blob: 76551b076a28737d50c30a26fac179f7d8bce11e [file] [log] [blame]
/*
* Copyright (c) 2020-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "src/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyValhall.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/GPUTarget.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "src/gpu/cl/kernels/gemm/ClGemmHelpers.h"
#include "src/runtime/CL/gemm/CLGEMMDefaultTypeValhall.h"
#include <utility>
namespace arm_compute
{
namespace opencl
{
namespace kernels
{
namespace gemm
{
using namespace arm_compute::misc::shape_calculator;
ClGemmDefaultConfigReshapedRhsOnlyValhall::ClGemmDefaultConfigReshapedRhsOnlyValhall(GPUTarget gpu)
: IClGemmKernelConfig(gpu)
{
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure(unsigned int m, unsigned int n, unsigned int k, unsigned int b, DataType data_type)
{
using ConfigurationFunctionExecutorPtr = std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> (ClGemmDefaultConfigReshapedRhsOnlyValhall::*)(unsigned int m, unsigned int n, unsigned int k,
unsigned int b);
CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G77(&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f32,
&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f16,
&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8);
CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G78(&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f32,
&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f16,
&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8);
CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G710(&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f32,
&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G710_f16,
&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8);
CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G715(&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G715_f32,
&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G715_f16,
&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8);
ConfigurationFunctionExecutorPtr func = nullptr;
switch(_target)
{
case GPUTarget::G78:
func = configs_G78.get_function(data_type);
break;
case GPUTarget::G710:
case GPUTarget::G610:
func = configs_G710.get_function(data_type);
break;
case GPUTarget::G715:
case GPUTarget::G615:
func = configs_G715.get_function(data_type);
break;
case GPUTarget::G77:
default:
func = configs_G77.get_function(data_type);
break;
}
ARM_COMPUTE_ERROR_ON_MSG(func == nullptr, "Data type not support for GEMM");
return (this->*func)(m, n, k, b);
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
{
if(m == 1)
{
const float r_mn = static_cast<float>(m) / static_cast<float>(n);
const float r_mk = static_cast<float>(m) / static_cast<float>(k);
if(r_mk <= 0.0064484127797186375)
{
if(r_mn <= 0.0028273810748942196)
{
GEMMLHSMatrixInfo lhs_info_buf;
GEMMRHSMatrixInfo rhs_info_buf;
GEMMLHSMatrixInfo lhs_info_img;
GEMMRHSMatrixInfo rhs_info_img;
const unsigned int h0 = std::max(n / 4, 1U);
std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 1, 4, 8, 1, 16, 0, 1, 0, 0, 1);
std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 1, 4, 4, 1, h0, 0, 1, 0, 1, 0);
