Skip to content

GitLab

Commit 1dd11890 authored by turneram's avatar turneram
Browse files

Formatting

parent 07167910
Hide whitespace changes
Inline Side-by-side
Showing with 308 additions and 269 deletions
src/targets/gpu/jit/ck_gemm.cpp
View file @ 1dd11890
......@@ -72,7 +72,6 @@ __global__ void ck_gemm_kernel(void* a_p, void* b_p, void* c_p)
)__migraphx__";
struct ck_gemm_compiler : compiler<ck_gemm_compiler>
{
std::vector<std::string> names() const { return {"ck_gemm"}; }
......
src/targets/gpu/kernels/include/migraphx/kernels/ck_elementwise.hpp
View file @ 1dd11890
......@@ -213,8 +213,8 @@ __device__ void ck_elementwise(const T& a_t, const U& b_t, const V& c_t)
AScalarPerVector,
BScalarPerVector,
CScalarPerVector>;
auto op = Add{};
auto op = Add{};
GridwiseBinEltwise::Run(a_t.data(), b_t.data(), c_t.data(), a_desc, b_desc, c_desc, op);
}
......
src/targets/gpu/kernels/include/migraphx/kernels/ck_elementwise2.hpp
View file @ 1dd11890
......@@ -164,12 +164,12 @@ struct Div
};
};
using InDataTypeTuple = ck::Tuple<ABDataType, ABDataType>;
using OutDataTypeTuple = ck::Tuple<CDataType>;
using ElementwiseOperation = Add;
using InDataTypeTuple = ck::Tuple<ABDataType, ABDataType>;
using OutDataTypeTuple = ck::Tuple<CDataType>;
using ElementwiseOperation = Add;
static constexpr auto MPerThread = 8;
using InScalarPerVectorSeq = ck::Sequence<1, 8>;
using OutScalarPerVectorSeq = ck::Sequence<8>;
using InScalarPerVectorSeq = ck::Sequence<1, 8>;
using OutScalarPerVectorSeq = ck::Sequence<8>;
// using DeviceElementwiseAddInstance =
// ck::tensor_operation::device::DeviceElementwise<ck::Tuple<ABDataType, ABDataType>,
......@@ -186,7 +186,7 @@ __device__ void ck_elementwise(const T& a_t, const U& b_t, const V& c_t)
// auto idx = make_index();
constexpr auto a_lens = get_shape_c<T>{}.lens;
constexpr auto a_strides = get_shape_c<T>{}.strides;
constexpr ck::index_t ndim = a_lens.size();
constexpr ck::index_t ndim = a_lens.size();
constexpr auto b_lens = get_shape_c<U>{}.lens;
constexpr auto b_strides = get_shape_c<U>{}.strides;
constexpr ck::index_t b_ndim = b_lens.size();
......@@ -197,47 +197,46 @@ __device__ void ck_elementwise(const T& a_t, const U& b_t, const V& c_t)
using DeviceElementwiseAddInstance =
ck::tensor_operation::device::DeviceElementwise<ck::Tuple<ABDataType, ABDataType>,
ck::Tuple<CDataType>,
Add,
ndim,
8,
ck::Sequence<1, 8>,
ck::Sequence<8>>;
ck::Tuple<CDataType>,
Add,
ndim,
8,
ck::Sequence<1, 8>,
ck::Sequence<8>>;
using shapes_t = std::array<ck::index_t, 3>;
//shapes_t lengths_abc;
//copy(c_lens.begin(), c_lens.end(), lengths_abc);
// shapes_t lengths_abc;
// copy(c_lens.begin(), c_lens.end(), lengths_abc);
shapes_t lengths_abc = {c_lens[0], c_lens[1], c_lens[2]};
//constexpr auto lengths_abc = static_cast<shapes_t>(c_lens[0], c_lens[1], c_lens[2]);
// constexpr auto lengths_abc = static_cast<shapes_t>(c_lens[0], c_lens[1], c_lens[2]);
constexpr auto strides_a = static_cast<shapes_t>(a_strides);
constexpr auto strides_b = static_cast<shapes_t>(b_strides);
constexpr auto strides_c = static_cast<shapes_t>(c_strides);
std::array<const void*, 2> input = {a_t.data(),
b_t.data()};
std::array<const void*, 2> input = {a_t.data(), b_t.data()};
std::array<void*, 1> output = {c_t.data()};
auto ck_add = DeviceElementwiseAddInstance{};
auto argument = ck_add.MakeArgumentPointer(
auto ck_add = DeviceElementwiseAddInstance{};
auto argument = ck_add.MakeArgumentPointer(
lengths_abc, {strides_a, strides_b}, {strides_c}, input, output, Add{});
using InGrid1dDescTuple = decltype(ck_add.GenerateInOutGrid1dDescTuple(ck::Number<ndim>{}));
using OutGrid1dDescTuple = decltype(ck_add.GenerateInOutGrid1dDescTuple(ck::Number<ndim>{}));
using InDataTypePointerTuple = decltype(ck_add.GenerateInDataTypePointerTuple());
using OutDataTypePointerTuple = decltype(ck_add.GenerateOutDataTypePointerTuple());
using GridwiseElementwise = ck::GridwiseElementwise_1D<InGrid1dDescTuple,
OutGrid1dDescTuple,
InDataTypePointerTuple,
OutDataTypePointerTuple,
ElementwiseOperation,
MPerThread,
InScalarPerVectorSeq,
OutScalarPerVectorSeq>;
using GridwiseElementwise = ck::GridwiseElementwise_1D<InGrid1dDescTuple,
OutGrid1dDescTuple,
InDataTypePointerTuple,
OutDataTypePointerTuple,
ElementwiseOperation,
MPerThread,
InScalarPerVectorSeq,
OutScalarPerVectorSeq>;
GridwiseElementwise::Run(argument.in_grid_1d_desc_tuple_,
argument.out_grid_1d_desc_tuple_,
argument.in_dev_buffers_,
argument.out_dev_buffers_,
argument.elementwise_op_);
argument.out_grid_1d_desc_tuple_,
argument.in_dev_buffers_,
argument.out_dev_buffers_,
argument.elementwise_op_);
}
} // namespace migraphx
......
