ROCm/composable_kernel
1
0
Fork 0
mirror of https://github.com/ROCm/composable_kernel.git synced 2026-05-12 01:10:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

adding int8 direct that reads pre-vectorized data

Browse Source
This commit is contained in:
Chao Liu
2019-03-19 00:05:41 -05:00
parent 18ffbd6802
commit 050a1a6890
6 changed files with 247 additions and 95 deletions
Download Patch File Download Diff File Expand all files Collapse all files

65
driver/driver.hip.cpp
View File

@@ -88,9 +88,12 @@ auto make_TensorDescriptor(TConstTensorDesc)
return TensorDescriptor(lengths, strides);
}
template <class T, class LowerPads, class UpperPads>
void host_direct_convolution(
const Tensor<T>& in_nchw, const Tensor<T>& wei_kcyx, Tensor<T>& out, LowerPads, UpperPads)
template <class TIn, class TWei, class TOut, class LowerPads, class UpperPads>
void host_direct_convolution(const Tensor<TIn>& in_nchw,
const Tensor<TWei>& wei_kcyx,
Tensor<TOut>& out_nkhw,
LowerPads,
UpperPads)
{
unsigned h_pad_low = LowerPads{}.Get(Number<0>{});
unsigned w_pad_low = LowerPads{}.Get(Number<1>{});
@@ -116,21 +119,24 @@ void host_direct_convolution(
}
}
}
out(n, k, ho, wo) = v;
out_nkhw(n, k, ho, wo) = v;
};
auto f_par = make_ParallelTensorFunctor(f,
out.mDesc.GetLengths()[0],
out.mDesc.GetLengths()[1],
out.mDesc.GetLengths()[2],
out.mDesc.GetLengths()[3]);
out_nkhw.mDesc.GetLengths()[0],
out_nkhw.mDesc.GetLengths()[1],
out_nkhw.mDesc.GetLengths()[2],
out_nkhw.mDesc.GetLengths()[3]);
f_par(std::thread::hardware_concurrency());
}
template <class T, class LowerPads, class UpperPads>
void host_winograd_3x3_convolution(
const Tensor<T>& in_nchw, const Tensor<T>& wei_kcyx, Tensor<T>& out, LowerPads, UpperPads)
template <class TIn, class TWei, class TOut, class LowerPads, class UpperPads>
void host_winograd_3x3_convolution(const Tensor<TIn>& in_nchw,
const Tensor<TWei>& wei_kcyx,
Tensor<TOut>& out_nkhw,
LowerPads,
UpperPads)
{
constexpr std::size_t HoPerTile = 2;
constexpr std::size_t WoPerTile = 2;
@@ -144,8 +150,8 @@ void host_winograd_3x3_convolution(
std::size_t Y = wei_kcyx.mDesc.GetLengths()[2];
std::size_t X = wei_kcyx.mDesc.GetLengths()[3];
std::size_t HO = out.mDesc.GetLengths()[2];
std::size_t WO = out.mDesc.GetLengths()[3];
std::size_t HO = out_nkhw.mDesc.GetLengths()[2];
std::size_t WO = out_nkhw.mDesc.GetLengths()[3];
unsigned h_pad_low = LowerPads{}.Get(Number<0>{});
unsigned w_pad_low = LowerPads{}.Get(Number<1>{});
@@ -180,7 +186,7 @@ void host_winograd_3x3_convolution(
}
else
{
in_hold(n, c, htile, wtile, j, i) = T(0);
in_hold(n, c, htile, wtile, j, i) = TIn(0);
}
}
}
@@ -347,8 +353,8 @@ void host_winograd_3x3_convolution(
std::size_t ho = HoPerTile * htile + j;
for(int i = 0; i < WoPerTile; ++i)
{
std::size_t wo = WoPerTile * wtile + i;
out(n, k, ho, wo) = out_hold(n, k, htile, wtile, j, i);
std::size_t wo = WoPerTile * wtile + i;
out_nkhw(n, k, ho, wo) = out_hold(n, k, htile, wtile, j, i);
}
}
};
@@ -403,7 +409,7 @@ int main(int argc, char* argv[])
constexpr unsigned HPad = 0;
constexpr unsigned WPad = 0;
#elif 1
#elif 0
// 3x3, 34x34
constexpr unsigned N = 64;
constexpr unsigned C = 256;
@@ -502,7 +508,7 @@ int main(int argc, char* argv[])
constexpr unsigned HPad = 1;
constexpr unsigned WPad = 1;
#elif 1
#elif 0
// 1x1 filter, 28x28 image
constexpr unsigned N = 16;
constexpr unsigned C = 256;
@@ -562,6 +568,18 @@ int main(int argc, char* argv[])
constexpr unsigned HPad = 2;
constexpr unsigned WPad = 2;
#elif 1
// 1x1 filter, 32x32 image
constexpr unsigned N = 64;
constexpr unsigned C = 256;
constexpr unsigned HI = 32;
constexpr unsigned WI = 32;
constexpr unsigned K = 512;
constexpr unsigned Y = 1;
constexpr unsigned X = 1;
constexpr unsigned HPad = 0;
constexpr unsigned WPad = 0;
#endif
auto lower_pads = Sequence<HPad, WPad>{};
@@ -576,11 +594,12 @@ int main(int argc, char* argv[])
ostream_ConstantTensorDescriptor(wei_kcyx_desc, std::cout << "wei_kcyx_desc: ");
ostream_ConstantTensorDescriptor(out_nkhw_desc, std::cout << "out_nkhw_desc: ");
using Float = float;
Tensor<Float> in_nchw(make_TensorDescriptor(in_nchw_desc));
Tensor<Float> wei_kcyx(make_TensorDescriptor(wei_kcyx_desc));
Tensor<Float> out_nkhw_host(make_TensorDescriptor(out_nkhw_desc));
Tensor<Float> out_nkhw_device(make_TensorDescriptor(out_nkhw_desc));
using in_data_t = char;
using out_data_t = int32_t;
Tensor<in_data_t> in_nchw(make_TensorDescriptor(in_nchw_desc));
Tensor<in_data_t> wei_kcyx(make_TensorDescriptor(wei_kcyx_desc));
Tensor<out_data_t> out_nkhw_host(make_TensorDescriptor(out_nkhw_desc));
Tensor<out_data_t> out_nkhw_device(make_TensorDescriptor(out_nkhw_desc));
std::size_t num_thread = std::thread::hardware_concurrency();