContext
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LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py374 # Step 1: Compute TMEM allocationsCOMMENT
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py385 # Step 2: Compute SMEM bytes per stageCOMMENT
LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py404 # Step 3: Compute final stage countsCOMMENT
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LOWpython/CuTeDSL/cutlass/testing.py560 # Step 2: Capture profiling graphCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py584 # Step 3: Instantiate executable graphsCOMMENT
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LOWpython/CuTeDSL/cutlass/testing.py600 # Step 5: Profile execution using selected profilerCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py619 # Step 6: Cleanup - Destroy graph executablesCOMMENT
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LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py152 # Step 2: consolidate duplicated framesCOMMENT
LOWpython/cutlass_library/sm100_utils.py90#### Step 1: generate MMA instruction shapes based on levelsCOMMENT
LOWpython/cutlass_library/sm100_utils.py56#### Step 0: define levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py106#### Step 1: generate MMA instruction shapes based on levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py406#### Step 3: map tile description to valid schedulesCOMMENT
LOWpython/cutlass_library/sm90_utils.py71#### Step 0: define levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py279#### Step 2: generate tile descriptions from math instruction shapesCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp576 // Step 1: reduce fragment input (Src) into tRS_rSrcCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp587 // Step 2: copy the partial results in tRS_rSrc to sRows in shared memoryCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp599 // Step 3: copy the partial results in sRows to tSR_sRow for reductionCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp613 // Step 4: atomically reduce the results to global memoryCOMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp341 /// Step 0: Step 1:COMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp559 /// Step 0: Step 1: Step 2: Step 3:COMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp569 /// Step 4: Step 5: Step 6: Step 7:COMMENT
LOW…lass_compiler/cutegen/test/cg_composed_layout_test.cpp190 // Step 1: layout_b((0,2)) = 0*3 + 2*1 = 2COMMENT
LOW…lass_compiler/cutegen/test/cg_composed_layout_test.cpp191 // Step 2: calculated_offset = off + layout_b(coord) = 0 + 2 = 2COMMENT
LOW…lass_compiler/cutegen/test/cg_composed_layout_test.cpp192 // Step 3: layout_a(calculated_offset) = layout_a(2) = 2*1 = 2COMMENT
LOW…eduling/blackwell/tutorial/01_copy_basics_ts/README.md107### Step 1: What resources are needed, and whyCOMMENT
LOW…eduling/blackwell/tutorial/01_copy_basics_ts/README.md130### Step 2: How to define the work on each resource (producer vs consumer)COMMENT
LOW…eduling/blackwell/tutorial/01_copy_basics_ts/README.md190### Step 3: How a value flows between resources (captured values)COMMENT
LOW…eduling/blackwell/tutorial/01_copy_basics_ts/README.md218### Step 4: How to define the scheduleCOMMENT
LOW…eduling/blackwell/tutorial/01_copy_basics_ts/README.md277### Step 5: How to define the dependency graphCOMMENT
LOW…eduling/blackwell/tutorial/01_copy_basics_ts/README.md297### Step 6: How to define the taskCOMMENT
LOW…eduling/blackwell/tutorial/01_copy_basics_ts/README.md323### Step 7: TaskManager and the fixed lifecycleCOMMENT
LOW…s/python/CuTeDSL/experimental/primitives/redux_sync.py526 # Step 1: load BF16 element and widen to FP32COMMENT
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Modern Structural Boilerplate126 hits · 127 pts