src/targets/gpu/kernels/include/migraphx/kernels/ck_gemm.hpp
View file @ 1dd11890
......@@ -60,19 +60,27 @@ __device__ void ck_gemm(const T& a_t, const U& b_t, const V& c_t, const W& p_t)
if(idx.global == 0)
{
printf("a_grid_desc_k0_m0_m1_k1{%i, %i, %i}\n", int(a_grid_desc_k0_m_k1.GetLength(I0)), int(a_grid_desc_k0_m_k1.GetLength(I1)), int(a_grid_desc_k0_m_k1.GetLength(I2)));
printf("b_grid_desc_k0_n0_n1_k1{%i, %i, %i}\n", int(b_grid_desc_k0_n_k1.GetLength(I0)), int(b_grid_desc_k0_n_k1.GetLength(I1)), int(b_grid_desc_k0_n_k1.GetLength(I2)));
printf("c_grid_desc_m_n{%i, %i}\n", int(c_grid_desc_m_n.GetLength(I0)), int(c_grid_desc_m_n.GetLength(I1)));
printf("a_grid_desc_k0_m0_m1_k1{%i, %i, %i}\n",
int(a_grid_desc_k0_m_k1.GetLength(I0)),
int(a_grid_desc_k0_m_k1.GetLength(I1)),
int(a_grid_desc_k0_m_k1.GetLength(I2)));
printf("b_grid_desc_k0_n0_n1_k1{%i, %i, %i}\n",
int(b_grid_desc_k0_n_k1.GetLength(I0)),
int(b_grid_desc_k0_n_k1.GetLength(I1)),
int(b_grid_desc_k0_n_k1.GetLength(I2)));
printf("c_grid_desc_m_n{%i, %i}\n",
int(c_grid_desc_m_n.GetLength(I0)),
int(c_grid_desc_m_n.GetLength(I1)));
}
AGridDesc_K0_M0_M1_K1 a_grid_desc_k0_m0_m1_k1;
BGridDesc_K0_N0_N1_K1 b_grid_desc_k0_n0_n1_k1;
CGridDesc_M0_M10_M11_N0_N10_N11 c_grid_desc_m0_m10_m11_n0_n10_n11;
DefaultBlock2CTileMap block_2_ctile_map;
if(true or GridwiseGemm::CheckValidity(
a_grid_desc_k0_m_k1, b_grid_desc_k0_n_k1, c_grid_desc_m_n))
if(true or
GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1, b_grid_desc_k0_n_k1, c_grid_desc_m_n))
{
//printf("Is valid\n");
// printf("Is valid\n");
a_grid_desc_k0_m0_m1_k1 =
GridwiseGemm::MakeAGridDescriptor_K0_M0_M1_K1(a_grid_desc_k0_m_k1);
b_grid_desc_k0_n0_n1_k1 =
......@@ -83,79 +91,86 @@ __device__ void ck_gemm(const T& a_t, const U& b_t, const V& c_t, const W& p_t)
}
else
{
//printf("Not valid\n");
// printf("Not valid\n");
}
if(idx.global == 0)
{
printf("a_grid_desc_k0_m0_m1_k1{%i, %i, %i}\n", int(a_grid_desc_k0_m0_m1_k1.GetLength(I0)), int(a_grid_desc_k0_m0_m1_k1.GetLength(I1)), int(a_grid_desc_k0_m0_m1_k1.GetLength(I2)));
printf("b_grid_desc_k0_n0_n1_k1{%i, %i, %i}\n", int(b_grid_desc_k0_n0_n1_k1.GetLength(I0)), int(b_grid_desc_k0_n0_n1_k1.GetLength(I1)), int(b_grid_desc_k0_n0_n1_k1.GetLength(I2)));
printf("c_grid_desc_m0_m10_m11_n0_n10_n11{%i, %i}\n", int(c_grid_desc_m0_m10_m11_n0_n10_n11.GetLength(I0)), int(c_grid_desc_m0_m10_m11_n0_n10_n11.GetLength(I1)));
printf("a_grid_desc_k0_m0_m1_k1{%i, %i, %i}\n",
int(a_grid_desc_k0_m0_m1_k1.GetLength(I0)),
int(a_grid_desc_k0_m0_m1_k1.GetLength(I1)),
int(a_grid_desc_k0_m0_m1_k1.GetLength(I2)));
printf("b_grid_desc_k0_n0_n1_k1{%i, %i, %i}\n",
int(b_grid_desc_k0_n0_n1_k1.GetLength(I0)),
int(b_grid_desc_k0_n0_n1_k1.GetLength(I1)),
int(b_grid_desc_k0_n0_n1_k1.GetLength(I2)));
printf("c_grid_desc_m0_m10_m11_n0_n10_n11{%i, %i}\n",
int(c_grid_desc_m0_m10_m11_n0_n10_n11.GetLength(I0)),
int(c_grid_desc_m0_m10_m11_n0_n10_n11.GetLength(I1)));
}
const auto K0 = a_grid_desc_k0_m0_m1_k1.GetLength(I0);
const bool has_main_k_block_loop = GridwiseGemm::CalculateHasMainKBlockLoop(K0);
const bool has_double_tail_k_block_loop =
