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Commit a037693f authored by ltqin's avatar ltqin
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Merge branch 'develop' into conv_splitk_f32

parents 0694d6ed 4041850f
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Showing with 2745 additions and 434 deletions
CMakeLists.txt
View file @ a037693f
...@@ -200,3 +200,4 @@ enable_cppcheck( ...@@ -200,3 +200,4 @@ enable_cppcheck(
add_subdirectory(host) add_subdirectory(host)
add_subdirectory(example) add_subdirectory(example)
add_subdirectory(profiler) add_subdirectory(profiler)
add_subdirectory(test)
composable_kernel/include/tensor_operation/blockwise_gemm_dlops_v3.hpp
View file @ a037693f
...@@ -10,99 +10,99 @@ template <index_t BlockSize, ...@@ -10,99 +10,99 @@ template <index_t BlockSize,
typename FloatA, typename FloatA,
typename FloatB, typename FloatB,
typename FloatC, typename FloatC,
typename BlockMatrixA, typename ABlockDesc_E1_K1_E2,
typename BlockMatrixB, typename BBlockDesc_E1_N_Ho_Wo_E2,
typename ThreadMatrixC, typename CThreadDesc_K_N_Ho_Wo,
index_t KPerThread,
index_t HPerThread,
index_t WPerThread,
index_t EPerThreadLoop, index_t EPerThreadLoop,
index_t ThreadGemmADataPerRead_K, index_t KPerThreadLoop>
index_t ThreadGemmBDataPerRead_W>
struct BlockwiseGemmDlops_km_kn_m0m1n0n1_v3 struct BlockwiseGemmDlops_km_kn_m0m1n0n1_v3
{ {
struct MatrixIndex static constexpr auto I0 = Number<0>{};
{ static constexpr auto I1 = Number<1>{};
index_t k; static constexpr auto I2 = Number<2>{};
index_t h; static constexpr auto I3 = Number<3>{};
index_t w; static constexpr auto I4 = Number<4>{};
};
using AIndex = MultiIndex<3>;
using BIndex = MultiIndex<3>;
using CIndex = MultiIndex<4>;
static constexpr auto E1 = ABlockDesc_E1_K1_E2{}.GetLength(I0);
static constexpr auto KPerBlock = ABlockDesc_E1_K1_E2{}.GetLength(I1);
static constexpr auto E2 = ABlockDesc_E1_K1_E2{}.GetLength(I2);
static constexpr auto HoPerBlock = BBlockDesc_E1_N_Ho_Wo_E2{}.GetLength(I2);
static constexpr auto WoPerBlock = BBlockDesc_E1_N_Ho_Wo_E2{}.GetLength(I3);
// HACK: fix this @Jing Zhang static constexpr auto KPerThread = CThreadDesc_K_N_Ho_Wo{}.GetLength(I0);
static constexpr index_t KPerThreadSubC = 4; static constexpr auto HoPerThread = CThreadDesc_K_N_Ho_Wo{}.GetLength(I2);
static constexpr auto WoPerThread = CThreadDesc_K_N_Ho_Wo{}.GetLength(I3);
static constexpr auto a_thread_mtx_ = make_naive_tensor_descriptor_packed( static constexpr auto a_thread_mtx_ = make_naive_tensor_descriptor_packed(
make_tuple(Number<EPerThreadLoop>{}, Number<KPerThreadSubC>{})); make_tuple(Number<EPerThreadLoop>{}, Number<KPerThreadLoop>{}, Number<E2>{}));
static constexpr auto b_thread_mtx_ = make_naive_tensor_descriptor_packed(make_tuple( static constexpr auto b_thread_mtx_ =
Number<EPerThreadLoop>{}, Number<1>{}, Number<HPerThread>{}, Number<WPerThread>{})); make_naive_tensor_descriptor_packed(make_tuple(Number<EPerThreadLoop>{},
Number<1>{},
Number<HoPerThread>{},
Number<WoPerThread>{},
Number<E2>{}));
static constexpr auto c_thread_mtx_ = make_naive_tensor_descriptor_packed(make_tuple( static constexpr auto c_thread_mtx_ = make_naive_tensor_descriptor_packed(make_tuple(
Number<KPerThreadSubC>{}, Number<1>{}, Number<HPerThread>{}, Number<WPerThread>{})); Number<KPerThreadLoop>{}, Number<1>{}, Number<HoPerThread>{}, Number<WoPerThread>{}));
using AThreadCopy = ThreadwiseTensorSliceTransfer_v4<FloatA,
FloatA,
BlockMatrixA,
decltype(a_thread_mtx_),
Sequence<EPerThreadLoop, KPerThreadSubC>,
Sequence<0, 1>,
1,
ThreadGemmADataPerRead_K,
1>;
__device__ BlockwiseGemmDlops_km_kn_m0m1n0n1_v3() __device__ BlockwiseGemmDlops_km_kn_m0m1n0n1_v3()
: c_thread_begin_mtx_idx_{GetBeginOfThreadMatrixC(get_thread_local_1d_id())}, : c_thread_origin_data_idx_{GetBeginOfCThreadDesc_K_N_Ho_Wo(get_thread_local_1d_id())},
a_thread_copy_{make_tuple(0, c_thread_begin_mtx_idx_.k * KPerThread)} a_thread_copy_{make_tuple(0, c_thread_origin_data_idx_[I0] * KPerThread, 0)}
{ {
static_assert(BlockMatrixA::IsKnownAtCompileTime() && static_assert(ABlockDesc_E1_K1_E2::IsKnownAtCompileTime() &&
BlockMatrixB::IsKnownAtCompileTime() && BBlockDesc_E1_N_Ho_Wo_E2::IsKnownAtCompileTime() &&
ThreadMatrixC::IsKnownAtCompileTime(), CThreadDesc_K_N_Ho_Wo::IsKnownAtCompileTime(),
"wrong! Desc should be known at compile-time"); "wrong! Desc should be known at compile-time");
constexpr auto I0 = Number<0>{}; static_assert(
constexpr auto I1 = Number<1>{}; ABlockDesc_E1_K1_E2{}.GetLength(I0) == BBlockDesc_E1_N_Ho_Wo_E2{}.GetLength(I0) &&
constexpr auto I2 = Number<2>{}; ABlockDesc_E1_K1_E2{}.GetLength(I2) == BBlockDesc_E1_N_Ho_Wo_E2{}.GetLength(I4),
constexpr auto I3 = Number<3>{}; "wrong! E dimension not consistent\n");
static_assert(BlockMatrixA{}.GetLength(I0) == BlockMatrixB{}.GetLength(I0),
"wrong! K dimension not consistent\n");
constexpr index_t K = BlockMatrixA{}.GetLength(I1); // A is transposed static_assert(E1 % EPerThreadLoop == 0, "");
constexpr index_t H = BlockMatrixB{}.GetLength(I2); static_assert(KPerThread % KPerThreadLoop == 0, "");
constexpr index_t W = BlockMatrixB{}.GetLength(I3);
static_assert(K % KPerThread == 0 && H % HPerThread == 0 && W % WPerThread == 0, static_assert(KPerBlock % KPerThread == 0 && HoPerBlock % HoPerThread == 0 &&
WoPerBlock % WoPerThread == 0,
"wrong! Cannot evenly divide work among\n"); "wrong! Cannot evenly divide work among\n");
constexpr auto KThreadCluster = K / KPerThread; constexpr auto KThreadCluster = KPerBlock / KPerThread;
constexpr auto HThreadCluster = H / HPerThread; constexpr auto HThreadCluster = HoPerBlock / HoPerThread;
constexpr auto WThreadCluster = W / WPerThread; constexpr auto WThreadCluster = WoPerBlock / WoPerThread;
static_assert(BlockSize == KThreadCluster * HThreadCluster * WThreadCluster, static_assert(BlockSize == KThreadCluster * HThreadCluster * WThreadCluster,
"wrong! wrong blocksize\n"); "wrong! wrong blocksize\n");
} }
__device__ static constexpr auto GetThreadMatrixCLengths() __device__ static constexpr auto GetCThreadDesc_K_N_Ho_WoLengths()
{ {
return Sequence<KPerThread, 1, HPerThread, WPerThread>{}; return Sequence<KPerThread, I1, HoPerThread, WoPerThread>{};
} }
__device__ static MatrixIndex GetBeginOfThreadMatrixC(index_t thread_id) __device__ static CIndex GetBeginOfCThreadDesc_K_N_Ho_Wo(index_t thread_id)
{ {
constexpr index_t H = BlockMatrixB{}.GetLength(Number<2>{}); constexpr auto K0 = KPerBlock / KPerThread;
constexpr index_t W = BlockMatrixB{}.GetLength(Number<3>{}); constexpr auto N0 = I1;
constexpr auto H0 = HoPerBlock / HoPerThread;
constexpr auto num_w_threads = W / WPerThread; constexpr auto W0 = WoPerBlock / WoPerThread;
constexpr auto num_h_threads = H / HPerThread;
constexpr auto num_hw_threads = num_w_threads * num_h_threads; constexpr auto c_threadid_to_k_n_h_w_thread_cluster_adaptor =
make_single_stage_tensor_adaptor(
index_t k_thread_id = thread_id / num_hw_threads; make_tuple(make_merge_transform(make_tuple(K0, N0, H0, W0))),
index_t hw_thread_id = thread_id % num_hw_threads; make_tuple(Sequence<0, 1, 2, 3>{}),
make_tuple(Sequence<0>{}));
index_t h_thread_id = hw_thread_id / num_w_threads;
index_t w_thread_id = hw_thread_id % num_w_threads; const auto c_k_n_h_w_thread_cluster_idx =
c_threadid_to_k_n_h_w_thread_cluster_adaptor.CalculateBottomIndex(
return MatrixIndex{k_thread_id, h_thread_id, w_thread_id}; make_multi_index(thread_id));
return c_k_n_h_w_thread_cluster_idx;
} }
template <typename ABlockBuffer, typename BThreadBuffer, typename CThreadBuffer> template <typename ABlockBuffer, typename BThreadBuffer, typename CThreadBuffer>
...@@ -116,19 +116,7 @@ struct BlockwiseGemmDlops_km_kn_m0m1n0n1_v3 ...@@ -116,19 +116,7 @@ struct BlockwiseGemmDlops_km_kn_m0m1n0n1_v3
is_same<remove_cvref_t<typename CThreadBuffer::type>, remove_cvref_t<FloatC>>::value && is_same<remove_cvref_t<typename CThreadBuffer::type>, remove_cvref_t<FloatC>>::value &&
"wrong! inconsistent type"); "wrong! inconsistent type");
constexpr auto I0 = Number<0>{}; constexpr auto a_block_mtx = ABlockDesc_E1_K1_E2{};
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto EPerBlock = a_block_mtx.GetLength(I0);
// HACK: fix this @Jing Zhang
constexpr auto HoPerThreadSubC = 2;
constexpr auto WoPerThreadSubC = 2;
static_assert(KPerThread % KPerThreadSubC == 0, "");
static_assert(HPerThread % HoPerThreadSubC == 0, "");
static_assert(WPerThread % WoPerThreadSubC == 0, "");
// thread A buffer for GEMM // thread A buffer for GEMM
StaticBuffer<AddressSpaceEnum_t::Vgpr, FloatA, a_thread_mtx_.GetElementSpaceSize(), true> StaticBuffer<AddressSpaceEnum_t::Vgpr, FloatA, a_thread_mtx_.GetElementSpaceSize(), true>
...@@ -139,42 +127,46 @@ struct BlockwiseGemmDlops_km_kn_m0m1n0n1_v3 ...@@ -139,42 +127,46 @@ struct BlockwiseGemmDlops_km_kn_m0m1n0n1_v3
FloatC, FloatC,
decltype(a_thread_mtx_), decltype(a_thread_mtx_),
decltype(b_thread_mtx_), decltype(b_thread_mtx_),
decltype(c_thread_mtx_), decltype(c_thread_mtx_)>{};
HoPerThreadSubC,
WoPerThreadSubC>{};
static_for<0, EPerBlock, EPerThreadLoop>{}([&](auto e_begin) { static_for<0, E1, EPerThreadLoop>{}([&](auto e_begin) {
static_for<0, KPerThread, KPerThreadSubC>{}([&](auto k_begin) { static_for<0, KPerThread, KPerThreadLoop>{}([&](auto k_begin) {
a_thread_copy_.Run(a_block_mtx, a_thread_copy_.Run(a_block_mtx,
make_tuple(e_begin, k_begin), make_tuple(e_begin, k_begin, I0),
a_block_buf, a_block_buf,
a_thread_mtx_, a_thread_mtx_,
make_tuple(I0, I0), make_tuple(I0, I0, I0),
a_thread_buf); a_thread_buf);
static_for<0, HPerThread, HoPerThreadSubC>{}([&](auto h_begin) { threadwise_gemm.Run(a_thread_buf,
