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Commit 1ad95e66 authored by Paul's avatar Paul
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parent bb666690
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Showing with 93 additions and 95 deletions
src/targets/gpu/device/include/migraph/gpu/device/nary.hpp
View file @ 1ad95e66
......@@ -51,69 +51,74 @@ auto nary_nonstandard_impl(F f, argument result, Arguments... args)
});
}
template<class F>
void binary_broadcast_vec_impl(F f, const argument& result, const argument& arg1, const argument& arg2)
template <class F>
void binary_broadcast_vec_impl(F f,
const argument& result,
const argument& arg1,
const argument& arg2)
{
const auto& output_shape = result.get_shape();
const auto& b_shape = arg2.get_shape();
auto bdim = std::distance(b_shape.strides().begin(),
std::find_if(b_shape.strides().begin(),
b_shape.strides().end(),
[](auto x) { return x != 0; }));
auto bdim_len = output_shape.lens()[bdim];
auto bdim_stride = output_shape.strides()[bdim];
auto bdim_next_stride = bdim_stride * bdim_len;
const auto& output_shape = result.get_shape();
const auto& b_shape = arg2.get_shape();
auto bdim =
std::distance(b_shape.strides().begin(),
std::find_if(b_shape.strides().begin(), b_shape.strides().end(), [](auto x) {
return x != 0;
}));
auto bdim_len = output_shape.lens()[bdim];
auto bdim_stride = output_shape.strides()[bdim];
auto bdim_next_stride = bdim_stride * bdim_len;
visit_all(result, arg1, arg2)([&](auto output, auto input1, auto input2) {
using type = std::remove_cv_t<typename decltype(output)::value_type>;
auto* xp = as_vec4(input1.data());
auto* yp = as_vec4(input2.data());
auto* outp = as_vec4(output.data());
visit_all(result, arg1, arg2)([&](auto output, auto input1, auto input2) {
using type = std::remove_cv_t<typename decltype(output)::value_type>;
auto* xp = as_vec4(input1.data());
auto* yp = as_vec4(input2.data());
auto* outp = as_vec4(output.data());
const std::size_t vec_size = 4;
const std::size_t nlocal = 1024;
const std::size_t nglobal = 256 * nlocal;
const std::size_t n = output.size() / vec_size;
const std::size_t bdim_vec_len = bdim_len / vec_size;
const std::size_t vec_size = 4;
const std::size_t nlocal = 1024;
const std::size_t nglobal = 256 * nlocal;
const std::size_t n = output.size() / vec_size;
const std::size_t bdim_vec_len = bdim_len / vec_size;
launch(nglobal, nlocal)([=](auto idx) __device__ {
MIGRAPH_DEVICE_SHARED vec4<type> buffer[2048 / vec_size];
// Load bias into LDS
for(size_t i = idx.local; i < bdim_vec_len; i += nlocal)
{
buffer[i] = yp[i];
}
__syncthreads();
auto* bp = as_pointer(buffer);
// Process the data
for(size_t i = idx.global; i < n; i += nglobal)
launch(nglobal, nlocal)([=](auto idx) __device__ {
MIGRAPH_DEVICE_SHARED vec4<type> buffer[2048 / vec_size];
// Load bias into LDS
for(size_t i = idx.local; i < bdim_vec_len; i += nlocal)
{
buffer[i] = yp[i];
}
__syncthreads();
auto* bp = as_pointer(buffer);
// Process the data
for(size_t i = idx.global; i < n; i += nglobal)
{
auto bidx = ((i * vec_size) % bdim_next_stride) / bdim_stride;
auto b = bp[bidx];
vec4<type> x = xp[i];
vec4<type> out = outp[i];
for(std::size_t j = 0; j < vec_size; j++)
{
auto bidx = ((i * vec_size) % bdim_next_stride) / bdim_stride;
auto b = bp[bidx];
vec4<type> x = xp[i];
vec4<type> out = outp[i];
for(std::size_t j = 0; j < vec_size; j++)
{
out[j] = f(x[j], b);
}
outp[i] = out;
out[j] = f(x[j], b);
}
});
outp[i] = out;
}
});
});
}
template<class F>
template <class F>
void binary_broadcast_impl(F f, const argument& result, const argument& arg1, const argument& arg2)
{
const auto& output_shape = result.get_shape();
const auto& b_shape = arg2.get_shape();
auto bdim = std::distance(b_shape.strides().begin(),
std::find_if(b_shape.strides().begin(),
b_shape.strides().end(),
[](auto x) { return x != 0; }));
auto bdim_len = output_shape.lens()[bdim];
auto bdim_stride = output_shape.strides()[bdim];
auto bdim_next_stride = bdim_stride * bdim_len;
auto bdim =
std::distance(b_shape.strides().begin(),
std::find_if(b_shape.strides().begin(), b_shape.strides().end(), [](auto x) {
return x != 0;
}));