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Verbosity Indicators78 hits · 122 pts
SeverityFileLineSnippetContext
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LOW…ors/cutlass/operators/fusion/passes/pass_dag_2_tree.py62 # Step 2: find the lowest common ancestor (LCA) of all its parentsCOMMENT
LOW…cutlass/operators/fusion/passes/pass_preprocess_red.py51 # Step 1: find the compute nodes with op=redCOMMENT
LOW…cutlass/operators/fusion/passes/pass_preprocess_red.py63 # Step 2: for each compute, merge it with the succeeding storeCOMMENT
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LOW…cutedsl/gemm/implementations/sm100_mixed_input_impl.py404 # Step 3: Compute final stage countsCOMMENT
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LOWpython/cutlass_cppgen/backend/c_types.py566 # Step 1: convert the dtypeCOMMENT
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LOW…s_cppgen/backend/evt/passes/pass_layout_elimination.py60 # Step 1: get the propagation directionCOMMENT
LOW…hon/cutlass_cppgen/backend/evt/backend/emitter_base.py78 # Step 1: emit individual node type declCOMMENT
LOW…hon/cutlass_cppgen/backend/evt/backend/emitter_base.py90 # Step 2: post-processing & get callback nameCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py522 # Step 1: Capture warmup graphCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py560 # Step 2: Capture profiling graphCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py584 # Step 3: Instantiate executable graphsCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py594 # Step 4: Execute warmup graph (cache warming)COMMENT
LOWpython/CuTeDSL/cutlass/testing.py600 # Step 5: Profile execution using selected profilerCOMMENT
LOWpython/CuTeDSL/cutlass/testing.py619 # Step 6: Cleanup - Destroy graph executablesCOMMENT
LOW…eDSL/cutlass/utils/static_persistent_tile_scheduler.py622 # Step 1: Decode current_work_linear_idx using FastDivmod objectsCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py149 # Step 1: filter internal framesCOMMENT
LOWpython/CuTeDSL/cutlass/base_dsl/utils/stacktrace.py152 # Step 2: consolidate duplicated framesCOMMENT
LOW…SL/cutlass/base_dsl/tvm_ffi_builder/tvm_ffi_builder.py1746 # otherwise, it appears more than once, we need to check if the value matchesCOMMENT
LOWpython/cutlass_library/sm100_utils.py90#### Step 1: generate MMA instruction shapes based on levelsCOMMENT
LOWpython/cutlass_library/sm100_utils.py56#### Step 0: define levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py106#### Step 1: generate MMA instruction shapes based on levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py406#### Step 3: map tile description to valid schedulesCOMMENT
LOWpython/cutlass_library/sm90_utils.py71#### Step 0: define levelsCOMMENT
LOWpython/cutlass_library/sm90_utils.py279#### Step 2: generate tile descriptions from math instruction shapesCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp576 // Step 1: reduce fragment input (Src) into tRS_rSrcCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp587 // Step 2: copy the partial results in tRS_rSrc to sRows in shared memoryCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp599 // Step 3: copy the partial results in sRows to tSR_sRow for reductionCOMMENT
LOW…/cutlass/epilogue/threadblock/fusion/visitor_store.hpp613 // Step 4: atomically reduce the results to global memoryCOMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp341 /// Step 0: Step 1:COMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp559 /// Step 0: Step 1: Step 2: Step 3:COMMENT
LOW…/cutlass/transform/collective/sm90_wgmma_transpose.hpp569 /// Step 4: Step 5: Step 6: Step 7:COMMENT
LOW…lass_compiler/cutegen/test/cg_composed_layout_test.cpp190 // Step 1: layout_b((0,2)) = 0*3 + 2*1 = 2COMMENT