static_for<0, WPerThread, WoPerThreadSubC>{}([&](auto w_begin) { make_tuple(I0, I0, I0),
threadwise_gemm.Run(a_thread_buf, b_thread_buf,
make_tuple(I0, I0), make_tuple(e_begin, I0, I0, I0, I0),
b_thread_buf, c_thread_buf,
make_tuple(e_begin, I0, h_begin, w_begin), make_tuple(k_begin, I0, I0, I0));
c_thread_buf,
make_tuple(k_begin, I0, h_begin, w_begin));
});
});
}); });
}); });
} }
template <typename ABlockSliceMoveStepIdx> template <typename ABlockSliceMoveStepIdx>
__device__ void MoveASliceWindow(const BlockMatrixA&, __device__ void MoveABlockSliceWindow(const ABlockSliceMoveStepIdx& a_block_slice_move_step_idx)
const ABlockSliceMoveStepIdx& a_block_slice_move_step_idx)
{ {
a_thread_copy_.MoveSrcSliceWindow(BlockMatrixA{}, a_block_slice_move_step_idx); a_thread_copy_.MoveSrcSliceWindow(ABlockDesc_E1_K1_E2{}, a_block_slice_move_step_idx);
} }
private: private:
MatrixIndex c_thread_begin_mtx_idx_; using AThreadCopy =
ThreadwiseTensorSliceTransfer_v4<FloatA,
FloatA,
ABlockDesc_E1_K1_E2,
decltype(a_thread_mtx_),
Sequence<EPerThreadLoop, KPerThreadLoop, E2>,
Sequence<0, 1, 2>,
2,
E2,
E2>;
CIndex c_thread_origin_data_idx_;
AThreadCopy a_thread_copy_; AThreadCopy a_thread_copy_;
}; };
......
composable_kernel/include/tensor_operation/threadwise_gemm_dlops_v3.hpp
View file @ a037693f
...@@ -9,21 +9,22 @@ namespace ck { ...@@ -9,21 +9,22 @@ namespace ck {
// C[M, N] += transpose(A[K, M]) * B[K, N] // C[M, N] += transpose(A[K, M]) * B[K, N]
// Element of matrix can be vectorized data // Element of matrix can be vectorized data
// Assume: // Assume:
// 1. ADesc, BDesc, CDesc are known at compile-time // 1. AThreadDesc_E1_K_E2, BThreadDesc_E1_N_Ho_Wo_E2, CThreadDesc_K_N_Ho_Wo are known at
// compile-time
// 2. AOriginIdx, BOriginIdx, COriginIdx are known at compile-time // 2. AOriginIdx, BOriginIdx, COriginIdx are known at compile-time
template <typename FloatA, template <typename FloatA,
typename FloatB, typename FloatB,
typename FloatC, typename FloatC,
typename ADesc, typename AThreadDesc_E1_K_E2,
typename BDesc, typename BThreadDesc_E1_N_Ho_Wo_E2,
typename CDesc, typename CThreadDesc_K_N_Ho_Wo,
index_t H, typename enable_if<AThreadDesc_E1_K_E2::IsKnownAtCompileTime() &&
index_t W, BThreadDesc_E1_N_Ho_Wo_E2::IsKnownAtCompileTime() &&
typename enable_if<ADesc::IsKnownAtCompileTime() && BDesc::IsKnownAtCompileTime() && CThreadDesc_K_N_Ho_Wo::IsKnownAtCompileTime(),
CDesc::IsKnownAtCompileTime(),
bool>::type = false> bool>::type = false>
struct ThreadwiseGemmDlops_km_kn_mn_v3 struct ThreadwiseGemmDlops_km_kn_mn_v3
{ {
template <typename ABuffer, template <typename ABuffer,
typename AOriginIdx, typename AOriginIdx,
typename BBuffer, typename BBuffer,
...@@ -37,8 +38,10 @@ struct ThreadwiseGemmDlops_km_kn_mn_v3 ...@@ -37,8 +38,10 @@ struct ThreadwiseGemmDlops_km_kn_mn_v3
CBuffer& c_buf, CBuffer& c_buf,
COriginIdx) COriginIdx)
{ {
static_assert(ADesc::IsKnownAtCompileTime() && BDesc::IsKnownAtCompileTime() &&
CDesc::IsKnownAtCompileTime(), static_assert(AThreadDesc_E1_K_E2::IsKnownAtCompileTime() &&
BThreadDesc_E1_N_Ho_Wo_E2::IsKnownAtCompileTime() &&
CThreadDesc_K_N_Ho_Wo::IsKnownAtCompileTime(),
"wrong! Desc should be known at compile-time"); "wrong! Desc should be known at compile-time");
static_assert(is_known_at_compile_time<remove_cvref_t<AOriginIdx>>::value && static_assert(is_known_at_compile_time<remove_cvref_t<AOriginIdx>>::value &&
...@@ -54,102 +57,107 @@ struct ThreadwiseGemmDlops_km_kn_mn_v3 ...@@ -54,102 +57,107 @@ struct ThreadwiseGemmDlops_km_kn_mn_v3
constexpr auto I0 = Number<0>{}; constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{}; constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto E1 = AThreadDesc_E1_K_E2{}.GetLength(I0);
constexpr auto K = AThreadDesc_E1_K_E2{}.GetLength(I1);
constexpr auto E2 = AThreadDesc_E1_K_E2{}.GetLength(I2);
constexpr auto E = ADesc{}.GetLength(I0); constexpr auto Ho = BThreadDesc_E1_N_Ho_Wo_E2{}.GetLength(I2);
constexpr auto K = ADesc{}.GetLength(I1); constexpr auto Wo = BThreadDesc_E1_N_Ho_Wo_E2{}.GetLength(I3);
constexpr auto a_origin_idx = to_multi_index(AOriginIdx{}); constexpr auto a_origin_idx = to_multi_index(AOriginIdx{});
constexpr auto b_origin_idx = to_multi_index(BOriginIdx{}); constexpr auto b_origin_idx = to_multi_index(BOriginIdx{});
constexpr auto c_origin_idx = to_multi_index(COriginIdx{}); constexpr auto c_origin_idx = to_multi_index(COriginIdx{});
static_for<0, E, 1>{}([&](auto e) { if constexpr((Ho % 2 == 0) && (Wo % 2 == 0))
{
constexpr auto SubHW = 2;
static_for<0, K, 1>{}([&](auto k) { static_for<0, K, 1>{}([&](auto k) {
constexpr index_t a_offset = static_for<0, Ho, SubHW>{}([&](auto h) {
ADesc{}.CalculateOffset(a_origin_idx + make_tuple(e, k)); static_for<0, Wo, SubHW>{}([&](auto w) {
static_for<0, E1, 1>{}([&](auto e1) {
if constexpr(H == 2 && W == 2) static_for<0, E2, 1>{}([&](auto e2) {
{ constexpr index_t a_offset = AThreadDesc_E1_K_E2{}.CalculateOffset(
constexpr index_t b_offset_0 = a_origin_idx + make_tuple(e1, k, e2));
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, 0, 0));
constexpr index_t b_offset_1 = constexpr index_t b0_offset =
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, 0, 1)); BThreadDesc_E1_N_Ho_Wo_E2{}.CalculateOffset(
constexpr index_t b_offset_2 = b_origin_idx + make_tuple(e1, 0, h, w, e2));
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, 1, 0));
constexpr index_t b_offset_3 = constexpr index_t b1_offset =
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, 1, 1)); BThreadDesc_E1_N_Ho_Wo_E2{}.CalculateOffset(
b_origin_idx + make_tuple(e1, 0, h, w + 1, e2));
constexpr index_t c_offset_0 =
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, 0, 0)); constexpr index_t b2_offset =
constexpr index_t c_offset_1 = BThreadDesc_E1_N_Ho_Wo_E2{}.CalculateOffset(
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, 0, 1)); b_origin_idx + make_tuple(e1, 0, h + 1, w, e2));
constexpr index_t c_offset_2 =
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, 1, 0)); constexpr index_t b3_offset =
constexpr index_t c_offset_3 = BThreadDesc_E1_N_Ho_Wo_E2{}.CalculateOffset(
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, 1, 1)); b_origin_idx + make_tuple(e1, 0, h + 1, w + 1, e2));
amd_assembly_outer_product_1x4(a_buf[Number<a_offset>{}], constexpr index_t c0_offset =
b_buf[Number<b_offset_0>{}], CThreadDesc_K_N_Ho_Wo{}.CalculateOffset(c_origin_idx +
b_buf[Number<b_offset_1>{}], make_tuple(k, 0, h, w));
b_buf[Number<b_offset_2>{}],
b_buf[Number<b_offset_3>{}], constexpr index_t c1_offset =
c_buf(Number<c_offset_0>{}), CThreadDesc_K_N_Ho_Wo{}.CalculateOffset(
c_buf(Number<c_offset_1>{}), c_origin_idx + make_tuple(k, 0, h, w + 1));
c_buf(Number<c_offset_2>{}),
c_buf(Number<c_offset_3>{})); constexpr index_t c2_offset =
} CThreadDesc_K_N_Ho_Wo{}.CalculateOffset(
else if constexpr(H == 4 && W == 1) c_origin_idx + make_tuple(k, 0, h + 1, w));
{
constexpr index_t b_offset_0 = constexpr index_t c3_offset =
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, 0, 0)); CThreadDesc_K_N_Ho_Wo{}.CalculateOffset(
constexpr index_t b_offset_1 = c_origin_idx + make_tuple(k, 0, h + 1, w + 1));
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, 1, 0));
constexpr index_t b_offset_2 = amd_assembly_outer_product_1x4(a_buf[Number<a_offset>{}],
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, 2, 0)); b_buf[Number<b0_offset>{}],
constexpr index_t b_offset_3 = b_buf[Number<b1_offset>{}],
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, 3, 0)); b_buf[Number<b2_offset>{}],
b_buf[Number<b3_offset>{}],
constexpr index_t c_offset_0 = c_buf(Number<c0_offset>{}),
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, 0, 0)); c_buf(Number<c1_offset>{}),
constexpr index_t c_offset_1 = c_buf(Number<c2_offset>{}),
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, 1, 0)); c_buf(Number<c3_offset>{}));
constexpr index_t c_offset_2 = });
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, 2, 0)); });
constexpr index_t c_offset_3 = });
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, 3, 0)); });
});
amd_assembly_outer_product_1x4(a_buf[Number<a_offset>{}], }
b_buf[Number<b_offset_0>{}], else
b_buf[Number<b_offset_1>{}], {
b_buf[Number<b_offset_2>{}],
b_buf[Number<b_offset_3>{}], static_for<0, K, 1>{}([&](auto k) {
c_buf(Number<c_offset_0>{}), static_for<0, Ho, 1>{}([&](auto h) {
c_buf(Number<c_offset_1>{}), static_for<0, Wo, 1>{}([&](auto w) {
c_buf(Number<c_offset_2>{}), static_for<0, E1, 1>{}([&](auto e1) {
c_buf(Number<c_offset_3>{})); static_for<0, E2, 1>{}([&](auto e2) {
} constexpr index_t a_offset = AThreadDesc_E1_K_E2{}.CalculateOffset(
else a_origin_idx + make_tuple(e1, k, e2));
{
static_for<0, H, 1>{}([&](auto h) { constexpr index_t b_offset =
static_for<0, W, 1>{}([&](auto w) { BThreadDesc_E1_N_Ho_Wo_E2{}.CalculateOffset(
constexpr index_t b_offset = b_origin_idx + make_tuple(e1, 0, h, w, e2));
BDesc{}.CalculateOffset(b_origin_idx + make_tuple(e, 0, h, w));
constexpr index_t c_offset =
constexpr index_t c_offset = CThreadDesc_K_N_Ho_Wo{}.CalculateOffset(c_origin_idx +
CDesc{}.CalculateOffset(c_origin_idx + make_tuple(k, 0, h, w)); make_tuple(k, 0, h, w));
#if 0 inner_product<FloatA, FloatB, FloatC>(a_buf[Number<a_offset>{}],
c_buf(Number<c_offset>{}) += inner_product_with_conversion<FloatC>{}( b_buf[Number<b_offset>{}],
a_buf[Number<a_offset>{}], b_buf[Number<b_offset>{}]); c_buf(Number<c_offset>{}));
#else });
amd_assembly_inner_product(a_buf[Number<a_offset>{}],
b_buf[Number<b_offset>{}],
c_buf(Number<c_offset>{}));
#endif
}); });
}); });
} });
}); });
}); }
} }
}; };
......
composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer.hpp
View file @ a037693f
...@@ -217,6 +217,22 @@ struct ThreadwiseTensorSliceTransfer_v1r3 ...@@ -217,6 +217,22 @@ struct ThreadwiseTensorSliceTransfer_v1r3
is_dst_valid, is_dst_valid,
dst_vector.template AsType<dst_vector_t>()[Number<0>{}]); dst_vector.template AsType<dst_vector_t>()[Number<0>{}]);
} }
else if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::Add)
{
typename vector_type_maker<DstData, DstScalarPerVector>::type tmp;
tmp.template AsType<dst_vector_t>()(Number<0>{}) =
dst_buf.template Get<dst_vector_t>(dst_coord_.GetOffset(), is_dst_valid);
static_for<0, DstScalarPerVector, 1>{}([&](auto t) {
dst_vector.template AsType<DstData>()(t) += tmp.template AsType<DstData>()[t];
});
dst_buf.template Set<dst_vector_t>(
dst_coord_.GetOffset(),
is_dst_valid,
dst_vector.template AsType<dst_vector_t>()[Number<0>{}]);
}
constexpr auto move_on_dim = [&]() constexpr constexpr auto move_on_dim = [&]() constexpr
{ {
...@@ -666,6 +682,25 @@ struct ThreadwiseTensorSliceTransfer_v2 ...@@ -666,6 +682,25 @@ struct ThreadwiseTensorSliceTransfer_v2
move_tensor_coordinate(src_desc, src_coord_, adjusted_step); move_tensor_coordinate(src_desc, src_coord_, adjusted_step);
} }
// src_slice_origin_step_idx need to be known at compile-time, for performance reason
template <typename SrcMoveSliceWindowStepHack>
__device__ void
MoveSrcSliceWindow(const SrcDesc& src_desc,
const Index& src_slice_origin_step_idx,
const SrcMoveSliceWindowStepHack& src_move_slice_window_step_hack)
{
// if src coord was not reset by RunRead(), then need to adjust the step here
const auto adjusted_step_idx =
SrcResetCoordinateAfterRun ? src_slice_origin_step_idx
: src_slice_origin_step_idx + GetSrcCoordinateResetStep();
// is it OK to construct a new step every time?
const auto adjusted_step = make_tensor_coordinate_step(
src_desc, adjusted_step_idx, src_move_slice_window_step_hack);
move_tensor_coordinate(src_desc, src_coord_, adjusted_step);
}
private: private:
SrcCoord src_coord_; SrcCoord src_coord_;
}; // namespace ck }; // namespace ck
......
composable_kernel/include/utility/amd_buffer_addressing.hpp
View file @ a037693f
...@@ -268,14 +268,14 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -268,14 +268,14 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
const float2_t tmp = llvm_amdgcn_raw_buffer_load_fp32x2( const float2_t tmp = llvm_amdgcn_raw_buffer_load_fp32x2(
src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0); src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0);
return as_type<double>(tmp); return bit_cast<double>(tmp);
} }
else if constexpr(N == 2) else if constexpr(N == 2)
{ {
const float4_t tmp = llvm_amdgcn_raw_buffer_load_fp32x4( const float4_t tmp = llvm_amdgcn_raw_buffer_load_fp32x4(
src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0); src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0);
return as_type<double2_t>(tmp); return bit_cast<double2_t>(tmp);
} }
else if constexpr(N == 4) else if constexpr(N == 4)
{ {
...@@ -289,8 +289,8 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -289,8 +289,8 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
0); 0);
vector_type<double, 4> tmp; vector_type<double, 4> tmp;
tmp.AsType<double2_t>()(Number<0>{}) = as_type<double2_t>(f32_0); tmp.AsType<double2_t>()(Number<0>{}) = bit_cast<double2_t>(f32_0);
tmp.AsType<double2_t>()(Number<1>{}) = as_type<double2_t>(f32_1); tmp.AsType<double2_t>()(Number<1>{}) = bit_cast<double2_t>(f32_1);
return tmp.AsType<double4_t>()(Number<0>{}); return tmp.AsType<double4_t>()(Number<0>{});
} }
...@@ -351,7 +351,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -351,7 +351,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
float4_t tmp = llvm_amdgcn_raw_buffer_load_fp32x4( float4_t tmp = llvm_amdgcn_raw_buffer_load_fp32x4(
src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0); src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0);
return as_type<half8_t>(tmp); return bit_cast<half8_t>(tmp);
} }
} }
else if constexpr(is_same<T, ushort>::value) else if constexpr(is_same<T, ushort>::value)
...@@ -376,7 +376,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -376,7 +376,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
int32x4_t tmp = llvm_amdgcn_raw_buffer_load_i32x4( int32x4_t tmp = llvm_amdgcn_raw_buffer_load_i32x4(
src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0); src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0);
return as_type<ushort8_t>(tmp); return bit_cast<ushort8_t>(tmp);
} }
} }
else if constexpr(is_same<T, int32_t>::value) else if constexpr(is_same<T, int32_t>::value)
...@@ -427,7 +427,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -427,7 +427,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
int16_t tmp = llvm_amdgcn_raw_buffer_load_i16( int16_t tmp = llvm_amdgcn_raw_buffer_load_i16(
src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0); src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0);
return as_type<int8x2_t>(tmp); return bit_cast<int8x2_t>(tmp);
#endif #endif
} }
else if constexpr(N == 4) else if constexpr(N == 4)
...@@ -439,7 +439,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -439,7 +439,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
int32_t tmp = llvm_amdgcn_raw_buffer_load_i32( int32_t tmp = llvm_amdgcn_raw_buffer_load_i32(
src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0); src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0);
return as_type<int8x4_t>(tmp); return bit_cast<int8x4_t>(tmp);
#endif #endif
} }
else if constexpr(N == 8) else if constexpr(N == 8)
...@@ -461,7 +461,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -461,7 +461,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
int32x2_t tmp = llvm_amdgcn_raw_buffer_load_i32x2( int32x2_t tmp = llvm_amdgcn_raw_buffer_load_i32x2(
src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0); src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0);
return as_type<int8x8_t>(tmp); return bit_cast<int8x8_t>(tmp);
#endif #endif
} }
else if constexpr(N == 16) else if constexpr(N == 16)
...@@ -495,7 +495,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w ...@@ -495,7 +495,7 @@ __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_w
int32x4_t tmp = llvm_amdgcn_raw_buffer_load_i32x4( int32x4_t tmp = llvm_amdgcn_raw_buffer_load_i32x4(
src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0); src_wave_buffer_resource, src_thread_addr_offset, src_wave_addr_offset, 0);
return as_type<int8x16_t>(tmp); return bit_cast<int8x16_t>(tmp);
#endif #endif
} }
} }
...@@ -521,7 +521,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src ...@@ -521,7 +521,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
// use fp32 store to mimic fp64 store // use fp32 store to mimic fp64 store
if constexpr(N == 1) if constexpr(N == 1)
{ {
llvm_amdgcn_raw_buffer_store_fp32x2(as_type<float2_t>(src_thread_data), llvm_amdgcn_raw_buffer_store_fp32x2(bit_cast<float2_t>(src_thread_data),
dst_wave_buffer_resource, dst_wave_buffer_resource,
dst_thread_addr_offset, dst_thread_addr_offset,
dst_wave_addr_offset, dst_wave_addr_offset,
...@@ -529,7 +529,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src ...@@ -529,7 +529,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
} }
else if constexpr(N == 2) else if constexpr(N == 2)
{ {
llvm_amdgcn_raw_buffer_store_fp32x4(as_type<float4_t>(src_thread_data), llvm_amdgcn_raw_buffer_store_fp32x4(bit_cast<float4_t>(src_thread_data),
dst_wave_buffer_resource, dst_wave_buffer_resource,
dst_thread_addr_offset, dst_thread_addr_offset,
dst_wave_addr_offset, dst_wave_addr_offset,
...@@ -591,6 +591,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src ...@@ -591,6 +591,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
} }
else if constexpr(N == 8) else if constexpr(N == 8)
{ {
#if 0
vector_type<half_t, 8> tmp{src_thread_data}; vector_type<half_t, 8> tmp{src_thread_data};
llvm_amdgcn_raw_buffer_store_fp16x4(tmp.AsType<half4_t>()[Number<0>{}], llvm_amdgcn_raw_buffer_store_fp16x4(tmp.AsType<half4_t>()[Number<0>{}],
...@@ -604,6 +605,13 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src ...@@ -604,6 +605,13 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
dst_thread_addr_offset, dst_thread_addr_offset,
dst_wave_addr_offset + 4 * sizeof(half_t), dst_wave_addr_offset + 4 * sizeof(half_t),
0); 0);
#else
llvm_amdgcn_raw_buffer_store_fp32x4(bit_cast<float4_t>(src_thread_data),
dst_wave_buffer_resource,
dst_thread_addr_offset,
dst_wave_addr_offset,
0);
#endif
} }
} }
else if constexpr(is_same<T, ushort>::value) else if constexpr(is_same<T, ushort>::value)
...@@ -695,7 +703,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src ...@@ -695,7 +703,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
dst_wave_addr_offset, dst_wave_addr_offset,
0); 0);
#else #else
llvm_amdgcn_raw_buffer_store_i16(as_type<int16_t>(src_thread_data), llvm_amdgcn_raw_buffer_store_i16(bit_cast<int16_t>(src_thread_data),
dst_wave_buffer_resource, dst_wave_buffer_resource,
dst_thread_addr_offset, dst_thread_addr_offset,
dst_wave_addr_offset, dst_wave_addr_offset,
...@@ -711,7 +719,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src ...@@ -711,7 +719,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
dst_wave_addr_offset, dst_wave_addr_offset,
0); 0);
#else #else
llvm_amdgcn_raw_buffer_store_i32(as_type<int32_t>(src_thread_data), llvm_amdgcn_raw_buffer_store_i32(bit_cast<int32_t>(src_thread_data),
dst_wave_buffer_resource, dst_wave_buffer_resource,
dst_thread_addr_offset, dst_thread_addr_offset,
dst_wave_addr_offset, dst_wave_addr_offset,
...@@ -720,7 +728,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src ...@@ -720,7 +728,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
} }
else if constexpr(N == 8) else if constexpr(N == 8)
{ {
llvm_amdgcn_raw_buffer_store_i32x2(as_type<int32x2_t>(src_thread_data), llvm_amdgcn_raw_buffer_store_i32x2(bit_cast<int32x2_t>(src_thread_data),
dst_wave_buffer_resource, dst_wave_buffer_resource,
dst_thread_addr_offset, dst_thread_addr_offset,
dst_wave_addr_offset, dst_wave_addr_offset,
...@@ -728,7 +736,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src ...@@ -728,7 +736,7 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
} }
else if constexpr(N == 16) else if constexpr(N == 16)
{ {
llvm_amdgcn_raw_buffer_store_i32x4(as_type<int32x4_t>(src_thread_data), llvm_amdgcn_raw_buffer_store_i32x4(bit_cast<int32x4_t>(src_thread_data),
dst_wave_buffer_resource, dst_wave_buffer_resource,
dst_thread_addr_offset, dst_thread_addr_offset,
dst_wave_addr_offset, dst_wave_addr_offset,
......
