Files
composable_kernel/include/ck_tile/host/reference/reference_reduce.hpp
rocking 3d60953477 [Ck tile] support rmsnorm and related fusion (#1605)
* Add reduce2d new api

* Prevent user use cross warp reduction

* Fix bug of std caculation

* Add rmsnorm2d

* Add rmsnorm small example

* Remove static assert to prevent compile fail

* Add script to test performance and correctness

* Add missing cmake change

* refine naming

* refine example of rmsnorm

* Fix bug of rmsnorm

* Refine naming

* Fix cmake

* clang format

* Refine pipeline name

* Add add_rmsnorm2d_rdquant kernel

* Add reduce op

* host verification

* Fix bug of one pass pipeline

* Refine tile size

* Add two pass pipeline

* Rename two pass to three pass

* Fix bug of kSaveX == false

* Add instance library

* Add test script

* Fix bug of x verification

* Add save_x to trait

* Add README

* Move reduce2d into reduce folder

* Fix bug of welford when number of m warp > 1

* remove reduncant comment

* 1. move 06_rmsnorm2d to 10_rmsnorm2d
2. move 07_add_rmsnorm2d_rdquant to 11_add_rmsnorm2d_rdquant

* clang format and add missing header

* Add host validation of add + layernorm2d + rsquant

* Revert "Add host validation of add + layernorm2d + rsquant"

This reverts commit 936cb45797.

* Remove deprecated flag
2024-10-30 15:22:56 +08:00

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993 B
C++

// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/host/host_tensor.hpp"
#include <thread>
namespace ck_tile {
template <typename XDataType, typename ComputeDataType, typename YDataType, typename ReduceOp>
CK_TILE_HOST void
reference_reduce(const HostTensor<XDataType>& x_m_n, HostTensor<YDataType>& y_m, ReduceOp reduce_op)
{
auto f = [&](auto m) {
const int N = x_m_n.mDesc.get_lengths()[1];
ComputeDataType v_acc = reduce_op.template GetIdentityValue<ComputeDataType>();
for(int n = 0; n < N; ++n)
{
const ComputeDataType v_a = type_convert<ComputeDataType>(x_m_n(m, n));
v_acc = reduce_op(v_acc, v_a);
}
y_m(m) = ck_tile::type_convert<YDataType>(v_acc);
};
make_ParallelTensorFunctor(f, y_m.mDesc.get_lengths()[0])(std::thread::hardware_concurrency());
}
} // namespace ck_tile