GridwiseGemm::CalculateHasDoubleTailKBlockLoop(K0);
const auto K0 = a_grid_desc_k0_m0_m1_k1.GetLength(I0);
const bool has_main_k_block_loop = GridwiseGemm::CalculateHasMainKBlockLoop(K0);
const bool has_double_tail_k_block_loop = GridwiseGemm::CalculateHasDoubleTailKBlockLoop(K0);
if(has_main_k_block_loop && has_double_tail_k_block_loop)
{
constexpr bool HasMainKBlockLoop = true;
constexpr bool HasMainKBlockLoop = true;
constexpr bool HasDoubleTailKBlockLoop = true;
GridwiseGemm::Run(a_t.data(),
b_t.data(),
c_t.data(),
p_t.data(),
a_grid_desc_k0_m0_m1_k1,
b_grid_desc_k0_n0_n1_k1,
c_grid_desc_m0_m10_m11_n0_n10_n11,
block_2_ctile_map,
ck::integral_constant<bool, HasMainKBlockLoop>{},
ck::integral_constant<bool, HasDoubleTailKBlockLoop>{});
b_t.data(),
c_t.data(),
p_t.data(),
a_grid_desc_k0_m0_m1_k1,
b_grid_desc_k0_n0_n1_k1,
c_grid_desc_m0_m10_m11_n0_n10_n11,
block_2_ctile_map,
ck::integral_constant<bool, HasMainKBlockLoop>{},
ck::integral_constant<bool, HasDoubleTailKBlockLoop>{});
}
else if(has_main_k_block_loop && !has_double_tail_k_block_loop)
{
constexpr bool HasMainKBlockLoop = true;
constexpr bool HasMainKBlockLoop = true;
constexpr bool HasDoubleTailKBlockLoop = false;
GridwiseGemm::Run(a_t.data(),
b_t.data(),
c_t.data(),
p_t.data(),
a_grid_desc_k0_m0_m1_k1,
b_grid_desc_k0_n0_n1_k1,
c_grid_desc_m0_m10_m11_n0_n10_n11,
block_2_ctile_map,
ck::integral_constant<bool, HasMainKBlockLoop>{},
ck::integral_constant<bool, HasDoubleTailKBlockLoop>{});
b_t.data(),
c_t.data(),
p_t.data(),
a_grid_desc_k0_m0_m1_k1,
b_grid_desc_k0_n0_n1_k1,
c_grid_desc_m0_m10_m11_n0_n10_n11,
block_2_ctile_map,
ck::integral_constant<bool, HasMainKBlockLoop>{},
ck::integral_constant<bool, HasDoubleTailKBlockLoop>{});
}
else if(!has_main_k_block_loop && has_double_tail_k_block_loop)
{
constexpr bool HasMainKBlockLoop = false;
constexpr bool HasMainKBlockLoop = false;
constexpr bool HasDoubleTailKBlockLoop = true;
GridwiseGemm::Run(a_t.data(),
b_t.data(),
c_t.data(),
p_t.data(),
a_grid_desc_k0_m0_m1_k1,
b_grid_desc_k0_n0_n1_k1,
c_grid_desc_m0_m10_m11_n0_n10_n11,
block_2_ctile_map,
ck::integral_constant<bool, HasMainKBlockLoop>{},
ck::integral_constant<bool, HasDoubleTailKBlockLoop>{});
b_t.data(),
c_t.data(),
p_t.data(),
a_grid_desc_k0_m0_m1_k1,
b_grid_desc_k0_n0_n1_k1,
c_grid_desc_m0_m10_m11_n0_n10_n11,
block_2_ctile_map,
ck::integral_constant<bool, HasMainKBlockLoop>{},
ck::integral_constant<bool, HasDoubleTailKBlockLoop>{});
}
else
else
{
constexpr bool HasMainKBlockLoop = false;
constexpr bool HasMainKBlockLoop = false;
constexpr bool HasDoubleTailKBlockLoop = false;
GridwiseGemm::Run(a_t.data(),
b_t.data(),
c_t.data(),
p_t.data(),
a_grid_desc_k0_m0_m1_k1,
b_grid_desc_k0_n0_n1_k1,
c_grid_desc_m0_m10_m11_n0_n10_n11,
block_2_ctile_map,
ck::integral_constant<bool, HasMainKBlockLoop>{},
ck::integral_constant<bool, HasDoubleTailKBlockLoop>{});
b_t.data(),
c_t.data(),
p_t.data(),
a_grid_desc_k0_m0_m1_k1,
b_grid_desc_k0_n0_n1_k1,
c_grid_desc_m0_m10_m11_n0_n10_n11,
block_2_ctile_map,
ck::integral_constant<bool, HasMainKBlockLoop>{},
ck::integral_constant<bool, HasDoubleTailKBlockLoop>{});
}
}
......