composable_kernel/include/utility/amd_inline_asm.hpp
View file @ a037693f
...@@ -211,14 +211,14 @@ amd_assembly_outer_product_1x2(int8x4_t a, int8x4_t b0, int8x4_t b1, int32_t& c0 ...@@ -211,14 +211,14 @@ amd_assembly_outer_product_1x2(int8x4_t a, int8x4_t b0, int8x4_t b1, int32_t& c0
v_dot4_i32_i8 %1, %2, %4, %1\n \ v_dot4_i32_i8 %1, %2, %4, %1\n \
" "
: "=v"(c0), "=v"(c1) : "=v"(c0), "=v"(c1)
: "v"(as_type<int32_t>(a)), : "v"(bit_cast<int32_t>(a)),
"v"(as_type<int32_t>(b0)), "v"(bit_cast<int32_t>(b0)),
"v"(as_type<int32_t>(b1)), "v"(bit_cast<int32_t>(b1)),
"0"(c0), "0"(c0),
"1"(c1)); "1"(c1));
#else #else
c0 = __builtin_amdgcn_sdot4(as_type<int32_t>(a), as_type<int32_t>(b0), c0, false); c0 = __builtin_amdgcn_sdot4(bit_cast<int32_t>(a), bit_cast<int32_t>(b0), c0, false);
c1 = __builtin_amdgcn_sdot4(as_type<int32_t>(a), as_type<int32_t>(b1), c1, false); c1 = __builtin_amdgcn_sdot4(bit_cast<int32_t>(a), bit_cast<int32_t>(b1), c1, false);
#endif #endif
} }
...@@ -244,20 +244,20 @@ __device__ void amd_assembly_outer_product_1x4(int8x4_t a, ...@@ -244,20 +244,20 @@ __device__ void amd_assembly_outer_product_1x4(int8x4_t a,
v_dot4_i32_i8 %3, %4, %8, %3\n \ v_dot4_i32_i8 %3, %4, %8, %3\n \
" "
: "=v"(c0), "=v"(c1), "=v"(c2), "=v"(c3) : "=v"(c0), "=v"(c1), "=v"(c2), "=v"(c3)
: "v"(as_type<int32_t>(a)), : "v"(bit_cast<int32_t>(a)),
"v"(as_type<int32_t>(b0)), "v"(bit_cast<int32_t>(b0)),
"v"(as_type<int32_t>(b1)), "v"(bit_cast<int32_t>(b1)),
"v"(as_type<int32_t>(b2)), "v"(bit_cast<int32_t>(b2)),
"v"(as_type<int32_t>(b3)), "v"(bit_cast<int32_t>(b3)),
"0"(c0), "0"(c0),
"1"(c1), "1"(c1),
"2"(c2), "2"(c2),
"3"(c3)); "3"(c3));
#else #else
c0 = __builtin_amdgcn_sdot4(as_type<int32_t>(a), as_type<int32_t>(b0), c0, false); c0 = __builtin_amdgcn_sdot4(bit_cast<int32_t>(a), bit_cast<int32_t>(b0), c0, false);
c1 = __builtin_amdgcn_sdot4(as_type<int32_t>(a), as_type<int32_t>(b1), c1, false); c1 = __builtin_amdgcn_sdot4(bit_cast<int32_t>(a), bit_cast<int32_t>(b1), c1, false);
c2 = __builtin_amdgcn_sdot4(as_type<int32_t>(a), as_type<int32_t>(b2), c2, false); c2 = __builtin_amdgcn_sdot4(bit_cast<int32_t>(a), bit_cast<int32_t>(b2), c2, false);
c3 = __builtin_amdgcn_sdot4(as_type<int32_t>(a), as_type<int32_t>(b3), c3, false); c3 = __builtin_amdgcn_sdot4(bit_cast<int32_t>(a), bit_cast<int32_t>(b3), c3, false);
#endif #endif
} }
......
composable_kernel/include/utility/amd_xdlops.hpp
View file @ a037693f
...@@ -340,8 +340,8 @@ struct intrin_mfma_i32_32x32x8i8<32, 32> ...@@ -340,8 +340,8 @@ struct intrin_mfma_i32_32x32x8i8<32, 32>
__device__ static void Run(const int8x4_t& reg_a, const int8x4_t& reg_b, FloatC& reg_c) __device__ static void Run(const int8x4_t& reg_a, const int8x4_t& reg_b, FloatC& reg_c)
{ {
reg_c.template AsType<int32x16_t>()(Number<0>{}) = reg_c.template AsType<int32x16_t>()(Number<0>{}) =
llvm_intrin_amdgcn_mfma_i32_32x32x8i8(as_type<int>(reg_a), llvm_intrin_amdgcn_mfma_i32_32x32x8i8(bit_cast<int>(reg_a),
as_type<int>(reg_b), bit_cast<int>(reg_b),
reg_c.template AsType<int32x16_t>()[Number<0>{}], reg_c.template AsType<int32x16_t>()[Number<0>{}],
0, 0,
0, 0,
...@@ -359,8 +359,8 @@ struct intrin_mfma_i32_16x16x16i8<16, 16> ...@@ -359,8 +359,8 @@ struct intrin_mfma_i32_16x16x16i8<16, 16>
__device__ static void Run(const int8x4_t& reg_a, const int8x4_t& reg_b, FloatC& reg_c) __device__ static void Run(const int8x4_t& reg_a, const int8x4_t& reg_b, FloatC& reg_c)
{ {
reg_c.template AsType<int32x4_t>()(Number<0>{}) = reg_c.template AsType<int32x4_t>()(Number<0>{}) =
llvm_intrin_amdgcn_mfma_i32_16x16x16i8(as_type<int>(reg_a), llvm_intrin_amdgcn_mfma_i32_16x16x16i8(bit_cast<int>(reg_a),
as_type<int>(reg_b), bit_cast<int>(reg_b),
reg_c.template AsType<int32x4_t>()[Number<0>{}], reg_c.template AsType<int32x4_t>()[Number<0>{}],
0, 0,
0, 0,
......
composable_kernel/include/utility/config.hpp
View file @ a037693f
...@@ -96,9 +96,22 @@ ...@@ -96,9 +96,22 @@
// pass tensor descriptor by value or void* // pass tensor descriptor by value or void*
#define CK_EXPERIMENTAL_PASS_TENSOR_DESCRIPTOR_BY_VALUE 1 #define CK_EXPERIMENTAL_PASS_TENSOR_DESCRIPTOR_BY_VALUE 1
#define CK_EXPERIMENTAL_PASS_TENSOR_DESCRIPTOR_BY_VOID_POINTER 0 #define CK_EXPERIMENTAL_PASS_TENSOR_DESCRIPTOR_BY_VOID_POINTER 0
#define CK_EXPERIMENTAL_STATIC_TENSOR_DESCRIPTOR 0
// merge transformation use magic number division // merge transformation use magic number division
#ifndef CK_EXPERIMENTAL_MERGE_USE_MAGIC_DIVISION
#define CK_EXPERIMENTAL_MERGE_USE_MAGIC_DIVISION 1 #define CK_EXPERIMENTAL_MERGE_USE_MAGIC_DIVISION 1
#endif
// use __builtin_memcpy instead of pointer cast to access a vector from pointer of scalar
#ifndef CK_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
#define CK_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS 0
#endif
// use __builtin_memcpy instead of union to do bit_cast
#ifndef CK_EXPERIMENTAL_USE_MEMCPY_FOR_BIT_CAST
#define CK_EXPERIMENTAL_USE_MEMCPY_FOR_BIT_CAST 1
#endif
// hack: have underlying assumption that need to be satsified, otherwise it's a bug // hack: have underlying assumption that need to be satsified, otherwise it's a bug
// hack for forcing register to keep idx_diff_low_const in SGPR. idx_diff_low_const must be // hack for forcing register to keep idx_diff_low_const in SGPR. idx_diff_low_const must be
...@@ -118,7 +131,7 @@ ...@@ -118,7 +131,7 @@
#define CK_WORKAROUND_SWDEV_XXXXXX_INT8_BUFFER_LOAD_STORE_ISSUE 1 #define CK_WORKAROUND_SWDEV_XXXXXX_INT8_BUFFER_LOAD_STORE_ISSUE 1
#endif #endif
// workaround for compiler crash when using buffer load/store for i8 // workaround for compiler gnerating inefficient ds_write instructions
#ifndef CK_WORKAROUND_SWDEV_XXXXXX_INT8_DS_WRITE_ISSUE #ifndef CK_WORKAROUND_SWDEV_XXXXXX_INT8_DS_WRITE_ISSUE
#define CK_WORKAROUND_SWDEV_XXXXXX_INT8_DS_WRITE_ISSUE 1 #define CK_WORKAROUND_SWDEV_XXXXXX_INT8_DS_WRITE_ISSUE 1
#endif #endif
...@@ -133,7 +146,15 @@ namespace ck { ...@@ -133,7 +146,15 @@ namespace ck {
enum InMemoryDataOperationEnum_t enum InMemoryDataOperationEnum_t
{ {
Set, Set,
AtomicAdd AtomicAdd,
Add
};
enum ActivTypeEnum_t
{
None = 0,
LeakyRelu,
Sigmoid
}; };
// index type // index type
......