auto bdim_len = output_shape.lens()[bdim];
auto bdim_stride = output_shape.strides()[bdim];
auto bdim_next_stride = bdim_stride * bdim_len;
visit_all(result, arg1, arg2)([&](auto output, auto input1, auto input2) {
using type = std::remove_cv_t<typename decltype(output)::value_type>;
......@@ -148,77 +153,70 @@ void binary_broadcast_impl(F f, const argument& result, const argument& arg1, co
template <class F, class... Arguments>
void nary_standard_vec_impl(F f, argument result, Arguments... args)
{
// assert(x.get_shape().elements() == y.get_shape().elements());
const auto& output_shape = result.get_shape();
visit_all(result, args...)([&](auto output, auto... inputs) {
using type = std::remove_cv_t<typename decltype(output)::value_type>;
const std::size_t vec_size = 4;
auto data = pack_vec4(inputs.data()...);
auto* outp = as_vec4(output.data());
gs_launch(output_shape.elements() / vec_size)([=](auto i) {
vec4<type> out = outp[i];
data(
[&](auto... xs) {
for(std::size_t j = 0; j < vec_size; j++)
{
out[j] = f(xs[j]...);
}
},
i);
outp[i] = out;
});
// assert(x.get_shape().elements() == y.get_shape().elements());
const auto& output_shape = result.get_shape();
visit_all(result, args...)([&](auto output, auto... inputs) {
using type = std::remove_cv_t<typename decltype(output)::value_type>;
const std::size_t vec_size = 4;
auto data = pack_vec4(inputs.data()...);
auto* outp = as_vec4(output.data());
gs_launch(output_shape.elements() / vec_size)([=](auto i) {
vec4<type> out = outp[i];
data(
[&](auto... xs) {
for(std::size_t j = 0; j < vec_size; j++)
{
out[j] = f(xs[j]...);
}
},
i);
outp[i] = out;
});
});
}
template <class F, class... Arguments>
void nary_standard_impl(F f, argument result, Arguments... args)
{
// assert(x.get_shape().elements() == y.get_shape().elements());
const auto& output_shape = result.get_shape();
visit_all(result, args...)([&](auto output, auto... inputs) {
auto data = pack(inputs.data()...);
auto* outp = output.data();
gs_launch(output_shape.elements())(
[=](auto i) { data([&](auto... xps) { outp[i] = f(xps[i]...); }); });
});
// assert(x.get_shape().elements() == y.get_shape().elements());
const auto& output_shape = result.get_shape();
visit_all(result, args...)([&](auto output, auto... inputs) {
auto data = pack(inputs.data()...);
auto* outp = output.data();
gs_launch(output_shape.elements())(
[=](auto i) { data([&](auto... xps) { outp[i] = f(xps[i]...); }); });
});
}
template <class F, class... Arguments>
void nary_impl(F f, argument result, Arguments... args)
{
bool standard = all_of({args.get_shape()...}, [](const shape& s) { return s.standard(); });
bool packed = all_of({args.get_shape()...}, [](const shape& s) { return s.packed(); });
bool same_shapes =
all_of({args.get_shape()...}, [&](const shape& s) { return s == result.get_shape(); });
if(standard or (packed and same_shapes))
nary_standard_impl(f, result, args...);
else
nary_nonstandard_impl(f, result, args...);
bool standard = all_of({args.get_shape()...}, [](const shape& s) { return s.standard(); });
bool packed = all_of({args.get_shape()...}, [](const shape& s) { return s.packed(); });
bool same_shapes =
all_of({args.get_shape()...}, [&](const shape& s) { return s == result.get_shape(); });
if(standard or (packed and same_shapes))
nary_standard_impl(f, result, args...);
else
nary_nonstandard_impl(f, result, args...);
}
template <class... Arguments>
auto nary_nonstandard(argument result, Arguments... args)
{
return [=](auto f) {
nary_nonstandard_impl(f, result, args...);
};
return [=](auto f) { nary_nonstandard_impl(f, result, args...); };
}
template <class... Arguments>
auto nary_standard(argument result, Arguments... args)
{
return [=](auto f) {
nary_standard_impl(f, result, args...);
};
return [=](auto f) { nary_standard_impl(f, result, args...); };
}
template <class... Arguments>
auto nary(argument result, Arguments... args)
{
return [=](auto f) {
nary_impl(f, result, args...);
};
return [=](auto f) { nary_impl(f, result, args...); };
}
inline auto nary(const argument& result, const argument& arg1, const argument& arg2)
......
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