src/targets/gpu/kernels/include/migraphx/kernels/ck_gemm2.hpp
View file @ 1dd11890
......@@ -37,7 +37,7 @@ template <class T, class U, class V, class W>
__device__ void ck_gemm(const T& a_t, const U& b_t, const V& c_t, const W& p_t)
{
static gemm tp{};
using GridwiseGemm = decltype(tp.gg);
using GridwiseGemm = decltype(tp.gg);
constexpr auto alens = get_shape_c<T>{}.lens;
constexpr auto m = alens[0];
constexpr auto k = alens[1];
......@@ -53,38 +53,51 @@ __device__ void ck_gemm(const T& a_t, const U& b_t, const V& c_t, const W& p_t)
if(idx.global == 0)
printf("%i %i %i, %i %i %i\n", int(m), int(n), int(k), int(as), int(bs), int(cs));
constexpr auto a_grid_desc_ak0_m_ak1 = tp.MakeAGridDescriptor_AK0_M_AK1(static_cast<ck::index_t>(m), static_cast<ck::index_t>(k), static_cast<ck::index_t>(as));
constexpr auto b_grid_desc_bk0_n_bk1 = tp.MakeBGridDescriptor_BK0_N_BK1(static_cast<ck::index_t>(k), static_cast<ck::index_t>(n), static_cast<ck::index_t>(bs));
constexpr auto c_grid_desc_m_n = tp.MakeCGridDescriptor_M_N(static_cast<ck::index_t>(m), static_cast<ck::index_t>(n), static_cast<ck::index_t>(cs));
constexpr auto a_grid_desc_ak0_m_ak1 = tp.MakeAGridDescriptor_AK0_M_AK1(
static_cast<ck::index_t>(m), static_cast<ck::index_t>(k), static_cast<ck::index_t>(as));
constexpr auto b_grid_desc_bk0_n_bk1 = tp.MakeBGridDescriptor_BK0_N_BK1(
static_cast<ck::index_t>(k), static_cast<ck::index_t>(n), static_cast<ck::index_t>(bs));
constexpr auto c_grid_desc_m_n = tp.MakeCGridDescriptor_M_N(
static_cast<ck::index_t>(m), static_cast<ck::index_t>(n), static_cast<ck::index_t>(cs));
/* constexpr */ auto block_2_ctile_map = tp.MakeDefaultBlock2CTileMap(c_grid_desc_m_n);
if(idx.global == 0)
{
printf("a_grid_desc_ak0_m_ak1{%i, %i, %i}\n", int(a_grid_desc_ak0_m_ak1.GetLength(I0)), int(a_grid_desc_ak0_m_ak1.GetLength(I1)), int(a_grid_desc_ak0_m_ak1.GetLength(I2)));
printf("b_grid_desc_bk0_n_bk1{%i, %i, %i}\n", int(b_grid_desc_bk0_n_bk1.GetLength(I0)), int(b_grid_desc_bk0_n_bk1.GetLength(I1)), int(b_grid_desc_bk0_n_bk1.GetLength(I2)));
printf("c_grid_desc_m_n{%i, %i}\n", int(c_grid_desc_m_n.GetLength(I0)), int(c_grid_desc_m_n.GetLength(I1)));
printf("a_grid_desc_ak0_m_ak1{%i, %i, %i}\n",
int(a_grid_desc_ak0_m_ak1.GetLength(I0)),
int(a_grid_desc_ak0_m_ak1.GetLength(I1)),
int(a_grid_desc_ak0_m_ak1.GetLength(I2)));
printf("b_grid_desc_bk0_n_bk1{%i, %i, %i}\n",
int(b_grid_desc_bk0_n_bk1.GetLength(I0)),
int(b_grid_desc_bk0_n_bk1.GetLength(I1)),
int(b_grid_desc_bk0_n_bk1.GetLength(I2)));
printf("c_grid_desc_m_n{%i, %i}\n",
int(c_grid_desc_m_n.GetLength(I0)),
int(c_grid_desc_m_n.GetLength(I1)));
}
GridwiseGemm::CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
c_grid_desc_mblock_mperblock_nblock_nperblock{};
if(true or GridwiseGemm::CheckValidity(a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
c_grid_desc_m_n,
block_2_ctile_map))
c_grid_desc_mblock_mperblock_nblock_nperblock{};
if(true or
GridwiseGemm::CheckValidity(
a_grid_desc_ak0_m_ak1, b_grid_desc_bk0_n_bk1, c_grid_desc_m_n, block_2_ctile_map))
{
c_grid_desc_mblock_mperblock_nblock_nperblock =
GridwiseGemm::MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
c_grid_desc_m_n);
GridwiseGemm::MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(c_grid_desc_m_n);
}
// if(idx.global == 0)
// {
// printf("a_grid_desc_k0_m0_m1_k1{%i, %i, %i}\n", int(a_grid_desc_k0_m0_m1_k1.GetLength(I0)), int(a_grid_desc_k0_m0_m1_k1.GetLength(I1)), int(a_grid_desc_k0_m0_m1_k1.GetLength(I2)));
// printf("b_grid_desc_k0_n0_n1_k1{%i, %i, %i}\n", int(b_grid_desc_k0_n0_n1_k1.GetLength(I0)), int(b_grid_desc_k0_n0_n1_k1.GetLength(I1)), int(b_grid_desc_k0_n0_n1_k1.GetLength(I2)));
// printf("c_grid_desc_m0_m10_m11_n0_n10_n11{%i, %i}\n", int(c_grid_desc_m0_m10_m11_n0_n10_n11.GetLength(I0)), int(c_grid_desc_m0_m10_m11_n0_n10_n11.GetLength(I1)));
// printf("a_grid_desc_k0_m0_m1_k1{%i, %i, %i}\n",
// int(a_grid_desc_k0_m0_m1_k1.GetLength(I0)), int(a_grid_desc_k0_m0_m1_k1.GetLength(I1)),
// int(a_grid_desc_k0_m0_m1_k1.GetLength(I2))); printf("b_grid_desc_k0_n0_n1_k1{%i, %i,
// %i}\n", int(b_grid_desc_k0_n0_n1_k1.GetLength(I0)),
// int(b_grid_desc_k0_n0_n1_k1.GetLength(I1)), int(b_grid_desc_k0_n0_n1_k1.GetLength(I2)));
// printf("c_grid_desc_m0_m10_m11_n0_n10_n11{%i, %i}\n",
// int(c_grid_desc_m0_m10_m11_n0_n10_n11.GetLength(I0)),
// int(c_grid_desc_m0_m10_m11_n0_n10_n11.GetLength(I1)));
// }
const auto K =
a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2);
const auto K = a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2);
auto a_element_op = tp.a_element_op;
auto b_element_op = tp.b_element_op;
auto c_element_op = tp.c_element_op;