composable_kernel/include/utility/data_type.hpp
View file @ a037693f
...@@ -1081,11 +1081,11 @@ struct NumericLimits<half_t> ...@@ -1081,11 +1081,11 @@ struct NumericLimits<half_t>
static constexpr unsigned short binary_max = 0x7BFF; static constexpr unsigned short binary_max = 0x7BFF;
static constexpr unsigned short binary_lowest = 0xFBFF; static constexpr unsigned short binary_lowest = 0xFBFF;
__host__ __device__ static constexpr half_t Min() { return as_type<half_t>(binary_min); } __host__ __device__ static constexpr half_t Min() { return bit_cast<half_t>(binary_min); }
__host__ __device__ static constexpr half_t Max() { return as_type<half_t>(binary_max); } __host__ __device__ static constexpr half_t Max() { return bit_cast<half_t>(binary_max); }
__host__ __device__ static constexpr half_t Lowest() { return as_type<half_t>(binary_lowest); } __host__ __device__ static constexpr half_t Lowest() { return bit_cast<half_t>(binary_lowest); }
}; };
} // namespace ck } // namespace ck
......
composable_kernel/include/utility/dynamic_buffer.hpp
View file @ a037693f
...@@ -83,12 +83,28 @@ struct DynamicBuffer ...@@ -83,12 +83,28 @@ struct DynamicBuffer
{ {
if constexpr(InvalidElementUseNumericalZeroValue) if constexpr(InvalidElementUseNumericalZeroValue)
{ {
#if CK_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp;
__builtin_memcpy(&tmp, &(p_data_[i]), sizeof(X));
return is_valid_element ? tmp : X{0};
#else
return is_valid_element ? *c_style_pointer_cast<const X*>(&p_data_[i]) : X{0}; return is_valid_element ? *c_style_pointer_cast<const X*>(&p_data_[i]) : X{0};
#endif
} }
else else
{ {
#if CK_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp;
__builtin_memcpy(&tmp, &(p_data_[i]), sizeof(X));
return is_valid_element ? tmp : X{invalid_element_value_};
#else
return is_valid_element ? *c_style_pointer_cast<const X*>(&p_data_[i]) return is_valid_element ? *c_style_pointer_cast<const X*>(&p_data_[i])
: X{invalid_element_value_}; : X{invalid_element_value_};
#endif
} }
} }
} }
...@@ -117,7 +133,13 @@ struct DynamicBuffer ...@@ -117,7 +133,13 @@ struct DynamicBuffer
#else #else
if(is_valid_element) if(is_valid_element)
{ {
#if CK_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp = x;
__builtin_memcpy(&(p_data_[i]), &tmp, sizeof(X));
#else
*c_style_pointer_cast<X*>(&p_data_[i]) = x; *c_style_pointer_cast<X*>(&p_data_[i]) = x;
#endif
} }
#endif #endif
} }
...@@ -126,7 +148,13 @@ struct DynamicBuffer ...@@ -126,7 +148,13 @@ struct DynamicBuffer
if(is_valid_element) if(is_valid_element)
{ {
#if !CK_WORKAROUND_SWDEV_XXXXXX_INT8_DS_WRITE_ISSUE #if !CK_WORKAROUND_SWDEV_XXXXXX_INT8_DS_WRITE_ISSUE
#if CK_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp = x;
__builtin_memcpy(&(p_data_[i]), &tmp, sizeof(X));
#else
*c_style_pointer_cast<X*>(&p_data_[i]) = x; *c_style_pointer_cast<X*>(&p_data_[i]) = x;
#endif
#else #else
// HACK: compiler would lower IR "store<i8, 16> address_space(3)" into // HACK: compiler would lower IR "store<i8, 16> address_space(3)" into
// inefficient // inefficient
...@@ -201,7 +229,13 @@ struct DynamicBuffer ...@@ -201,7 +229,13 @@ struct DynamicBuffer
} }
else else
{ {
#if CK_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp = x;
__builtin_memcpy(&(p_data_[i]), &tmp, sizeof(X));
#else
*c_style_pointer_cast<X*>(&p_data_[i]) = x; *c_style_pointer_cast<X*>(&p_data_[i]) = x;
#endif
} }
#endif #endif
} }
...@@ -210,7 +244,13 @@ struct DynamicBuffer ...@@ -210,7 +244,13 @@ struct DynamicBuffer
{ {
if(is_valid_element) if(is_valid_element)
{ {
#if CK_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp = x;
__builtin_memcpy(&(p_data_[i]), &tmp, sizeof(X));
#else
*c_style_pointer_cast<X*>(&p_data_[i]) = x; *c_style_pointer_cast<X*>(&p_data_[i]) = x;
#endif
} }
} }
} }
......
composable_kernel/include/utility/inner_product.hpp
View file @ a037693f
...@@ -144,9 +144,9 @@ inner_product<int8x4_t, int8x4_t, int32_t>(const int8x4_t& a, const int8x4_t& b, ...@@ -144,9 +144,9 @@ inner_product<int8x4_t, int8x4_t, int32_t>(const int8x4_t& a, const int8x4_t& b,
v_dot4_i32_i8 %0, %1, %2, %0\n \ v_dot4_i32_i8 %0, %1, %2, %0\n \
" "
: "=v"(c) : "=v"(c)
: "v"(as_type<int32_t>(a)), "v"(as_type<int32_t>(b)), "0"(c)); : "v"(bit_cast<int32_t>(a)), "v"(bit_cast<int32_t>(b)), "0"(c));
#else #else
c = __builtin_amdgcn_sdot4(as_type<int32_t>(a), as_type<int32_t>(b), c, false); c = __builtin_amdgcn_sdot4(bit_cast<int32_t>(a), bit_cast<int32_t>(b), c, false);
#endif #endif
#else #else
const vector_type<int8_t, 4> a_vector{a}; const vector_type<int8_t, 4> a_vector{a};
......
composable_kernel/include/utility/magic_division.hpp
View file @ a037693f
...@@ -125,7 +125,7 @@ struct MagicDivision ...@@ -125,7 +125,7 @@ struct MagicDivision
__host__ __device__ static constexpr int32_t __host__ __device__ static constexpr int32_t
DoMagicDivision(int32_t dividend_i32, uint32_t multiplier, uint32_t shift) DoMagicDivision(int32_t dividend_i32, uint32_t multiplier, uint32_t shift)
{ {
uint32_t dividend_u32 = as_type<uint32_t>(dividend_i32); uint32_t dividend_u32 = bit_cast<uint32_t>(dividend_i32);
uint32_t tmp = __umulhi(dividend_u32, multiplier); uint32_t tmp = __umulhi(dividend_u32, multiplier);
return (tmp + dividend_u32) >> shift; return (tmp + dividend_u32) >> shift;
} }
......
composable_kernel/include/utility/statically_indexed_array.hpp
View file @ a037693f
...@@ -54,5 +54,49 @@ __host__ __device__ constexpr auto make_statically_indexed_array() ...@@ -54,5 +54,49 @@ __host__ __device__ constexpr auto make_statically_indexed_array()
return StaticallyIndexedArray<X, 0>(); return StaticallyIndexedArray<X, 0>();
} }
template <typename T, index_t N>
struct StaticallyIndexedArray_v2
{
__host__ __device__ constexpr StaticallyIndexedArray_v2() = default;
__host__ __device__ static constexpr index_t Size() { return N; }
// read access
template <index_t I>
__host__ __device__ constexpr const auto& At(Number<I>) const
{
static_assert(I < N, "wrong! out of range");
return data_[I];
}
// write access
template <index_t I>
__host__ __device__ constexpr auto& At(Number<I>)
{
static_assert(I < N, "wrong! out of range");
return data_[I];
}
// read access
template <index_t I>
__host__ __device__ constexpr const auto& operator[](Number<I> i) const
{
return At(i);
}
// write access
template <index_t I>
__host__ __device__ constexpr auto& operator()(Number<I> i)
{
return At(i);
}
__host__ __device__ static constexpr bool IsStaticBuffer() { return true; }
T data_[N];
};
} // namespace ck } // namespace ck
#endif #endif
composable_kernel/include/utility/type.hpp
View file @ a037693f
...@@ -32,8 +32,15 @@ template <typename T> ...@@ -32,8 +32,15 @@ template <typename T>
inline constexpr bool is_pointer_v = std::is_pointer<T>::value; inline constexpr bool is_pointer_v = std::is_pointer<T>::value;
template <typename Y, typename X, typename enable_if<sizeof(X) == sizeof(Y), bool>::type = false> template <typename Y, typename X, typename enable_if<sizeof(X) == sizeof(Y), bool>::type = false>
__host__ __device__ constexpr Y as_type(X x) __host__ __device__ constexpr Y bit_cast(const X& x)
{ {
#if CK_EXPERIMENTAL_USE_MEMCPY_FOR_BIT_CAST
Y y;
__builtin_memcpy(&y, &x, sizeof(X));
return y;
#else
union AsType union AsType
{ {
X x; X x;
...@@ -41,6 +48,7 @@ __host__ __device__ constexpr Y as_type(X x) ...@@ -41,6 +48,7 @@ __host__ __device__ constexpr Y as_type(X x)
}; };
return AsType{x}.y; return AsType{x}.y;
#endif
} }
} // namespace ck } // namespace ck
......
