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/***************************************************************************************************
* Copyright (c) 2023 - 2024 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.
*
**************************************************************************************************/
/*! \file
\brief Simple permutation kernel implementation.
*/
#include "cutlass/layout/pitch_linear.h"
#include "cutlass/layout/matrix.h"
#include "cutlass/tensor_view.h"
#include "cutlass/fast_math.h"
#include "cute/numeric/uint128.hpp"
namespace example
{
/**
* Assumes column-major input (M mode is contiguous, N mode is strided).
* For row major, the inputs must be switched accordingly.
*/
template<bool Batched, typename Element, typename Permute>
__global__ void
permute_kernel(Element const* __restrict__ input,
Element* __restrict__ output,
Permute permute,
int64_t num_elems,
cutlass::FastDivmod stride_divmod)
{
// CUTLASS 2.x batched permute functions assume 0 batch stride for target tensor
Element const * input_b = input + blockIdx.z * num_elems;
Element * output_b = output + (Batched ? 0 : blockIdx.z * num_elems);
for (int64_t k = threadIdx.x + blockIdx.x * blockDim.x; k < num_elems; k += blockDim.x * gridDim.x)
{
int i, j;
stride_divmod(j, i, k);
output_b[permute(cutlass::PitchLinearCoord(i, j))] = input_b[i + j * stride_divmod.divisor];
}
}
template<bool Batched, typename Permute, typename Element>
void permute(Element const* input,
Element * output,
int64_t num_elems,
int stride,
int batch_count,
cutlass::KernelHardwareInfo const& hw_info)
{
// Upcast to uint128_t data type
int factor = 128 / cutlass::sizeof_bits<Element>::value;
assert(stride % factor == 0);
int stride_upcast = stride/factor;
int64_t num_elems_upcast = num_elems / factor;
Permute permute_upcast(cutlass::PitchLinearCoord(stride_upcast, int(num_elems_upcast/stride_upcast)), stride_upcast);
cutlass::FastDivmod stride_divmod(stride);
dim3 blocks(hw_info.sm_count, 1, batch_count);
permute_kernel<Batched><<<blocks, 1024>>>(reinterpret_cast<cute::uint128_t const *>(input),
reinterpret_cast<cute::uint128_t *>(output),
permute_upcast,
num_elems_upcast,
stride_upcast);
}
} // namespace example
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