......@@ -93,31 +106,31 @@ __device__ void ck_gemm(const T& a_t, const U& b_t, const V& c_t, const W& p_t)
{
constexpr bool HasMainKBlockLoop = true;
GridwiseGemm::template Run<HasMainKBlockLoop>(a_t.data(),
b_t.data(),
c_t.data(),
p_t.data(),
a_element_op,
b_element_op,
c_element_op,
a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
c_grid_desc_mblock_mperblock_nblock_nperblock,
block_2_ctile_map);
b_t.data(),
c_t.data(),
p_t.data(),
a_element_op,
b_element_op,
c_element_op,
a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
c_grid_desc_mblock_mperblock_nblock_nperblock,
block_2_ctile_map);
}
else
else
{
constexpr bool HasMainKBlockLoop = false;
GridwiseGemm::template Run<HasMainKBlockLoop>(a_t.data(),
b_t.data(),
c_t.data(),
p_t.data(),
a_element_op,
b_element_op,
c_element_op,
a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
c_grid_desc_mblock_mperblock_nblock_nperblock,
block_2_ctile_map);
b_t.data(),
c_t.data(),
p_t.data(),
a_element_op,
b_element_op,
c_element_op,
a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
c_grid_desc_mblock_mperblock_nblock_nperblock,
block_2_ctile_map);
}
}
......
src/targets/gpu/kernels/include/migraphx/kernels/ck_gemm_includes.hpp
View file @ 1dd11890
......@@ -51,8 +51,8 @@ static constexpr auto I5 = ck::Number<5>{};
static constexpr ck::index_t K1 = 1;
static constexpr auto K1Number = ck::Number<K1>{};
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
// using ALayout = Row;
// using BLayout = Row;
// using CLayout = Row;
......@@ -86,7 +86,7 @@ using S = ck::Sequence<Is...>;
// static constexpr ck::index_t NPerBlock = 128;
// static constexpr ck::index_t KPerBlock = 32;
// static constexpr ck::index_t AK1 = 8;
// static constexpr ck::index_t BK1 = 2;
// static constexpr ck::index_t BK1 = 2;
// static constexpr ck::index_t MPerXDL = 32;
// static constexpr ck::index_t NPerXDL = 32;
// static constexpr ck::index_t MXdlPerWave = 4;
......@@ -126,7 +126,8 @@ struct BlockToCTileMap_M00_N0_M01Adapt
{
}
__host__ __device__ constexpr ck::index_t CalculateGridSize(const CGridDesc_M_N& c_grid_desc_m_n) const
__host__ __device__ constexpr ck::index_t
CalculateGridSize(const CGridDesc_M_N& c_grid_desc_m_n) const
{
const auto M0 = ck::math::integer_divide_ceil(c_grid_desc_m_n.GetLength(I0), MPerBlock);
const auto N0 = ck::math::integer_divide_ceil(c_grid_desc_m_n.GetLength(I1), NPerBlock);
......@@ -156,7 +157,7 @@ struct BlockToCTileMap_M00_N0_M01Adapt
ck::index_t idx_N0_M01_local = idx_N0 + idx_M01 * N0;
return ck::make_tuple(idx_N0_M01_local % M01_adapt + idx_M00 * M01_,
idx_N0_M01_local / M01_adapt);
idx_N0_M01_local / M01_adapt);
}
template <typename CTileIdx, typename CTileDim>
......@@ -166,7 +167,10 @@ struct BlockToCTileMap_M00_N0_M01Adapt
return true; // always valid provided that user gets grid size from CalculateGridSize()
}
__host__ __device__ bool CheckValidity(const CGridDesc_M_N& /* c_grid_desc_m_n */) const { return true; }
__host__ __device__ bool CheckValidity(const CGridDesc_M_N& /* c_grid_desc_m_n */) const
{
return true;
}
private:
ck::index_t M01_;
......@@ -217,7 +221,8 @@ template <typename ALayout,
ck::LoopScheduler LoopSched = ck::make_default_loop_scheduler()>
struct TuningParams
{
static constexpr auto MakeAGridDescriptor_AK0_M_AK1(ck::index_t MRaw, ck::index_t KRaw, ck::index_t StrideA)
static constexpr auto
MakeAGridDescriptor_AK0_M_AK1(ck::index_t MRaw, ck::index_t KRaw, ck::index_t StrideA)
{
const auto a_grid_desc_mraw_kraw = [&]() {
if constexpr(ck::is_same_v<ck::tensor_layout::gemm::RowMajor, ALayout>)
......@@ -239,88 +244,90 @@ struct TuningParams
const auto KPad = K - KRaw;
if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::MKPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNKPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNKPadding)
{
// pad both M and K
//assert(K % AK1 == 0);
// assert(K % AK1 == 0);
const auto AK0 = K / AK1;
const auto a_grid_desc_m_k =
transform_tensor_descriptor(a_grid_desc_mraw_kraw,
ck::make_tuple(ck::make_right_pad_transform(MRaw, MPad),
ck::make_right_pad_transform(KRaw, KPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
const auto a_grid_desc_m_k = transform_tensor_descriptor(
a_grid_desc_mraw_kraw,
ck::make_tuple(ck::make_right_pad_transform(MRaw, MPad),
ck::make_right_pad_transform(KRaw, KPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
const auto a_grid_desc_ak0_m_ak1 =
transform_tensor_descriptor(a_grid_desc_m_k,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(AK0, AK1)),
ck::make_pass_through_transform(M)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
const auto a_grid_desc_ak0_m_ak1 = transform_tensor_descriptor(