example/1_gemm_xdl/gemm_xdl.cpp
View file @ a037693f
...@@ -9,7 +9,6 @@ ...@@ -9,7 +9,6 @@
#include "device.hpp" #include "device.hpp"
#include "host_tensor.hpp" #include "host_tensor.hpp"
#include "host_tensor_generator.hpp" #include "host_tensor_generator.hpp"
#include "gemm_common.hpp"
#include "host_gemm.hpp" #include "host_gemm.hpp"
#include "device_tensor.hpp" #include "device_tensor.hpp"
#include "device_base.hpp" #include "device_base.hpp"
...@@ -139,12 +138,12 @@ int main(int argc, char* argv[]) ...@@ -139,12 +138,12 @@ int main(int argc, char* argv[])
{ {
case 0: break; case 0: break;
case 1: case 1:
a_m_k.GenerateTensorValue(GeneratorTensor_2{-5, 5}); a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
b_k_n.GenerateTensorValue(GeneratorTensor_2{-5, 5}); b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
break; break;
default: default:
a_m_k.GenerateTensorValue(GeneratorTensor_3<float>{0.0, 1.0}); a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
b_k_n.GenerateTensorValue(GeneratorTensor_3<float>{-0.5, 0.5}); b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
} }
DeviceMem a_m_k_device_buf(sizeof(ADataType) * a_m_k.mDesc.GetElementSpace()); DeviceMem a_m_k_device_buf(sizeof(ADataType) * a_m_k.mDesc.GetElementSpace());
......
host/driver_offline/CMakeLists.txt
View file @ a037693f
...@@ -13,16 +13,25 @@ include_directories(BEFORE ...@@ -13,16 +13,25 @@ include_directories(BEFORE
) )
set(CONV_FWD_DRIVER_OFFLINE_SOURCE src/conv_fwd_driver_offline.cpp) set(CONV_FWD_DRIVER_OFFLINE_SOURCE src/conv_fwd_driver_offline.cpp)
set(CONV_FWD_DRIVER_OFFLINE_NCHWC_SOURCE src/conv_fwd_driver_offline_nchwc.cpp)
set(CONV_ADD_FWD_DRIVER_OFFLINE_NCHWC_SOURCE src/conv_add_fwd_driver_offline_nchwc.cpp)
set(CONV_MAXPOOL_FWD_DRIVER_OFFLINE_NCHWC_SOURCE src/conv_maxpool_fwd_driver_offline_nchwc.cpp)
set(CONV_BWD_DRIVER_OFFLINE_SOURCE src/conv_bwd_driver_offline.cpp) set(CONV_BWD_DRIVER_OFFLINE_SOURCE src/conv_bwd_driver_offline.cpp)
set(CONV_WRW_DRIVER_OFFLINE_SOURCE src/conv_wrw_driver_offline.cpp) set(CONV_WRW_DRIVER_OFFLINE_SOURCE src/conv_wrw_driver_offline.cpp)
set(GEMM_DRIVER_OFFLINE_SOURCE src/gemm_driver_offline.cpp) set(GEMM_DRIVER_OFFLINE_SOURCE src/gemm_driver_offline.cpp)
add_executable(conv_fwd_driver_offline ${CONV_FWD_DRIVER_OFFLINE_SOURCE}) add_executable(conv_fwd_driver_offline ${CONV_FWD_DRIVER_OFFLINE_SOURCE})
add_executable(conv_fwd_driver_offline_nchwc ${CONV_FWD_DRIVER_OFFLINE_NCHWC_SOURCE})
add_executable(conv_add_fwd_driver_offline_nchwc ${CONV_ADD_FWD_DRIVER_OFFLINE_NCHWC_SOURCE})
add_executable(conv_maxpool_fwd_driver_offline_nchwc ${CONV_MAXPOOL_FWD_DRIVER_OFFLINE_NCHWC_SOURCE})
add_executable(conv_bwd_driver_offline ${CONV_BWD_DRIVER_OFFLINE_SOURCE}) add_executable(conv_bwd_driver_offline ${CONV_BWD_DRIVER_OFFLINE_SOURCE})
add_executable(conv_wrw_driver_offline ${CONV_WRW_DRIVER_OFFLINE_SOURCE}) add_executable(conv_wrw_driver_offline ${CONV_WRW_DRIVER_OFFLINE_SOURCE})
add_executable(gemm_driver_offline ${GEMM_DRIVER_OFFLINE_SOURCE}) add_executable(gemm_driver_offline ${GEMM_DRIVER_OFFLINE_SOURCE})
target_link_libraries(conv_fwd_driver_offline PRIVATE host_tensor) target_link_libraries(conv_fwd_driver_offline PRIVATE host_tensor)
target_link_libraries(conv_fwd_driver_offline_nchwc PRIVATE host_tensor)
target_link_libraries(conv_add_fwd_driver_offline_nchwc PRIVATE host_tensor)
target_link_libraries(conv_maxpool_fwd_driver_offline_nchwc PRIVATE host_tensor)
target_link_libraries(conv_bwd_driver_offline PRIVATE host_tensor) target_link_libraries(conv_bwd_driver_offline PRIVATE host_tensor)
target_link_libraries(conv_wrw_driver_offline PRIVATE host_tensor) target_link_libraries(conv_wrw_driver_offline PRIVATE host_tensor)
target_link_libraries(gemm_driver_offline PRIVATE host_tensor) target_link_libraries(gemm_driver_offline PRIVATE host_tensor)
host/driver_offline/include/device_convolution_add_forward_implicit_gemm_v5r1_dlops_nc0hwc1_kc0yxc1_nk0hwk1.hpp 0 → 100644
View file @ a037693f
#include <unistd.h>
#include "device.hpp"
#include "host_tensor.hpp"
#include "driver_convolution_add_forward_implicit_gemm_v5r1_dlops_nc0hwc1_kc0yxc1_nk0hwk1.hpp"
template <typename TInWei,
typename TAcc,
typename TOut,
ck::ActivTypeEnum_t activ_type,
typename InLengths,
typename WeiLengths,
typename AddLengths,
typename OutLengths,
typename ConvStrides,
typename ConvDilations,
typename InLeftPads,
typename InRightPads>
void device_convolution_add_forward_implicit_gemm_v5r1_dlops_nc0hwc1_kc0yxc1_nk0hwk1(
const InLengths& in_n_c0_hi_wi_c1_lengths,
const WeiLengths& wei_k_c0_y_x_c1_lengths,
const AddLengths& add_n_k0_hox2_wox2_k1_lengths,
const OutLengths& out_n_k0_ho_wo_k1_lengths,
const ConvStrides& conv_strides,
const ConvDilations& conv_dilations,
const InLeftPads& in_left_pads,
const InRightPads& in_right_pads,
const Tensor<TInWei>& in_n_c0_hi_wi_c1,
const Tensor<TInWei>& wei_k_c0_y_x_c1,
const Tensor<TOut>& bias_k0_k1,
const Tensor<TOut>& add_n_k0_hox2_wox2_k1,
Tensor<TOut>& add_n_k0_hox2_wox2_k1_out,
ck::index_t nrepeat)
{
using namespace ck;
std::cout << __func__ << std::endl;
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto I4 = Number<4>{};
const auto N = out_n_k0_ho_wo_k1_lengths[I0];
const auto K0 = out_n_k0_ho_wo_k1_lengths[I1];
const auto Ho = out_n_k0_ho_wo_k1_lengths[I2];
const auto Wo = out_n_k0_ho_wo_k1_lengths[I3];
const auto K1 = out_n_k0_ho_wo_k1_lengths[I4];
const auto C0 = in_n_c0_hi_wi_c1_lengths[I1];
const auto Hi = in_n_c0_hi_wi_c1_lengths[I2];
const auto Wi = in_n_c0_hi_wi_c1_lengths[I3];
const auto C1 = in_n_c0_hi_wi_c1_lengths[I4];
const auto K = wei_k_c0_y_x_c1_lengths[I0];
const auto Y = wei_k_c0_y_x_c1_lengths[I2];
const auto X = wei_k_c0_y_x_c1_lengths[I3];
const auto Hox2 = add_n_k0_hox2_wox2_k1_lengths[I2];
const auto Wox2 = add_n_k0_hox2_wox2_k1_lengths[I3];
DeviceMem in_n_c0_hi_wi_c1_device_buf(sizeof(TInWei) *
in_n_c0_hi_wi_c1.mDesc.GetElementSpace());
DeviceMem wei_k_c0_y_x_c1_device_buf(sizeof(TInWei) * wei_k_c0_y_x_c1.mDesc.GetElementSpace());
DeviceMem bias_k0_k1_device_buf(sizeof(TOut) * bias_k0_k1.mDesc.GetElementSpace());
DeviceMem add_n_k0_hox2_wox2_k1_device_buf(sizeof(TOut) *
add_n_k0_hox2_wox2_k1.mDesc.GetElementSpace());
in_n_c0_hi_wi_c1_device_buf.ToDevice(in_n_c0_hi_wi_c1.mData.data());
wei_k_c0_y_x_c1_device_buf.ToDevice(wei_k_c0_y_x_c1.mData.data());
bias_k0_k1_device_buf.ToDevice(bias_k0_k1.mData.data());
add_n_k0_hox2_wox2_k1_device_buf.ToDevice(add_n_k0_hox2_wox2_k1.mData.data());
constexpr index_t InWeiVectorSize = 8;
if(C1 % InWeiVectorSize != 0)
{
throw std::runtime_error("wrong! C1 cannot be divided by InWeiVectorSize");
}
#if 0
constexpr index_t BlockSize = 256;
constexpr index_t KPerBlock = 32;
constexpr index_t HoPerBlock = 8;
constexpr index_t WoPerBlock = 64;
constexpr index_t E1 = C0 * 9;
constexpr index_t E2 = 1;
constexpr index_t E1PerBlock = C0;
constexpr index_t KPerThread = 16;
constexpr index_t HoPerThread = 2;
constexpr index_t WoPerThread = 2;
constexpr index_t EPerThread = 1;
using ABlockTransferThreadSliceLengths_E0_E1_K0_K1_E2 = Sequence<1, 9, 1, E2>;
using ABlockTransferThreadClusterLengths_E0_E1_K0_K1_E2 = Sequence<1, E1PerBlock, KPerBlock, 1>;
constexpr index_t ABlockTransferSrcScalarPerVector_E2 = E2;
constexpr index_t ABlockTransferDstScalarPerVector_E2 = E2;
constexpr index_t BThreadTransferSrcScalarPerVector_E2 = E2;
constexpr index_t CThreadTransferDstScalarPerVector_K = K1;
#elif 1
constexpr auto BlockSize = 64;
constexpr auto KPerBlock = 8;
constexpr auto HoPerBlock = 8;
constexpr auto WoPerBlock = 32;
constexpr auto E1 = 2 * 9;
constexpr auto E2 = 1;
constexpr auto K2 = 2;
constexpr auto E1PerBlock = 2;
constexpr auto KPerThread = KPerBlock;
constexpr auto HoPerThread = 2;
constexpr auto WoPerThread = 2;
constexpr auto EPerThread = 1;
using ABlockTransferThreadSliceLengths_E0_E1_K0_K1_E2 = Sequence<1, 9, 1, 1, E2>;