return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
std::make_pair(lhs_info_buf, rhs_info_buf),
n, k, b, DataType::F32);
}
else
{
return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 8, 0, 1, 0, 0, 0);
}
}
else
{
if(r_mk <= 0.020312500186264515)
{
return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 4, 0, 1, 0, 0, 0);
}
else
{
return configure_lhs_rhs_info(m, n, 1, 4, 16, 1, 16, 0, 1, 0, 1, 0);
}
}
}
else
{
const float r_mn = static_cast<float>(m) / static_cast<float>(n);
const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
const float r_mk = static_cast<float>(m) / static_cast<float>(k);
if(workload <= 1999.2000122070312)
{
if(workload <= 747.1999816894531)
{
return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0);
}
else
{
GEMMLHSMatrixInfo lhs_info_buf;
GEMMRHSMatrixInfo rhs_info_buf;
GEMMLHSMatrixInfo lhs_info_img;
GEMMRHSMatrixInfo rhs_info_img;
std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 2, 0, 0, 0, 1, 1);
std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0);
return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
std::make_pair(lhs_info_buf, rhs_info_buf),
n, k, b, DataType::F32);
}
}
else
{
if(r_mn <= 0.03348214365541935)
{
if(r_mk <= 0.028125000186264515)
{
return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0);
}
else
{
GEMMLHSMatrixInfo lhs_info_buf;
GEMMRHSMatrixInfo rhs_info_buf;
GEMMLHSMatrixInfo lhs_info_img;
GEMMRHSMatrixInfo rhs_info_img;
std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 2, 0, 0, 0, 1, 1);
std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0);
return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
std::make_pair(lhs_info_buf, rhs_info_buf),
n, k, b, DataType::F32);
}
}
else
{
GEMMLHSMatrixInfo lhs_info_buf;
GEMMRHSMatrixInfo rhs_info_buf;
GEMMLHSMatrixInfo lhs_info_img;
GEMMRHSMatrixInfo rhs_info_img;
std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, 0, 1, 0, 0, 1);
std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 16, 0, 1, 0, 1, 0);
return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
std::make_pair(lhs_info_buf, rhs_info_buf),
n, k, b, DataType::F32);
}
}
}
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
{
const GeMMConfigsMatrix configs_1nkb_best =
{
{ 1, 8984, 640, 1, 1, 8, 8, 1, 0, 1, 1, 1, 1, 0 },
{ 1, 420, 392, 1, 1, 2, 8, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 644, 5288, 1, 1, 2, 8, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 6512, 6404, 1, 1, 4, 8, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 5304, 640, 1, 1, 4, 4, 1, 0, 1, 0, 1, 1, 0 },
{ 1, 1352, 1520, 1, 1, 2, 8, 1, 0, 1, 1, 1, 1, 0 },
{ 1, 4096, 25088, 1, 1, 2, 16, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 732, 8988, 1, 1, 2, 8, 1, 0, 1, 0, 1, 0, 0 }
};
const GeMMConfigsMatrix configs_mnkb_n_small_best =
{
{ 102400, 4, 96, 1, 2, 2, 16, 1, 4, 1, 1, 1, 1, 0 },
{ 102400, 2, 96, 1, 1, 2, 16, 1, 0, 1, 0, 1, 1, 1 },
{ 16384, 4, 128, 1, 1, 2, 16, 1, 0, 1, 0, 1, 1, 1 },
{ 16384, 2, 128, 1, 1, 2, 16, 1, 0, 1, 1, 1, 1, 1 }
};
const GeMMConfigsMatrix configs_mnkb_n_small_fallback =
{