a_grid_desc_m_k,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(AK0, AK1)),
ck::make_pass_through_transform(M)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
return a_grid_desc_ak0_m_ak1;
}
else if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::MPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNPadding)
{
// pad M, but not K
//assert(KRaw % AK1 == 0);
// assert(KRaw % AK1 == 0);
const auto AK0 = KRaw / AK1;
const auto a_grid_desc_ak0_m_ak1 =
transform_tensor_descriptor(a_grid_desc_mraw_kraw,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(AK0, AK1)),
ck::make_right_pad_transform(MRaw, MPad)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
const auto a_grid_desc_ak0_m_ak1 = transform_tensor_descriptor(
a_grid_desc_mraw_kraw,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(AK0, AK1)),
ck::make_right_pad_transform(MRaw, MPad)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
return a_grid_desc_ak0_m_ak1;
}
else if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::KPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::NKPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::NKPadding)
{
// pad K, but not M
//assert(K % AK1 == 0);
// assert(K % AK1 == 0);
const auto AK0 = K / AK1;
const auto a_grid_desc_m_k = transform_tensor_descriptor(
a_grid_desc_mraw_kraw,
ck::make_tuple(ck::make_pass_through_transform(MRaw), ck::make_right_pad_transform(KRaw, KPad)),
ck::make_tuple(ck::make_pass_through_transform(MRaw),
ck::make_right_pad_transform(KRaw, KPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
const auto a_grid_desc_ak0_m_ak1 =
transform_tensor_descriptor(a_grid_desc_m_k,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(AK0, AK1)),
ck::make_pass_through_transform(MRaw)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
const auto a_grid_desc_ak0_m_ak1 = transform_tensor_descriptor(
a_grid_desc_m_k,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(AK0, AK1)),
ck::make_pass_through_transform(MRaw)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
return a_grid_desc_ak0_m_ak1;
}
else
{
// not pad M or K
//assert(KRaw % AK1 == 0);
// assert(KRaw % AK1 == 0);
const auto AK0 = KRaw / AK1;
const auto a_grid_desc_ak0_m_ak1 =
transform_tensor_descriptor(a_grid_desc_mraw_kraw,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(AK0, AK1)),
ck::make_pass_through_transform(MRaw)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
const auto a_grid_desc_ak0_m_ak1 = transform_tensor_descriptor(
a_grid_desc_mraw_kraw,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(AK0, AK1)),
ck::make_pass_through_transform(MRaw)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
return a_grid_desc_ak0_m_ak1;
}
}
static constexpr auto MakeBGridDescriptor_BK0_N_BK1(ck::index_t KRaw, ck::index_t NRaw, ck::index_t StrideB)
static constexpr auto
MakeBGridDescriptor_BK0_N_BK1(ck::index_t KRaw, ck::index_t NRaw, ck::index_t StrideB)
{
const auto b_grid_desc_nraw_kraw = [&]() {
if constexpr(is_same<ck::tensor_layout::gemm::RowMajor, BLayout>::value)
......@@ -342,88 +349,90 @@ struct TuningParams
const auto KPad = K - KRaw;
if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::NKPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNKPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNKPadding)
{
// pad both N and K
//assert(K % BK1 == 0);
// assert(K % BK1 == 0);
const auto BK0 = K / BK1;
const auto b_grid_desc_n_k =
transform_tensor_descriptor(b_grid_desc_nraw_kraw,
ck::make_tuple(ck::make_right_pad_transform(NRaw, NPad),
ck::make_right_pad_transform(KRaw, KPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
const auto b_grid_desc_n_k = transform_tensor_descriptor(
b_grid_desc_nraw_kraw,
ck::make_tuple(ck::make_right_pad_transform(NRaw, NPad),
ck::make_right_pad_transform(KRaw, KPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
const auto b_grid_desc_bk0_n_bk1 =
transform_tensor_descriptor(b_grid_desc_n_k,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(BK0, BK1)),
ck::make_pass_through_transform(N)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
const auto b_grid_desc_bk0_n_bk1 = transform_tensor_descriptor(
b_grid_desc_n_k,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(BK0, BK1)),
ck::make_pass_through_transform(N)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
return b_grid_desc_bk0_n_bk1;
}
else if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::NPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNPadding)
{
// pad N, but not K
//assert(KRaw % BK1 == 0);
// assert(KRaw % BK1 == 0);
const auto BK0 = KRaw / BK1;
const auto b_grid_desc_bk0_n_bk1 =