using ABlockTransferThreadClusterLengths_E0_E1_K0_K1_E2 =
Sequence<1, E1PerBlock, 1, KPerBlock, 1>;
constexpr auto ABlockTransferSrcScalarPerVector_E2 = E2;
constexpr auto ABlockTransferDstScalarPerVector_E2 = E2;
constexpr auto BThreadTransferSrcScalarPerVector_E2 = E2;
constexpr auto CThreadTransferDstScalarPerVector_K = InWeiVectorSize;
#endif
const auto in_n_c0_hi_wi_c1_desc =
make_naive_tensor_descriptor_packed(make_tuple(N, C0, Hi, Wi, E2));
const auto wei_k_c0_y_x_c1_desc =
make_naive_tensor_descriptor_packed(make_tuple(K, C0, Y, X, E2));
const auto add_n_k0_hox2_wox2_k1_desc =
make_naive_tensor_descriptor_packed(make_tuple(N, K0, Hox2, Wox2, K1));
const auto out_n_k0_ho_wo_k1_desc =
make_naive_tensor_descriptor_packed(make_tuple(N, K0, Ho, Wo, K1));
constexpr auto conv_driver =
DriverDynamicConvolutionForwardImplicitGemmDlops_v5r1_nc0hwc1_kc0yxc1_nk0hwk1_add<
BlockSize,
typename vector_type<TInWei, InWeiVectorSize>::type,
TAcc,
TOut,
E1,
E2,
K2,
KPerBlock,
HoPerBlock,
WoPerBlock,
E1PerBlock,
KPerThread,
HoPerThread,
WoPerThread,
EPerThread,
ABlockTransferThreadSliceLengths_E0_E1_K0_K1_E2,
ABlockTransferThreadClusterLengths_E0_E1_K0_K1_E2,
ABlockTransferSrcScalarPerVector_E2,
ABlockTransferDstScalarPerVector_E2,
BThreadTransferSrcScalarPerVector_E2,
CThreadTransferDstScalarPerVector_K,
activ_type>{};
std::cerr << "conv_bias_activ_resize_add_input_"
<< "n" << N << "c" << C0 << "h" << Hi << "w" << Wi << "c" << C1 << "_filter_k" << K
<< "c" << C0 << "y" << Y << "x" << X << "c" << C1 << "_addout_n" << N << "k" << K0
<< "h" << Ho * 2 << "w" << Wo * 2 << "k" << K1 << std::endl;
for(int i = 0; i < 5; i++)
{
const auto ave_time =
conv_driver.Run(wei_k_c0_y_x_c1_desc,
in_n_c0_hi_wi_c1_desc,
out_n_k0_ho_wo_k1_desc,
add_n_k0_hox2_wox2_k1_desc,
conv_strides,
conv_dilations,
in_left_pads,
in_right_pads,
static_cast<typename vector_type<TInWei, InWeiVectorSize>::type*>(
wei_k_c0_y_x_c1_device_buf.GetDeviceBuffer()),
static_cast<typename vector_type<TInWei, InWeiVectorSize>::type*>(
in_n_c0_hi_wi_c1_device_buf.GetDeviceBuffer()),
static_cast<TOut*>(bias_k0_k1_device_buf.GetDeviceBuffer()),
static_cast<TOut*>(add_n_k0_hox2_wox2_k1_device_buf.GetDeviceBuffer()),
nrepeat);
{
float perf = static_cast<float>(std::size_t(2) * N * K * Ho * Wo * C0 * C1 * Y * X) /
(std::size_t(1000) * 1000 * 1000) / ave_time;
std::cout << "Average time : " << ave_time << " ms, " << perf << " TFlop/s"
<< std::endl;
}
}
add_n_k0_hox2_wox2_k1_device_buf.ToDevice(add_n_k0_hox2_wox2_k1.mData.data());
conv_driver.Run(wei_k_c0_y_x_c1_desc,
in_n_c0_hi_wi_c1_desc,
out_n_k0_ho_wo_k1_desc,
add_n_k0_hox2_wox2_k1_desc,
conv_strides,
conv_dilations,
in_left_pads,
in_right_pads,
static_cast<typename vector_type<TInWei, InWeiVectorSize>::type*>(
wei_k_c0_y_x_c1_device_buf.GetDeviceBuffer()),
static_cast<typename vector_type<TInWei, InWeiVectorSize>::type*>(
in_n_c0_hi_wi_c1_device_buf.GetDeviceBuffer()),
static_cast<TOut*>(bias_k0_k1_device_buf.GetDeviceBuffer()),
static_cast<TOut*>(add_n_k0_hox2_wox2_k1_device_buf.GetDeviceBuffer()),
0);
add_n_k0_hox2_wox2_k1_device_buf.FromDevice(add_n_k0_hox2_wox2_k1_out.mData.data());
}
host/driver_offline/include/device_convolution_forward_implicit_gemm_v5r1_dlops_nc0hwc1_kc0yxc1_nk0hwk1.hpp 0 → 100644
View file @ a037693f
#include <unistd.h>
#include "device.hpp"
#include "host_tensor.hpp"
#include "driver_convolution_forward_implicit_gemm_v5r1_dlops_nc0hwc1_kc0yxc1_nk0hwk1.hpp"
template <typename TInWei,
typename TAcc,
typename TOut,
ck::ActivTypeEnum_t activ_type,
typename InLengths,
typename WeiLengths,
typename OutLengths,
typename ConvStrides,
typename ConvDilations,
typename InLeftPads,
typename InRightPads>
void device_convolution_forward_implicit_gemm_v5r1_dlops_nc0hwc1_kc0yxc1_nk0hwk1(
const InLengths& in_n_c0_hi_wi_c1_lengths,
const WeiLengths& wei_k_c0_y_x_c1_lengths,
const OutLengths& out_n_k0_ho_wo_k1_lengths,
const ConvStrides& conv_strides,
const ConvDilations& conv_dilations,
const InLeftPads& in_left_pads,
const InRightPads& in_right_pads,
const Tensor<TInWei>& in_n_c0_hi_wi_c1,
const Tensor<TInWei>& wei_k_c0_y_x_c1,
const Tensor<TOut>& bias_k0_k1,
Tensor<TOut>& out_n_k0_ho_wo_k1,
ck::index_t nrepeat)
{
using namespace ck;
std::cout << __func__ << std::endl;
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
constexpr auto I4 = Number<4>{};
const auto N = out_n_k0_ho_wo_k1_lengths[I0];
const auto K0 = out_n_k0_ho_wo_k1_lengths[I1];
const auto Ho = out_n_k0_ho_wo_k1_lengths[I2];
const auto Wo = out_n_k0_ho_wo_k1_lengths[I3];
const auto K1 = out_n_k0_ho_wo_k1_lengths[I4];
const auto C0 = in_n_c0_hi_wi_c1_lengths[I1];
const auto Hi = in_n_c0_hi_wi_c1_lengths[I2];
const auto Wi = in_n_c0_hi_wi_c1_lengths[I3];
const auto C1 = in_n_c0_hi_wi_c1_lengths[I4];
const auto K = wei_k_c0_y_x_c1_lengths[I0];
const auto Y = wei_k_c0_y_x_c1_lengths[I2];
const auto X = wei_k_c0_y_x_c1_lengths[I3];
DeviceMem in_n_c0_hi_wi_c1_device_buf(sizeof(TInWei) *
in_n_c0_hi_wi_c1.mDesc.GetElementSpace());
DeviceMem wei_k_c0_y_x_c1_device_buf(sizeof(TInWei) * wei_k_c0_y_x_c1.mDesc.GetElementSpace());
DeviceMem bias_k0_k1_device_buf(sizeof(TOut) * bias_k0_k1.mDesc.GetElementSpace());
DeviceMem out_n_k0_ho_wo_k1_device_buf(sizeof(TOut) *
out_n_k0_ho_wo_k1.mDesc.GetElementSpace());
in_n_c0_hi_wi_c1_device_buf.ToDevice(in_n_c0_hi_wi_c1.mData.data());
wei_k_c0_y_x_c1_device_buf.ToDevice(wei_k_c0_y_x_c1.mData.data());
bias_k0_k1_device_buf.ToDevice(bias_k0_k1.mData.data());
constexpr index_t InWeiVectorSize = 8;
if(C1 % InWeiVectorSize != 0)
{
throw std::runtime_error("wrong! C1 cannot be divided by InWeiVectorSize");
}
#if 0
constexpr index_t BlockSize = 256;
constexpr index_t KPerBlock = 32;
constexpr index_t HoPerBlock = 8;
constexpr index_t WoPerBlock = 64;
constexpr index_t E1 = C0 * 9;
constexpr index_t E2 = 1;
constexpr index_t E1PerBlock = C0;
constexpr index_t KPerThread = 16;
constexpr index_t HoPerThread = 2;
constexpr index_t WoPerThread = 2;
constexpr index_t EPerThread = 1;
using ABlockTransferThreadSliceLengths_E0_E1_K0_K1_E2 = Sequence<1, 9, 1, E2>;
using ABlockTransferThreadClusterLengths_E0_E1_K0_K1_E2 = Sequence<1, E1PerBlock, KPerBlock, 1>;
constexpr index_t ABlockTransferSrcScalarPerVector_E2 = E2;
constexpr index_t ABlockTransferDstScalarPerVector_E2 = E2;
constexpr index_t BThreadTransferSrcScalarPerVector_E2 = E2;
constexpr index_t CThreadTransferDstScalarPerVector_K = K1;
#elif 1
constexpr index_t BlockSize = 64;
constexpr index_t KPerBlock = 8;
constexpr index_t HoPerBlock = 8;
constexpr index_t WoPerBlock = 32;
constexpr index_t E1 = 2 * 9;
constexpr index_t E2 = 1;
constexpr index_t K2 = 2;
constexpr index_t E1PerBlock = 2;
constexpr index_t KPerThread = KPerBlock;
constexpr index_t HoPerThread = 2;
constexpr index_t WoPerThread = 2;
constexpr index_t EPerThread = 1;
using ABlockTransferThreadSliceLengths_E0_E1_K0_K1_E2 = Sequence<1, 9, 1, 1, E2>;
using ABlockTransferThreadClusterLengths_E0_E1_K0_K1_E2 =
Sequence<1, E1PerBlock, 1, KPerBlock, 1>;
constexpr index_t ABlockTransferSrcScalarPerVector_E2 = E2;
constexpr index_t ABlockTransferDstScalarPerVector_E2 = E2;
constexpr index_t BThreadTransferSrcScalarPerVector_E2 = E2;
constexpr index_t CThreadTransferDstScalarPerVector_K = InWeiVectorSize;
#endif
if(KPerThread % InWeiVectorSize != 0)
{
throw std::runtime_error("wrong! C1 cannot be divided by InWeiVectorSize");
}
const auto in_n_c0_hi_wi_c1_desc =
make_naive_tensor_descriptor_packed(make_tuple(N, C0, Hi, Wi, E2));
const auto wei_k_c0_y_x_c1_desc =
make_naive_tensor_descriptor_packed(make_tuple(K, C0, Y, X, E2));
const auto out_n_k0_ho_wo_k1_desc =
make_naive_tensor_descriptor_packed(make_tuple(N, K0, Ho, Wo, K1));
constexpr auto conv_driver =
DriverDynamicConvolutionForwardImplicitGemmDlops_v5r1_nc0hwc1_kc0yxc1_nk0hwk1_outpad<
BlockSize,