{ 102400, 4, 96, 1, 2, 2, 16, 1, 4, 1, 1, 1, 1, 0 },
{ 102400, 2, 96, 1, 1, 2, 16, 1, 0, 1, 1, 1, 1, 0 },
{ 16384, 4, 128, 1, 2, 2, 16, 1, 2, 1, 1, 1, 1, 0 },
{ 16384, 2, 128, 1, 1, 2, 16, 1, 0, 1, 1, 1, 1, 0 }
};
const GeMMConfigsMatrix configs_mnkb_m_gt_n_best =
{
{ 25584, 88, 16, 1, 4, 8, 4, 1, 8, 1, 1, 1, 0, 0 },
{ 25584, 16, 68, 1, 4, 4, 8, 1, 16, 1, 1, 1, 0, 1 },
{ 369664, 32, 28, 1, 5, 4, 4, 1, 64, 1, 1, 1, 0, 1 },
{ 65792, 44, 24, 1, 4, 8, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 23036, 56, 736, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 1 },
{ 90968, 40, 600, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 1 },
{ 8944, 32, 776, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 1 },
{ 50176, 64, 300, 1, 4, 8, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 16544, 104, 160, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 1 },
{ 12604, 60, 160, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 1 },
{ 29584, 32, 28, 1, 4, 4, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 12544, 32, 27, 1, 2, 8, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 2688, 136, 1492, 1, 8, 4, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 3728, 96, 196, 1, 4, 8, 4, 1, 128, 1, 1, 1, 0, 0 }
};
const GeMMConfigsMatrix configs_mnkb_m_gt_n_fallback =
{
{ 25584, 88, 16, 1, 4, 8, 4, 1, 8, 1, 1, 1, 0, 0 },
{ 25584, 16, 68, 1, 2, 4, 8, 1, 4, 1, 1, 1, 0, 0 },
{ 369664, 32, 28, 1, 5, 4, 4, 1, 256, 1, 1, 1, 0, 0 },
{ 65792, 44, 24, 1, 4, 8, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 23036, 56, 736, 1, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 90968, 40, 600, 1, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 8944, 32, 776, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 0 },
{ 50176, 64, 300, 1, 4, 8, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 16544, 104, 160, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 0 },
{ 12604, 60, 160, 1, 4, 4, 8, 1, 256, 1, 1, 1, 0, 0 },
{ 29584, 32, 28, 1, 4, 4, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 12544, 32, 27, 1, 2, 8, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 2688, 136, 1492, 1, 8, 4, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 3728, 96, 196, 1, 4, 8, 4, 1, 128, 1, 1, 1, 0, 0 }
};
const GeMMConfigsMatrix configs_mnkb_n_gt_m_best =
{
{ 24, 488, 88, 1, 2, 4, 16, 1, 4, 1, 1, 1, 0, 0 },
{ 49, 1024, 512, 1, 4, 4, 8, 1, 128, 1, 1, 1, 0, 1 },
{ 49, 1024, 1024, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 1 },
};
const GeMMConfigsMatrix configs_mnkb_n_gt_m_fallback =
{
{ 24, 488, 88, 1, 2, 4, 16, 1, 4, 1, 1, 1, 0, 0 },
{ 49, 1024, 512, 1, 4, 4, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 49, 1024, 1024, 1, 4, 4, 8, 1, 256, 1, 1, 1, 0, 0 },
};
const GeMMConfigsMatrix configs_mnkb_squared_best =
{
{ 72, 92, 136, 1, 2, 2, 8, 1, 128, 1, 1, 1, 1, 0 },
{ 268, 824, 5076, 1, 4, 8, 4, 1, 256, 1, 1, 1, 0, 0 },
{ 180, 420, 952, 1, 4, 4, 8, 1, 64, 1, 1, 1, 0, 1 },
{ 1000, 152, 304, 1, 4, 4, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 272, 400, 2116, 1, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 196, 512, 512, 1, 5, 4, 4, 1, 64, 1, 1, 1, 0, 1 },
