[BUG] CuTe Python DSL: cute.coalesce(cute.prepend(...)) corrupts memory for complement layout

Author: new-TonyWangCreated May 20, 2026Updated Sep 17, 2026

Labelsbug? - Needs Triageinactive-30dinactive-90dCuTe DSL

Which component has the problem?

CuTe DSL

Bug Report

The CuTe Python DSL can hit native memory corruption when cute.coalesce() is applied to a layout produced by cute.prepend() using a complement layout.

Minimal example:

python

x_ori = cute.make_layout((6,), stride=(4,))  # (6):(4)
x = cute.complement(x_ori, 24)              # 4:1
combined = cute.prepend(x_ori, x)           # (4,6):(1,4)
coalesced = cute.coalesce(combined)         # expected 24:1
print(cute.pretty_str(coalesced))           # crashes

Expected result:

24:1

Actual result:

malloc(): unaligned tcache chunk detected

Environment

OS: Linux-6.8.0-100-generic-x86_64-with-glibc2.39
Python: 3.12.13 | packaged by Anaconda, Inc. | GCC 14.3.0
Python executable: /home/tongyu/miniconda3/envs/wty_py312/bin/python
cutlass.__version__: unknown
cutlass module path: /home/tongyu/miniconda3/envs/wty_py312/lib/python3.12/site-packages/nvidia_cutlass_dsl/python_packages/cutlass/__init__.py
nvidia-cutlass-dsl: 4.3.5
nvidia-cutlass-dsl-libs-base: 4.4.1
nvidia-cutlass-dsl-libs-cu13: 4.4.1

Relevant installed packages:

cuda-bindings                13.2.0
cuda-pathfinder              1.5.4
cuda-python                  13.2.0
cuda-tile                    1.1.0
nvidia-cutlass-dsl           4.3.5
nvidia-cutlass-dsl-libs-base 4.4.1
nvidia-cutlass-dsl-libs-cu13 4.4.1

Reproduction

Save as repro_cute_coalesce_prepend.py:

python

import cutlass
import cutlass.cute as cute
from cutlass._mlir import ir

print('python repro start', flush=True)
print('cutlass version:', getattr(cutlass, '__version__', 'unknown'), flush=True)

with ir.Context():
    x_ori = cute.make_layout((6,), stride=(4,))
    x = cute.complement(x_ori, 24)
    print('x_ori =', cute.pretty_str(x_ori), flush=True)
    print('x =', cute.pretty_str(x), flush=True)

    combined = cute.prepend(x_ori, x)
    print('combined =', cute.pretty_str(combined), flush=True)

    coalesced = cute.coalesce(combined)
    print('coalesced repr =', repr(coalesced), flush=True)

    # Expected: 24:1
    # Actual: malloc/tcache corruption before or during this print.
    print('coalesced pretty =', cute.pretty_str(coalesced), flush=True)

Run:

bash

python repro_cute_coalesce_prepend.py

Observed output:

python repro start
cutlass version: unknown
x_ori = (6):(4)
x = 4:1
combined = (4,6):(1,4)
coalesced repr = <cutlass.cute.core._Layout object at 0x...>
malloc(): unaligned tcache chunk detected

Expected behavior

cute.prepend(x_ori, x) pretty-prints as:

(4,6):(1,4)

This layout is contiguous in column-major order, so cute.coalesce() should return:

24:1

Equivalent construction through cute.make_layout() works conceptually:

python

with ir.Context():
    y = cute.make_layout((4, 6), stride=(1, 4))
    z = cute.coalesce(y)
    print(cute.pretty_str(z))  # 24:1

Actual behavior

cute.coalesce() returns a _Layout object, but cute.pretty_str() on that object triggers native memory corruption:

malloc(): unaligned tcache chunk detected

In some local runs, similar tcache/double-linked-list corruption also occurred around related layout objects after complement()/attribute access, suggesting a lifetime/ownership issue in the Python binding or underlying MLIR object wrapper.

Notes / suspected cause

This looks like a native lifetime or ownership bug rather than a Python exception-level issue:

No Python traceback is produced.
The process aborts with glibc allocator corruption.
The same logical layout can be represented as (4,6):(1,4) and should coalesce to 24:1.
The crash is tied to layouts produced via cute.prepend()/cute.complement() and then passed to cute.coalesce().

Source: NVIDIA/cutlass

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