typename vector_type<TInWei, InWeiVectorSize>::type,
TAcc,
TOut,
E1,
E2,
K2,
KPerBlock,
HoPerBlock,
WoPerBlock,
E1PerBlock,
KPerThread,
HoPerThread,
WoPerThread,
EPerThread,
ABlockTransferThreadSliceLengths_E0_E1_K0_K1_E2,
ABlockTransferThreadClusterLengths_E0_E1_K0_K1_E2,
ABlockTransferSrcScalarPerVector_E2,
ABlockTransferDstScalarPerVector_E2,
BThreadTransferSrcScalarPerVector_E2,
CThreadTransferDstScalarPerVector_K,
activ_type>{};
std::cerr << "conv_bias_activ_input_"
<< "n" << N << "c" << C0 << "h" << Hi << "w" << Wi << "c" << C1 << "_filter_k" << K
<< "c" << C0 << "y" << Y << "x" << X << "c" << C1 << "_convout_n" << N << "k" << K0
<< "h" << Ho << "w" << Wo << "k" << K1 << std::endl;
for(int i = 0; i < 5; i++)
{
const auto ave_time =
conv_driver.Run(wei_k_c0_y_x_c1_desc,
in_n_c0_hi_wi_c1_desc,
out_n_k0_ho_wo_k1_desc,
conv_strides,
conv_dilations,
in_left_pads,
in_right_pads,
static_cast<typename vector_type<TInWei, InWeiVectorSize>::type*>(
wei_k_c0_y_x_c1_device_buf.GetDeviceBuffer()),
static_cast<typename vector_type<TInWei, InWeiVectorSize>::type*>(
in_n_c0_hi_wi_c1_device_buf.GetDeviceBuffer()),
static_cast<TOut*>(bias_k0_k1_device_buf.GetDeviceBuffer()),
static_cast<TOut*>(out_n_k0_ho_wo_k1_device_buf.GetDeviceBuffer()),
nrepeat);
{
float perf = static_cast<float>(std::size_t(2) * N * K * Ho * Wo * C0 * C1 * Y * X) /
(std::size_t(1000) * 1000 * 1000) / ave_time;
std::cout << "Average time : " << ave_time << " ms, " << perf << " TFlop/s"
<< std::endl;
}
}
out_n_k0_ho_wo_k1_device_buf.FromDevice(out_n_k0_ho_wo_k1.mData.data());
}
host/driver_offline/include/device_convolution_forward_implicit_gemm_v5r1_dlops_nchw_kcyx_nkhw.hpp deleted 100644 → 0
View file @ 0694d6ed
#include <unistd.h>
#include "device.hpp"
#include "host_tensor.hpp"
#include "driver_convolution_forward_implicit_gemm_v5r1_dlops_nchw_kcyx_nkhw.hpp"
#include "driver_convolution_forward_implicit_gemm_v5r1_dlops_nchw_kcyx_nkhw_outpad.hpp"
template <typename TInWei,
ck::index_t InWeiVectorSize,
typename TAcc,
typename TOut,
typename InLengths,
typename WeiLengths,
typename OutLengths,
typename ConvStrides,
typename ConvDilations,
typename InLeftPads,
typename InRightPads>
void device_convolution_forward_implicit_gemm_v5r1_dlops_nchw_kcyx_nkhw(
const InLengths& in_n_c_hi_wi_lengths,
const WeiLengths& wei_k_c_y_x_lengths,
const OutLengths& out_n_k_ho_wo_lengths,
const ConvStrides& conv_strides,
const ConvDilations& conv_dilations,
const InLeftPads& in_left_pads,
const InRightPads& in_right_pads,
const Tensor<TInWei>& in_n_c_hi_wi,
const Tensor<TInWei>& wei_k_c_y_x,
Tensor<TOut>& out_n_k_ho_wo,
ck::index_t /* nrepeat */)
{
using namespace ck;
std::cout << __func__ << std::endl;
constexpr auto I0 = Number<0>{};
constexpr auto I1 = Number<1>{};
constexpr auto I2 = Number<2>{};
constexpr auto I3 = Number<3>{};
const auto N = out_n_k_ho_wo_lengths[I0];
const auto K = out_n_k_ho_wo_lengths[I1];
const auto C = wei_k_c_y_x_lengths[I1];
const auto Hi = in_n_c_hi_wi_lengths[I2];
const auto Wi = in_n_c_hi_wi_lengths[I3];
const auto Ho = out_n_k_ho_wo_lengths[I2];
const auto Wo = out_n_k_ho_wo_lengths[I3];
const auto Y = wei_k_c_y_x_lengths[I2];
const auto X = wei_k_c_y_x_lengths[I3];
const auto C0 = C / Number<InWeiVectorSize>{};
const auto C1 = Number<InWeiVectorSize>{};
const auto K0 = K / Number<InWeiVectorSize>{};
const auto K1 = Number<InWeiVectorSize>{};
Tensor<TInWei> in_n_c0_hi_wi_c1(
HostTensorDescriptor(std::initializer_list<index_t>{N, C0, Hi, Wi, C1}));
Tensor<TInWei> wei_k_c0_y_x_c1(
HostTensorDescriptor(std::initializer_list<index_t>{K, C0, Y, X, C1}));
Tensor<TOut> out_n_k0_ho_wo_k1(
HostTensorDescriptor(std::initializer_list<index_t>{N, K0, Ho, Wo, K1}));
auto f_nchw2nc0hwc1 = [&](auto n, auto hi, auto wi, auto c) {
in_n_c0_hi_wi_c1(n, c / InWeiVectorSize, hi, wi, c % InWeiVectorSize) =
in_n_c_hi_wi(n, c, hi, wi);
};
auto f_kcyx2kc0yxc1 = [&](auto k, auto y, auto x, auto c) {
wei_k_c0_y_x_c1(k, c / InWeiVectorSize, y, x, c % InWeiVectorSize) =
wei_k_c_y_x(k, c, y, x);
};
make_ParallelTensorFunctor(f_nchw2nc0hwc1, N, Hi, Wi, C)();
make_ParallelTensorFunctor(f_kcyx2kc0yxc1, K, Y, X, C)();
DeviceMem in_n_c0_hi_wi_c1_device_buf(sizeof(TInWei) *
in_n_c0_hi_wi_c1.mDesc.GetElementSpace());
DeviceMem wei_k_c0_y_x_c1_device_buf(sizeof(TInWei) * wei_k_c0_y_x_c1.mDesc.GetElementSpace());
DeviceMem out_n_k0_ho_wo_k1_device_buf(sizeof(TOut) *
out_n_k0_ho_wo_k1.mDesc.GetElementSpace());
in_n_c0_hi_wi_c1_device_buf.ToDevice(in_n_c0_hi_wi_c1.mData.data());
wei_k_c0_y_x_c1_device_buf.ToDevice(wei_k_c0_y_x_c1.mData.data());
const auto in_n_c0_hi_wi_desc = make_naive_tensor_descriptor_packed(make_tuple(N, C0, Hi, Wi));
const auto wei_k_c0_y_x_desc = make_naive_tensor_descriptor_packed(make_tuple(K, C0, Y, X));
const auto out_n_k0_ho_wo_k1_desc =
make_naive_tensor_descriptor_packed(make_tuple(N, K0, Ho, Wo, K1));
#if 1
// cdata = 64, BlockSize = 64, 16x8x32x4
constexpr index_t BlockSize = 64;
constexpr index_t KPerBlock = 16;
constexpr index_t HoPerBlock = 8;
constexpr index_t WoPerBlock = 32;
constexpr index_t EPerBlock = 1;
constexpr index_t KPerThread = KPerBlock;
constexpr index_t HoPerThread = 2;
constexpr index_t WoPerThread = 2;
constexpr index_t EPerThread = EPerBlock;
using ABlockTransferThreadSliceLengths_E_K = Sequence<3, 1>;
using ABlockTransferThreadClusterLengths_E_K = Sequence<3 * EPerBlock, KPerBlock>;
constexpr index_t ABlockTransferSrcScalarPerVector_E = 1;
constexpr index_t ABlockTransferDstScalarPerVector_K = 1;
constexpr index_t BThreadTransferSrcScalarPerVector_W = 1;
constexpr index_t CThreadTransferDstScalarPerVector_W = 16;
static_assert(KPerThread % CThreadTransferDstScalarPerVector_W == 0, "");
#else
constexpr index_t BlockSize = 64;
constexpr index_t KPerBlock = 16;
constexpr index_t HoPerBlock = 8;
constexpr index_t WoPerBlock = 32;
constexpr index_t EPerBlock = 1;
constexpr index_t KPerThread = 16;
constexpr index_t HoPerThread = 2;
constexpr index_t WoPerThread = 2;
constexpr index_t EPerThread = EPerBlock;
using ABlockTransferThreadSliceLengths_E_K = Sequence<9, 1>;
using ABlockTransferThreadClusterLengths_E_K = Sequence<EPerBlock, 16>;
constexpr index_t ABlockTransferSrcScalarPerVector_E = 1;
constexpr index_t ABlockTransferDstScalarPerVector_K = 1;
constexpr index_t BThreadTransferSrcScalarPerVector_W = 1;
constexpr index_t CThreadTransferDstScalarPerVector_W = K1;
static_assert(KPerThread % CThreadTransferDstScalarPerVector_W == 0, "");
#endif
constexpr auto conv_driver =
#if 0
DriverDynamicConvolutionForwardImplicitGemmDlops_v5r1_nchw_kcyx_nkhw_pad
#else
DriverDynamicConvolutionForwardImplicitGemmDlops_v5r1_nchw_kcyx_nkhw_outpad
#endif
<BlockSize,
typename vector_type<TInWei, InWeiVectorSize>::type,
TAcc,
TOut,
KPerBlock,
HoPerBlock,
WoPerBlock,
EPerBlock,
KPerThread,
HoPerThread,
WoPerThread,
EPerThread,
ABlockTransferThreadSliceLengths_E_K,
ABlockTransferThreadClusterLengths_E_K,
ABlockTransferSrcScalarPerVector_E,
ABlockTransferDstScalarPerVector_K,
BThreadTransferSrcScalarPerVector_W,
CThreadTransferDstScalarPerVector_W>{};
conv_driver.Run(wei_k_c0_y_x_desc,
in_n_c0_hi_wi_desc,
out_n_k0_ho_wo_k1_desc,
conv_strides,
conv_dilations,
in_left_pads,
in_right_pads,
static_cast<typename vector_type<TInWei, InWeiVectorSize>::type*>(
wei_k_c0_y_x_c1_device_buf.GetDeviceBuffer()),
static_cast<typename vector_type<TInWei, InWeiVectorSize>::type*>(
in_n_c0_hi_wi_c1_device_buf.GetDeviceBuffer()),
static_cast<TOut*>(out_n_k0_ho_wo_k1_device_buf.GetDeviceBuffer()));
out_n_k0_ho_wo_k1_device_buf.FromDevice(out_n_k0_ho_wo_k1.mData.data());
auto f_nk0hwk1_to_nkhw = [&](auto n, auto k, auto ho, auto wo) {
out_n_k_ho_wo(n, k, ho, wo) =
out_n_k0_ho_wo_k1(n, k / InWeiVectorSize, ho, wo, k % InWeiVectorSize);
};
make_ParallelTensorFunctor(f_nk0hwk1_to_nkhw, N, K, Ho, Wo)();
}
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