{ 24, 88, 236, 1, 2, 2, 8, 1, 64, 1, 1, 1, 1, 0 },
{ 24, 88, 488, 1, 2, 2, 8, 1, 64, 1, 1, 1, 1, 0 }
};
const GeMMConfigsMatrix configs_mnkb_squared_fallback =
{
{ 72, 92, 136, 1, 2, 2, 8, 1, 128, 1, 1, 1, 1, 0 },
{ 268, 824, 5076, 1, 4, 8, 4, 1, 256, 1, 1, 1, 0, 0 },
{ 180, 420, 952, 1, 4, 4, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 1000, 152, 304, 1, 4, 4, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 272, 400, 2116, 1, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 196, 512, 512, 1, 5, 4, 4, 1, 256, 1, 1, 1, 0, 0 },
{ 24, 88, 236, 1, 2, 2, 8, 1, 64, 1, 1, 1, 1, 0 },
{ 24, 88, 488, 1, 2, 2, 8, 1, 64, 1, 1, 1, 1, 0 }
};
const GeMMConfigsMatrix configs_mnkb_best_batched =
{
{ 3136, 64, 64, 36, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 4096, 48, 32, 36, 4, 4, 8, 1, 64, 1, 1, 1, 0, 1 },
{ 688, 92, 68, 32, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 24, 464, 412, 24, 4, 4, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 112, 184, 144, 28, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 5776, 64, 32, 36, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 1568, 64, 40, 36, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 2920, 64, 64, 24, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 }
};
const GeMMConfigsMatrix configs_mnkb_fallback_batched =
{
{ 3136, 64, 64, 36, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 4096, 48, 32, 36, 4, 4, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 688, 92, 68, 32, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 24, 464, 412, 24, 4, 4, 8, 1, 128, 1, 1, 1, 0, 0 },
{ 112, 184, 144, 28, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 5776, 64, 32, 36, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 1568, 64, 40, 36, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 },
{ 2920, 64, 64, 24, 4, 8, 4, 1, 64, 1, 1, 1, 0, 0 }
};
const GeMMConfigsMatrix *configs_best_to_use = nullptr;
const GeMMConfigsMatrix *configs_fallback_to_use = nullptr;
if(b == 1)
{
constexpr float ratio_m_gt_n = 10.f;
constexpr float ratio_n_gt_m = 0.1f;
constexpr unsigned int n_small_thr = 4;
const float ratio = static_cast<float>(m) / static_cast<float>(n);
if(m == 1)
{
// We do not need fallback in this case, as we never use cl_image for the rhs tensor
configs_best_to_use = &configs_1nkb_best;
configs_fallback_to_use = &configs_1nkb_best;
}
else if(n <= n_small_thr && ratio > ratio_m_gt_n)
{
configs_best_to_use = &configs_mnkb_n_small_best;
configs_fallback_to_use = &configs_mnkb_n_small_fallback;
}
else if(ratio > ratio_m_gt_n)
{
configs_best_to_use = &configs_mnkb_m_gt_n_best;
configs_fallback_to_use = &configs_mnkb_m_gt_n_fallback;
}
else if(ratio < ratio_n_gt_m)
{
configs_best_to_use = &configs_mnkb_n_gt_m_best;
configs_fallback_to_use = &configs_mnkb_n_gt_m_fallback;
}
else
{
configs_best_to_use = &configs_mnkb_squared_best;
configs_fallback_to_use = &configs_mnkb_squared_fallback;
}
}
else
{
configs_best_to_use = &configs_mnkb_best_batched;
configs_fallback_to_use = &configs_mnkb_fallback_batched;
}
GEMMLHSMatrixInfo lhs_info0;
GEMMRHSMatrixInfo rhs_info0;
