v4.2 tag release. (#2638)

examples/python/CuTeDSL/ampere/dynamic_smem_size.py

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+# Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: BSD-3-Clause
+
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+
+# 1. Redistributions of source code must retain the above copyright notice, this
+# list of conditions and the following disclaimer.
+
+# 2. Redistributions in binary form must reproduce the above copyright notice,
+# this list of conditions and the following disclaimer in the documentation
+# and/or other materials provided with the distribution.
+
+# 3. Neither the name of the copyright holder nor the names of its
+# contributors may be used to endorse or promote products derived from
+# this software without specific prior written permission.
+
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+import cutlass.cute as cute
+import cutlass
+
+"""
+Example of automatic shared memory size computation for configuring kernel launch
+
+This example demonstrates how to let the DSL automatically set shared memory
+  size for a kernel launch rather explicitly configuring it at launch time,
+  provided that developers are using `SmemAllocator` for all allocations.
+
+Usage:
+    python dynamic_smem_size.py         # Show auto inference
+"""
+
+
+@cute.struct
+class SharedData:
+    """A struct to demonstrate shared memory allocation."""
+
+    values: cute.struct.MemRange[cutlass.Float32, 64]  # 256 bytes
+    counter: cutlass.Int32  # 4 bytes
+    flag: cutlass.Int8  # 1 byte
+
+
+@cute.kernel
+def kernel():
+    """
+    Example kernel that allocates shared memory.
+    The total allocation will be automatically calculated when smem=None.
+    """
+    allocator = cutlass.utils.SmemAllocator()
+
+    # Allocate various types of shared memory
+    shared_data = allocator.allocate(SharedData)
+    raw_buffer = allocator.allocate(512, byte_alignment=64)
+    int_array = allocator.allocate_array(element_type=cutlass.Int32, num_elems=128)
+    tensor_smem = allocator.allocate_tensor(
+        element_type=cutlass.Float16,
+        layout=cute.make_layout((32, 16)),
+        byte_alignment=16,
+        swizzle=None,
+    )
+    return
+
+
+@cute.kernel
+def kernel_no_smem():
+    """
+    Example kernel that does not allocates shared memory.
+    The total allocation will be automatically calculated as 0 when smem=None.
+    """
+    tidx, _, _ = cute.arch.block_idx()
+    if tidx == 0:
+        cute.printf("Hello world")
+    return
+
+
+if __name__ == "__main__":
+    # Initialize CUDA context
+    cutlass.cuda.initialize_cuda_context()
+
+    print("Launching kernel with auto smem size. (launch config `smem=None`)")
+
+    # Compile the example
+    @cute.jit
+    def launch_kernel1():
+        k = kernel()
+        k.launch(
+            grid=(1, 1, 1),
+            block=(1, 1, 1),
+        )
+        print(f"Kernel recorded internal smem usage: {k.smem_usage()}")
+
+    @cute.jit
+    def launch_kernel2():
+        k = kernel_no_smem()
+        k.launch(
+            grid=(1, 1, 1),
+            block=(1, 1, 1),
+        )
+        print(f"Kernel recorded internal smem usage: {k.smem_usage()}")
+
+    cute.compile(launch_kernel1)
+    cute.compile(launch_kernel2)
+
+    print("PASS")