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cutlass/examples/python/CuTeDSL/ampere/dynamic_smem_size.py
2026-04-07 12:16:05 -04:00

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Python

# Copyright (c) 2025 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
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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_static():
"""
Example kernel that allocates shared memory.
The total allocation will be automatically calculated when smem=None.
"""
tidx, _, _ = cute.arch.block_idx()
if tidx == 0:
cute.printf("Running kernel_static")
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,
)
cute.printf("Kernel launch smem size: {}", cute.arch.dynamic_smem_size())
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("Running kernel_no_smem")
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 static example
@cute.jit
def launch_kernelno_smem():
kernel_no_smem().launch(
grid=(1, 1, 1),
block=(1, 1, 1),
)
# --------
print(f" > Run {kernel_no_smem.__name__}")
func = cute.compile(launch_kernelno_smem)
func()
cutlass.cuda.stream_sync(cutlass.cuda.default_stream())
@cute.jit
def launch_kernel_static():
kernel_static().launch(
grid=(1, 1, 1),
block=(1, 1, 1),
# smem=None
# auto infer launch kernel static smem usage
)
# --------
print(f" > Run {kernel_static.__name__} with sufficient smem")
func = cute.compile(launch_kernel_static)
func()
cutlass.cuda.stream_sync(cutlass.cuda.default_stream())
@cute.jit
def launch_kernel_static_insufficient():
kernel_static().launch(
grid=(1, 1, 1),
block=(1, 1, 1),
# launch kernel with static smem usage exceeds cfg
# show warning
smem=16,
)
# --------
print(f" > Run {kernel_static.__name__} with insufficient smem, show warning:")
func = cute.compile(launch_kernel_static_insufficient)
func()
cutlass.cuda.stream_sync(cutlass.cuda.default_stream())
print("PASS")