GEMMLHSMatrixInfo lhs_info1;
GEMMRHSMatrixInfo rhs_info1;
std::tie(lhs_info0, rhs_info0) = find_lhs_rhs_info(*configs_best_to_use, m, n, k, b);
std::tie(lhs_info1, rhs_info1) = find_lhs_rhs_info(*configs_fallback_to_use, m, n, k, b);
return select_lhs_rhs_info(std::make_pair(lhs_info0, rhs_info0),
std::make_pair(lhs_info1, rhs_info1),
n, k, b, DataType::F16);
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
{
ARM_COMPUTE_UNUSED(k);
ARM_COMPUTE_UNUSED(b);
if(m == 1)
{
const unsigned int h0 = std::max(n / 2, 1U);
return configure_lhs_rhs_info(m, n, 1, 4, 16, 1, h0, 0, 1, 0, 1);
}
else
{
const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(256)), static_cast<int>(1));
if(m >= 28)
{
return configure_lhs_rhs_info(m, n, 4, 4, 16, 1, h0, 0, 1, 0, 1);
}
else
{
return configure_lhs_rhs_info(m, n, 2, 4, 16, 1, h0, 0, 1, 0, 1);
}
}
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
{
const float r_mn = static_cast<float>(m) / static_cast<float>(n);
const float r_mk = static_cast<float>(m) / static_cast<float>(k);
const float r_nk = static_cast<float>(n) / static_cast<float>(k);
const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
if(m == 1)
{
if(workload <= 278.7000f)
{
if(workload <= 7.5000f)
{
return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
}
else
{
if(r_mn <= 0.0031f)
{
if(workload <= 256.6000f)
{
if(workload <= 16.7500f)
{
if(r_nk <= 1.6671f)
{
return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
}
else
{
return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
}
}
else
{
return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
}
}
else
{
return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
}
}
else
{
if(r_mk <= 0.0027f)
{
if(r_mk <= 0.0014f)
{
return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
}
else
{
if(workload <= 8.9500f)
{
return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
}
else
{
return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
}
}
}
else
{
if(workload <= 14.1500f)
{
return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
}
else
{
if(r_mk <= 0.0041f)
{
return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
}
else
{
return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
}
}
}
}
}
}
else
{
if(workload <= 363.7000f)
{
if(r_mk <= 0.0031f)
{
return configure_lhs_rhs_info(m, n, 1, 4, 2, 1, 32, 0, 1, 0, 1, 0);
}
else
{
return configure_lhs_rhs_info(m, n, 1, 4, 4, 1, 32, 0, 1, 0, 1, 0);
}
}
else
{
return configure_lhs_rhs_info(m, n, 1, 4, 2, 1, 32, 0, 1, 0, 1, 0);
}
}
}
else
{
if(workload <= 1384.8000f)
{
if(workload <= 704.0000f)
{
return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 32, 0, 1, 0, 1, 0);
}
else
{
return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 4, 0, 0, 0, 1, 1);
}
}
else
{
if(workload <= 16761.6006f)
{
if(r_mn <= 187.1250f)
{
return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 16, 0, 0, 0, 1, 1);
}
else
{
return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 4, 0, 0, 0, 1, 1);
}
}
else
{
if(r_mk <= 432.4630f)
{
return configure_lhs_rhs_info(m, n, 5, 4, 4, 1, 16, 0, 0, 0, 1, 1);
}
else
{
return configure_lhs_rhs_info(m, n, 2, 4, 4, 1, 16, 0, 1, 0, 1, 1);
