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v4.4.1 update (#3079)

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Junkai-Wu
2026-02-27 13:59:21 -05:00
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commit 3bb6e28d3c
13 changed files with 92 additions and 23 deletions
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README.md
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![ALT](./media/images/gemm-hierarchy-with-epilogue-no-labels.png "Complete CUDA GEMM decomposition")
# Overview
# CUTLASS 4.4.0
# CUTLASS 4.4.1
_CUTLASS 4.4.0 - Feb 2026_
_CUTLASS 4.4.1 - Feb 2026_
CUTLASS is a collection of abstractions for implementing high-performance matrix-matrix multiplication (GEMM)
and related computations at all levels and scales within CUDA. It incorporates strategies for
@@ -84,6 +84,7 @@ To get started quickly - please refer :
- Fixed `cute.printf` with f-string
- Fixed an indexing issue of scalar tensor
- Fixed small K reference check error for cta_tile_n = 256 case with overlapping accumulator optimization in [Blackwell SM100 persistent dense blockscaled GEMM with static scheduling](https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/dense_blockscaled_gemm_persistent.py).
- Fixed a segfault issue with tvm-ffi on aarch64
* API changes
- Deprecate get_num_tmem_alloc_cols from blackwell_helpers.py. Use the one from tmem_allocator.py instead.