transform_tensor_descriptor(b_grid_desc_nraw_kraw,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(BK0, BK1)),
ck::make_right_pad_transform(NRaw, NPad)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
const auto b_grid_desc_bk0_n_bk1 = transform_tensor_descriptor(
b_grid_desc_nraw_kraw,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(BK0, BK1)),
ck::make_right_pad_transform(NRaw, NPad)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
return b_grid_desc_bk0_n_bk1;
}
else if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::KPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MKPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MKPadding)
{
// pad K, but not N
//assert(K % BK1 == 0);
// assert(K % BK1 == 0);
const auto BK0 = K / BK1;
const auto b_grid_desc_n_k = transform_tensor_descriptor(
b_grid_desc_nraw_kraw,
ck::make_tuple(ck::make_pass_through_transform(NRaw), ck::make_right_pad_transform(KRaw, KPad)),
ck::make_tuple(ck::make_pass_through_transform(NRaw),
ck::make_right_pad_transform(KRaw, KPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
const auto b_grid_desc_bk0_n_bk1 =
transform_tensor_descriptor(b_grid_desc_n_k,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(BK0, BK1)),
ck::make_pass_through_transform(NRaw)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
const auto b_grid_desc_bk0_n_bk1 = transform_tensor_descriptor(
b_grid_desc_n_k,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(BK0, BK1)),
ck::make_pass_through_transform(NRaw)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
return b_grid_desc_bk0_n_bk1;
}
else
{
// not pad N or K
//assert(KRaw % BK1 == 0);
// assert(KRaw % BK1 == 0);
const auto BK0 = KRaw / BK1;
const auto b_grid_desc_bk0_n_bk1 =
transform_tensor_descriptor(b_grid_desc_nraw_kraw,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(BK0, BK1)),
ck::make_pass_through_transform(NRaw)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
const auto b_grid_desc_bk0_n_bk1 = transform_tensor_descriptor(
b_grid_desc_nraw_kraw,
ck::make_tuple(make_unmerge_transform(ck::make_tuple(BK0, BK1)),
ck::make_pass_through_transform(NRaw)),
ck::make_tuple(ck::Sequence<1>{}, ck::Sequence<0>{}),
ck::make_tuple(ck::Sequence<0, 2>{}, ck::Sequence<1>{}));
return b_grid_desc_bk0_n_bk1;
}
}
static constexpr auto MakeCGridDescriptor_M_N(ck::index_t MRaw, ck::index_t NRaw, ck::index_t StrideC)
static constexpr auto
MakeCGridDescriptor_M_N(ck::index_t MRaw, ck::index_t NRaw, ck::index_t StrideC)
{
const auto c_grid_desc_mraw_nraw = [&]() {
if constexpr(is_same<ck::tensor_layout::gemm::RowMajor, CLayout>::value)
......@@ -445,32 +454,35 @@ struct TuningParams
const auto NPad = N - NRaw;
if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNKPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MNKPadding)
{
// pad M and N
return transform_tensor_descriptor(c_grid_desc_mraw_nraw,
ck::make_tuple(ck::make_right_pad_transform(MRaw, MPad),
ck::make_right_pad_transform(NRaw, NPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
return transform_tensor_descriptor(
c_grid_desc_mraw_nraw,
ck::make_tuple(ck::make_right_pad_transform(MRaw, MPad),
ck::make_right_pad_transform(NRaw, NPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
}
else if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::MPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MKPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::MKPadding)
{
// pad M, but not N
return transform_tensor_descriptor(
c_grid_desc_mraw_nraw,
ck::make_tuple(ck::make_right_pad_transform(MRaw, MPad), ck::make_pass_through_transform(NRaw)),
ck::make_tuple(ck::make_right_pad_transform(MRaw, MPad),
ck::make_pass_through_transform(NRaw)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
}
else if constexpr(GemmSpec == ck::tensor_operation::device::GemmSpecialization::NPadding ||
GemmSpec == ck::tensor_operation::device::GemmSpecialization::NKPadding)
GemmSpec == ck::tensor_operation::device::GemmSpecialization::NKPadding)
{
// pad N, but not M
return transform_tensor_descriptor(
c_grid_desc_mraw_nraw,
ck::make_tuple(ck::make_pass_through_transform(MRaw), ck::make_right_pad_transform(NRaw, NPad)),
ck::make_tuple(ck::make_pass_through_transform(MRaw),
ck::make_right_pad_transform(NRaw, NPad)),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}),
ck::make_tuple(ck::Sequence<0>{}, ck::Sequence<1>{}));
}
......@@ -544,7 +556,7 @@ struct TuningParams
};
using gemm = TuningParams
// clang-format off
// clang-format off
//| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Specialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
//| | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
......