}
}
}
}
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
{
const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
const float r_mn = static_cast<float>(m) / static_cast<float>(n);
const float r_mk = static_cast<float>(m) / static_cast<float>(k);
const float r_nk = static_cast<float>(n) / static_cast<float>(k);
if(m == 1)
{
if(r_mn <= 0.0045f)
{
if(workload <= 278.7000f)
{
return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 8, 0, 0, 0, 1, 1);
}
else
{
return configure_lhs_rhs_info(m, n, 1, 4, 8, 1, 32, 0, 0, 1, 0, 0);
}
}
else
{
return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 8, 0, 0, 1, 0, 0);
}
}
else
{
if(workload <= 1384.8000f)
{
if(r_nk <= 0.8333f)
{
if(r_mk <= 0.9119f)
{
return configure_lhs_rhs_info(m, n, 2, 2, 16, 1, 4, 0, 1, 0, 1, 1);
}
else
{
if(r_nk <= 0.1181f)
{
return configure_lhs_rhs_info(m, n, 2, 2, 8, 1, 32, 0, 0, 1, 0, 0);
}
else
{
return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0);
}
}
}
else
{
if(r_mk <= 1.0013f)
{
return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 1);
}
else
{
return configure_lhs_rhs_info(m, n, 5, 4, 8, 1, 4, 0, 1, 1, 0, 1);
}
}
}
else
{
if(workload <= 11404.7998f)
{
if(r_mk <= 2.2884f)
{
if(r_nk <= 0.9286f)
{
return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 4, 0, 1, 1, 0, 1);
}
else
{
return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 1);
}
}
else
{
return configure_lhs_rhs_info(m, n, 5, 4, 8, 1, 4, 0, 1, 1, 0, 1);
}
}
else
{
if(r_nk <= 1.1926f)
{
if(r_mn <= 1385.7917f)
{
return configure_lhs_rhs_info(m, n, 6, 4, 8, 1, 4, 0, 1, 1, 0, 1);
}
else
{
return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 32, 0, 1, 1, 0, 0);
}
}
else
{
return configure_lhs_rhs_info(m, n, 6, 4, 8, 1, 32, 0, 1, 1, 0, 1);
}
}
}
}
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G715_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
{
unsigned int best_m0;
unsigned int best_n0;
if(is_mmul_kernel_preferred(m, n, k, b, DataType::F32, best_m0, best_n0))
{
return configure_lhs_rhs_info(m, n, best_m0, best_n0, 1, 1, 4, false, true, false, false, true);
}
else
{
return configure_G77_f32(m, n, k, b);
}
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G710_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
{
const GeMMConfigsMatrix configs_1nkb_best =
{
{ 1, 8984, 640, 1, 1, 2, 2, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 420, 392, 1, 1, 2, 8, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 644, 5288, 1, 1, 2, 8, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 6512, 6404, 1, 1, 2, 4, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 5304, 640, 1, 1, 2, 4, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 1352, 1520, 1, 1, 2, 4, 1, 0, 1, 0, 1, 0, 0 },
{ 1, 4096, 25088, 1, 1, 2, 8, 1, 0, 1, 0, 1, 1, 0 },
{ 1, 732, 8988, 1, 1, 2, 8, 1, 0, 1, 0, 1, 0, 0 }
};
const GeMMConfigsMatrix configs_mnkb_n_small_best =
{
{ 102400, 4, 96, 1, 1, 2, 16, 1, 0, 1, 0, 1, 0, 0 },
{ 102400, 2, 96, 1, 1, 2, 16, 1, 0, 1, 0, 1, 0, 0 },
{ 16384, 4, 128, 1, 1, 2, 16, 1, 0, 1, 0, 1, 0, 0 },
{ 16384, 2, 128, 1, 1, 2, 16, 1, 0, 1, 0, 1, 0, 0 }
};
const GeMMConfigsMatrix configs_mnkb_m_gt_n_best =
{
{ 25584, 88, 16, 1, 4, 8, 4, 1, 4, 1, 1, 1, 0, 0 },
{ 25584, 16, 68, 1, 2, 4, 16, 1, 8, 1, 1, 1, 0, 1 },
{ 369664, 32, 28, 1, 2, 8, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 65792, 44, 24, 1, 4, 8, 4, 1, 8, 1, 1, 1, 0, 0 },
{ 23036, 56, 736, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 90968, 40, 600, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 8944, 32, 776, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 2688, 136, 1492, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 50176, 64, 300, 1, 4, 8, 4, 1, 8, 1, 1, 1, 0, 1 },
{ 16544, 104, 160, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 12604, 60, 160, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 3728, 96, 196, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 29584, 32, 28, 1, 2, 8, 4, 1, 16, 1, 1, 1, 0, 0 },
{ 12544, 32, 27, 1, 2, 8, 8, 1, 16, 1, 1, 1, 0, 0 },
};
const GeMMConfigsMatrix configs_mnkb_m_gt_n_fallback =
{
{ 25584, 88, 16, 1, 4, 8, 4, 1, 4, 1, 1, 1, 0, 0 },
{ 25584, 16, 68, 1, 2, 4, 8, 1, 4, 1, 1, 1, 1, 0 },
{ 369664, 32, 28, 1, 2, 8, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 65792, 44, 24, 1, 4, 8, 4, 1, 8, 1, 1, 1, 0, 0 },
{ 23036, 56, 736, 1, 4, 8, 4, 1, 16, 1, 1, 1, 0, 0 },
{ 90968, 40, 600, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 0 },
{ 8944, 32, 776, 1, 2, 8, 8, 1, 16, 1, 1, 1, 0, 0 },
{ 2688, 136, 1492, 1, 4, 4, 8, 1, 8, 1, 1, 1, 0, 0 },
{ 50176, 64, 300, 1, 4, 8, 4, 1, 128, 1, 1, 1, 0, 0 },
{ 16544, 104, 160, 1, 4, 8, 4, 1, 16, 1, 1, 1, 0, 0 },
{ 12604, 60, 160, 1, 2, 8, 8, 1, 8, 1, 1, 1, 0, 0 },
{ 3728, 96, 196, 1, 2, 8, 8, 1, 64, 1, 1, 1, 0, 0 },
{ 29584, 32, 28, 1, 2, 8, 4, 1, 16, 1, 1, 1, 0, 0 },
{ 12544, 32, 27, 1, 2, 8, 8, 1, 16, 1, 1, 1, 0, 0 },
};
const GeMMConfigsMatrix configs_mnkb_n_gt_m_best =
{
{ 24, 488, 88, 1, 2, 2, 8, 1, 8, 1, 1, 1, 1, 0 },
{ 49, 1024, 512, 1, 2, 4, 8, 1, 8, 1, 1, 1, 1, 0 },
{ 49, 1024, 1024, 1, 2, 4, 8, 1, 4, 1, 1, 1, 1, 0 }
};
const GeMMConfigsMatrix configs_mnkb_n_gt_m_fallback =
{
{ 24, 488, 88, 1, 2, 2, 8, 1, 8, 1, 1, 1, 1, 0 },
{ 49, 1024, 512, 1, 2, 4, 8, 1, 8, 1, 1, 1, 1, 0 },
{ 49, 1024, 1024, 1, 2, 4, 8, 1, 4, 1, 1, 1, 1, 0 }
};
const GeMMConfigsMatrix configs_mnkb_squared_best =
{
{ 24, 88, 236, 1, 2, 2, 8, 1, 4, 1, 1, 1, 1, 0 },
{ 24, 88, 488, 1, 2, 2, 8, 1, 4, 1, 1, 1, 1, 0 },
{ 72, 92, 136, 1, 2, 2, 8, 1, 32, 1, 1, 1, 1, 0 },
{ 268, 824, 5076, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 180, 420, 952, 1, 4, 4, 8, 1, 16, 1, 1, 1, 0, 1 },
{ 1000, 152, 304, 1, 4, 8, 4, 1, 32, 1, 1, 1, 0, 0 },
{ 272, 400, 2116, 1, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 196, 512, 512, 1, 5, 2, 8, 1, 4, 1, 1, 1, 1, 1 },
};
const GeMMConfigsMatrix configs_mnkb_squared_fallback =
{
{ 24, 88, 236, 1, 2, 2, 8, 1, 4, 1, 1, 1, 1, 0 },
{ 24, 88, 488, 1, 2, 2, 8, 1, 4, 1, 1, 1, 1, 0 },
{ 72, 92, 136, 1, 2, 2, 8, 1, 32, 1, 1, 1, 1, 0 },
{ 268, 824, 5076, 1, 4, 8, 4, 1, 8, 1, 1, 1, 0, 0 },
{ 180, 420, 952, 1, 5, 2, 8, 1, 8, 1, 1, 1, 1, 0 },
{ 1000, 152, 304, 1, 4, 8, 4, 1, 32, 1, 1, 1, 0, 0 },
{ 272, 400, 2116, 1, 2, 8, 4, 1, 4, 1, 1, 1, 0, 0 },
