From bf9da7b76c766d7ee7d536afc77880a4ef1f1156 Mon Sep 17 00:00:00 2001
From: Haicheng Wu <57973641+hwu36@users.noreply.github.com>
Date: Wed, 25 Dec 2024 17:11:15 -0500
Subject: [PATCH] Update CHANGELOG.md

---
 CHANGELOG.md | 21 +--------------------
 1 file changed, 1 insertion(+), 20 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 1ba870eba..2c105cf80 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -23,26 +23,7 @@
 - A new hardware support for comparisons and computations of [`cutlass::bfloat16_t`](./include/cutlass/bfloat16.h)
 - Fixed use of isnan on Windows for [`half_t`](./test/unit/core/functional.cu).
 - Various improvements and fixes from the community and CUTLASS team. Thanks to everyone who submitted PRs!
-
-- [Minimal SM90 WGMMA + TMA GEMM example in 100 lines of code](./examples/cute/tutorial/wgmma_sm90.cu)
-- [Exposure of L2 `cache_hint`s in TMA copy atoms](./include/cute/arch/copy_sm90_tma.hpp#L48)
-- Exposure of raster order and tile swizzle extent in [CUTLASS library profiler](./media/docs/profiler.md#GEMM), and
-[example 48](./examples/48_hopper_warp_specialized_gemm/48_hopper_warp_specialized_gemm.cu).
-- [TMA store based and EVT supported epilogues](./include/cutlass/epilogue/collective/sm90_epilogue_array_tma_warpspecialized.hpp) for [Hopper pointer array batched kernels](./test/unit/gemm/device/sm90_gemm_f16_f16_f16_tensor_op_f32_ptr_array.cu).
-- A new [`GemmSparseUniversal` API for CUTLASS 2.x Ampere kernels](./include/cutlass/gemm/device/gemm_sparse_universal.h) to enable serial and parallel split-k for sparse tensor cores and new tiny tile sizes to better support LLM inferrence:
-  + [FP16 TN](./test/unit/gemm/device/gemm_f16t_f16n_f32t_tensor_op_f32_sparse_sm80.cu#L269-L393) and [NT](./test/unit/gemm/device/gemm_f16n_f16t_f32t_tensor_op_f32_sparse_sm80.cu#L269-L411).
-  + [int8 TN](./test/unit/gemm/device/gemm_s8t_s8n_s32t_tensor_op_s32_sparse_sm80.cu#L264-L452).
-  + [int4 TN](./test/unit/gemm/device/gemm_s4t_s4n_s32t_tensor_op_s32_sparse_sm80.cu#L264-L452).
-  + [FP32 TN](./test/unit/gemm/device/gemm_f32t_f32n_f32t_tensor_op_f32_sparse_sm80.cu#L427-L642) and [NT](./test/unit/gemm/device/gemm_f32n_f32t_f32t_tensor_op_f32_sparse_sm80.cu#L427-L456).
-- [CUDA host adapter](./include/cutlass/cuda_host_adapter.hpp) extensions to support TMA descriptor construction driver APIs.
-- Inclusion of more [Hopper fprop, dgrad, and wgrad convolution kernels in CUTLASS library and profiler](./python/cutlass_library/generator.py).
-- Support for residual add (beta != 0) in convolution kernels.
-- A new convolution [epilogue](./examples/16_ampere_tensorop_conv2dfprop/ampere_tensorop_conv2dfprop.cu#L269) for CUTLASS 2.x to support non-packed NHWC output.
-- A refactor of [include files throughout CUTLASS core directories](./include/cutlass/gemm/collective/collective_mma_decl.hpp) to reduce circular dependencies and [tests to guard against them](./test/self_contained_includes/CMakeLists.txt).
-- [A guide for setting up VSCode to work well with CUTLASS](./media/docs/ide_setup.md) and [expanded code style guide](./media/docs/programming_guidelines.md).
-- Better support for MSVC as a host compiler.
-- Many performance optimizations, improvements, and bug fixes including fixes for FlashAttention-2.
-- Optimal code generation with CUDA toolkit versions 12.4 and 12.5u1.
+- Optimal code generation with CUDA toolkit versions 12.6.
 
 ## [3.5.1](https://github.com/NVIDIA/cutlass/releases/tag/v3.5.1) (2024-07-25)