LOW…lass_compiler/cutegen/test/cg_composed_layout_test.cpp191 // Step 2: calculated_offset = off + layout_b(coord) = 0 + 2 = 2COMMENT
LOW…lass_compiler/cutegen/test/cg_composed_layout_test.cpp192 // Step 3: layout_a(calculated_offset) = layout_a(2) = 2*1 = 2COMMENT
LOW…s/python/CuTeDSL/experimental/primitives/redux_sync.py526 # Step 1: load BF16 element and widen to FP32COMMENT
LOW…s/python/CuTeDSL/experimental/primitives/redux_sync.py529 # Step 2: warp abs-max — single ``redux.sync.max.abs.f32``COMMENT
LOW…s/python/CuTeDSL/experimental/primitives/redux_sync.py533 # Step 3: guard against zero-valued rows; compute inverse scaleCOMMENT
LOW…s/python/CuTeDSL/experimental/primitives/redux_sync.py539 # Step 4: quantize — F2FP.SATFINITE saturates to ±448 automaticallyCOMMENT
LOW…s/python/CuTeDSL/experimental/primitives/redux_sync.py542 # Step 5: lane 0 writes the per-row dequantization scaleCOMMENT
LOW…ython/CuTeDSL/experimental/primitives/tma/tma_store.py122 # Step 1: TMA load src tile into smem_in.COMMENT
LOW…ython/CuTeDSL/experimental/primitives/tma/tma_store.py141 # Step 2: All threads cooperatively add a constant.COMMENT
18 more matches not shown…
AI Response Leakage4 hits · 30 pts
SeverityFileLineSnippetContext
HIGH…CuTeDSL/dsl_tutorials/programmatic_dependent_launch.py171 # In this example, we add a loop (10 times) for all the copy and compute operations in the following codeCOMMENT
HIGH…CuTeDSL/dsl_tutorials/programmatic_dependent_launch.py183 # In this example, the second kernel's second operand ``gB`` has no dependencies, its loading can overlapCOMMENT
HIGH…scaled_gemm/dense_blockscaled_mxfp6_gemm_persistent.py520 # In this example, we have a fixed strucuture that we follow:COMMENT
HIGH…CuTeDSL/cute/blackwell/tutorial/tutorial_tma/tma_v1.py260 # In this example `copy_elems = 1` and `thread_layout` has shape (T, V) = (num_trans_threads, 1),COMMENT
Dead Code13 hits · 26 pts
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MEDIUMpython/CuTeDSL/_mlir_helpers/op.py575CODE
MEDIUMpython/CuTeDSL/_mlir_helpers/op.py580CODE
MEDIUMpython/CuTeDSL/_mlir_helpers/op.py585CODE
MEDIUMpython/CuTeDSL/_mlir_helpers/op.py587CODE
MEDIUMpython/CuTeDSL/_mlir_helpers/op.py592CODE
MEDIUMpython/CuTeDSL/_mlir_helpers/op.py594CODE
MEDIUMpython/CuTeDSL/_mlir_helpers/op.py663CODE
MEDIUMpython/CuTeDSL/_mlir_helpers/op.py664CODE
MEDIUMpython/CuTeDSL/_mlir_helpers/op.py666CODE
MEDIUMpython/cutlass_library/rank_k_operation.py84CODE
MEDIUMpython/cutlass_library/rank_2k_operation.py86CODE
MEDIUMpython/cutlass_library/symm_operation.py86CODE
MEDIUMpython/cutlass_library/trmm_operation.py83CODE
Cross-Language Confusion5 hits · 11 pts
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HIGHpython/cutlass_cppgen/backend/conv2d_operation.py257 if (args.tensor_c_numel >= 0 && args.tensor_c_numel == tc_C.at(3) && args.tensor_c_numel < size_C) {CODE
HIGH…uTeDSL/cutlass/experimental/primitives/nvvm_wrapper.py3971 non-conforming values undefined). The wrapper exposes the full option set thisSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/dsl.py1856 process stderr and the lookup returns null, which the upstream wrapperSTRING
HIGHpython/CuTeDSL/cutlass/base_dsl/array.py3023 Elements where the mask is False use the default value (or are undefined).STRING
HIGHpython/CuTeDSL/cutlass/base_dsl/array.py3812 Elements where mask is False use the default value (or are undefined).STRING
Example Usage Blocks2 hits · 3 pts
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LOWpython/cutlass_library/emit_kernel_listing.py41# Example usage:COMMENT
LOWcutlass_compiler/scripts/run_integration_host.sh41# Usage:COMMENT
Modern AI Meta-Vocabulary1 hit · 3 pts
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MEDIUM…buted/distributed_gemm_all_reduce_lamport_blackwell.py2647 # Test scaffold: slot[0] enters as the Lamport -0.0 sentinelCOMMENT