{ 196, 512, 512, 1, 5, 2, 8, 1, 8, 1, 1, 1, 1, 0 },
};
const GeMMConfigsMatrix configs_mnkb_best_batched =
{
{ 3136, 64, 64, 36, 4, 8, 4, 1, 16, 1, 1, 1, 0, 1 },
{ 4096, 48, 32, 36, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 688, 92, 68, 32, 4, 8, 4, 1, 32, 1, 1, 1, 0, 1 },
{ 24, 464, 412, 24, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 112, 184, 144, 28, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 5776, 64, 32, 36, 4, 4, 8, 1, 4, 1, 1, 1, 0, 1 },
{ 1568, 64, 40, 36, 4, 8, 4, 1, 8, 1, 1, 1, 0, 1 },
{ 2920, 64, 64, 24, 4, 8, 4, 1, 8, 1, 1, 1, 0, 1 }
};
const GeMMConfigsMatrix configs_mnkb_fallback_batched =
{
{ 3136, 64, 64, 36, 4, 8, 4, 1, 8, 1, 1, 1, 0, 0 },
{ 4096, 48, 32, 36, 4, 4, 8, 1, 64, 1, 1, 1, 0, 0 },
{ 688, 92, 68, 32, 4, 8, 4, 1, 32, 1, 1, 1, 0, 0 },
{ 24, 464, 412, 24, 2, 8, 4, 1, 32, 1, 1, 1, 0, 0 },
{ 112, 184, 144, 28, 4, 4, 8, 1, 8, 1, 1, 1, 0, 0 },
{ 5776, 64, 32, 36, 2, 8, 8, 1, 32, 1, 1, 1, 0, 0 },
{ 1568, 64, 40, 36, 4, 8, 4, 1, 16, 1, 1, 1, 0, 0 },
{ 2920, 64, 64, 24, 4, 8, 4, 1, 8, 1, 1, 1, 0, 0 }
};
const GeMMConfigsMatrix *configs_best_to_use = nullptr;
const GeMMConfigsMatrix *configs_fallback_to_use = nullptr;
if(b == 1)
{
constexpr float ratio_m_gt_n = 10.f;
constexpr float ratio_n_gt_m = 0.1f;
constexpr unsigned int n_small_thr = 4;
const float ratio = static_cast<float>(m) / static_cast<float>(n);
if(m == 1)
{
// We do not need fallback in this case, as we never use cl_image for the rhs tensor
configs_best_to_use = &configs_1nkb_best;
configs_fallback_to_use = &configs_1nkb_best;
}
else if(n <= n_small_thr && ratio > ratio_m_gt_n)
{
configs_best_to_use = &configs_mnkb_n_small_best;
configs_fallback_to_use = &configs_mnkb_n_small_best;
}
else if(ratio > ratio_m_gt_n)
{
configs_best_to_use = &configs_mnkb_m_gt_n_best;
configs_fallback_to_use = &configs_mnkb_m_gt_n_fallback;
}
else if(ratio < ratio_n_gt_m)
{
configs_best_to_use = &configs_mnkb_n_gt_m_best;
configs_fallback_to_use = &configs_mnkb_n_gt_m_fallback;
}
else
{
configs_best_to_use = &configs_mnkb_squared_best;
configs_fallback_to_use = &configs_mnkb_squared_fallback;
}
}
else
{
configs_best_to_use = &configs_mnkb_best_batched;
configs_fallback_to_use = &configs_mnkb_fallback_batched;
}
GEMMLHSMatrixInfo lhs_info0;
GEMMRHSMatrixInfo rhs_info0;
GEMMLHSMatrixInfo lhs_info1;
GEMMRHSMatrixInfo rhs_info1;
std::tie(lhs_info0, rhs_info0) = find_lhs_rhs_info(*configs_best_to_use, m, n, k, b);
std::tie(lhs_info1, rhs_info1) = find_lhs_rhs_info(*configs_fallback_to_use, m, n, k, b);
return select_lhs_rhs_info(std::make_pair(lhs_info0, rhs_info0),
std::make_pair(lhs_info1, rhs_info1),
n, k, b, DataType::F16);
}
std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G715_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
{
unsigned int best_m0;
unsigned int best_n0;
if(is_mmul_kernel_preferred(m, n, k, b, DataType::F16, best_m0, best_n0))
{
return configure_lhs_rhs_info(m, n, best_m0, best_n0, 1, 1, 4, false, true, false, false, true);
}
else
{
return configure_G78_f16(m, n, k, b);
}
}
} // namespace gemm
} // namespace kernels
} // namespace opencl
} // namespace arm_compute