src/targets/gpu/kernels/include/migraphx/kernels/ck_includes.hpp
View file @ 1dd11890
......@@ -52,7 +52,7 @@ static constexpr auto K1Number = ck::Number<K1>{};
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
using ALayout = Row;//Col;
using ALayout = Row; // Col;
using BLayout = Row;
using CLayout = Row;
......@@ -216,39 +216,39 @@ using BGridDesc_K0_N_K1 = decltype(MakeBGridDescriptor_K0_N_K1(1, 1, 1));
using CGridDesc_M_N = decltype(MakeCGridDescriptor_M_N(1, 1, 1));
using GridwiseGemm =
ck::GridwiseGemmDl_km_kn_mn_v1r3<BlockSize,
ADataType,
AccDataType,
CDataType,
ck::InMemoryDataOperationEnum::Set,
AGridDesc_K0_M_K1,
BGridDesc_K0_N_K1,
CGridDesc_M_N,
MPerBlock,
NPerBlock,
K0PerBlock,
M1PerThread,
N1PerThread,
KPerThread,
M1N1ThreadClusterM1Xs,
M1N1ThreadClusterN1Xs,
ABlockTransferThreadSliceLengths_K0_M0_M1_K1,
ABlockTransferThreadClusterLengths_K0_M0_M1_K1,
ABlockTransferThreadClusterArrangeOrder,
ABlockTransferSrcAccessOrder,
ABlockTransferSrcVectorTensorLengths_K0_M0_M1_K1,
ABlockTransferSrcVectorTensorContiguousDimOrder,
ABlockTransferDstVectorTensorLengths_K0_M0_M1_K1,
BBlockTransferThreadSliceLengths_K0_N0_N1_K1,
BBlockTransferThreadClusterLengths_K0_N0_N1_K1,
BBlockTransferThreadClusterArrangeOrder,
BBlockTransferSrcAccessOrder,
BBlockTransferSrcVectorTensorLengths_K0_N0_N1_K1,
BBlockTransferSrcVectorTensorContiguousDimOrder,
BBlockTransferDstVectorTensorLengths_K0_N0_N1_K1,
CThreadTransferSrcDstAccessOrder,
CThreadTransferSrcDstVectorDim,
CThreadTransferDstScalarPerVector>;
ck::GridwiseGemmDl_km_kn_mn_v1r3<BlockSize,
ADataType,
AccDataType,
CDataType,
ck::InMemoryDataOperationEnum::Set,
AGridDesc_K0_M_K1,
BGridDesc_K0_N_K1,
CGridDesc_M_N,
MPerBlock,
NPerBlock,
K0PerBlock,
M1PerThread,
N1PerThread,
KPerThread,
M1N1ThreadClusterM1Xs,
M1N1ThreadClusterN1Xs,
ABlockTransferThreadSliceLengths_K0_M0_M1_K1,
ABlockTransferThreadClusterLengths_K0_M0_M1_K1,
ABlockTransferThreadClusterArrangeOrder,
ABlockTransferSrcAccessOrder,
ABlockTransferSrcVectorTensorLengths_K0_M0_M1_K1,
ABlockTransferSrcVectorTensorContiguousDimOrder,
ABlockTransferDstVectorTensorLengths_K0_M0_M1_K1,
BBlockTransferThreadSliceLengths_K0_N0_N1_K1,
BBlockTransferThreadClusterLengths_K0_N0_N1_K1,
BBlockTransferThreadClusterArrangeOrder,
BBlockTransferSrcAccessOrder,
BBlockTransferSrcVectorTensorLengths_K0_N0_N1_K1,
BBlockTransferSrcVectorTensorContiguousDimOrder,
BBlockTransferDstVectorTensorLengths_K0_N0_N1_K1,
CThreadTransferSrcDstAccessOrder,
CThreadTransferSrcDstVectorDim,
CThreadTransferDstScalarPerVector>;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
......@@ -267,8 +267,7 @@ using BGridDesc_K0_N0_N1_K1 =
decltype(GridwiseGemm::MakeBGridDescriptor_K0_N0_N1_K1(BGridDesc_K0_N_K1{}));
using CGridDesc_M0_M10_M11_N0_N10_N11 =
decltype(GridwiseGemm::MakeCGridDescriptor_M0_M10_M11_N0_N10_N11(CGridDesc_M_N{}));
using DefaultBlock2CTileMap =
decltype(GridwiseGemm::MakeDefaultBlock2CTileMap(CGridDesc_M_N{}));
using DefaultBlock2CTileMap = decltype(GridwiseGemm::MakeDefaultBlock2CTileMap(CGridDesc_M_N{}));
} // namespace migraphx
#endif
test/verify/0ack_test_ck_gemm.cpp
View file @ 1dd11890
......@@ -37,8 +37,10 @@
// migraphx::shape m2_shape{migraphx::shape::float_type, {4096, 4096}};
// auto l1 = mm->add_parameter("1", m1_shape);
// auto l2 = mm->add_parameter("2", m2_shape);
// // l1 = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), l1);
// // l2 = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), l2);
// // l1 = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}),
// l1);
// // l2 = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}),
// l2);
// mm->add_instruction(migraphx::make_op("ck_gemm"), l1, l2);
......@@ -54,15 +56,15 @@ struct test_ck_gemm : verify_program<test_ck_gemm>
auto* mm = p.get_main_module();
migraphx::shape m1_shape{migraphx::shape::half_type, {2, 3}};
migraphx::shape m2_shape{migraphx::shape::half_type, {3, 4}};
std::vector<float> v1(2*3, 1);
std::vector<float> v1(2 * 3, 1);
std::iota(v1.begin(), v1.end(), 1);
std::vector<float> v2(3*4, 1);
//std::iota(v2.begin(), v2.end(), 1);
std::vector<float> v2(3 * 4, 1);
// std::iota(v2.begin(), v2.end(), 1);
auto l1 = mm->add_literal(migraphx::literal{m1_shape, v1});
auto l2 = mm->add_literal(migraphx::literal{m2_shape, v2});
// auto l1 = mm->add_parameter("1", m1_shape);
// auto l2 = mm->add_parameter("2", m2_shape);
//l1 = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), l1);
// l1 = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), l1);
// l2 = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), l2);
mm->add_instruction(migraphx::make_op("ck_gemm"), l1, l2);
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment