add fwd_driver_offline_nchwc

composable_kernel/include/utility/reduction_functions_binop.hpp

+/*******************************************************************************
+ *
+ * MIT License
+ *
+ * Copyright (c) 2020 Advanced Micro Devices, Inc.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ *
+ *******************************************************************************/
+#ifndef CK_REDUCTION_FUNCTIONS_BINOP_HPP
+#define CK_REDUCTION_FUNCTIONS_BINOP_HPP
+
+#include "data_type.hpp"
+
+#include "reduction_common.hpp"
+#include "reduction_operator.hpp"
+
+namespace ck {
+namespace detail {
+
+static inline __device__ bool isnan(half_t x) { return __hisnan(x); };
+
+template <NanPropagation_t nanPropaOpt, typename opReduce, typename compType>
+struct binop_with_nan_check;
+
+template <typename opReduce, typename compType>
+struct binop_with_nan_check<NanPropagation_t::NOT_PROPAGATE_NAN, opReduce, compType>
+{
+    // cppcheck-suppress constParameter
+    __device__ static inline void calculate(compType& accuVal, compType currVal)
+    {
+        opReduce{}(accuVal, currVal);
+    };
+
+    // The method is called when the opReduce is indexable and the user asked for indices
+    __device__ static inline void
+    // cppcheck-suppress constParameter
+    calculate(compType& accuVal, compType currVal, int& accuIndex, int currIndex)
+    {
+        bool changed = false;
+
+        opReduce{}(accuVal, currVal, changed);
+
+        if(changed)
+            accuIndex = currIndex;
+    };
+};
+
+template <typename opReduce, typename compType>
+struct binop_with_nan_check<NanPropagation_t::PROPAGATE_NAN, opReduce, compType>
+{
+    __device__ static inline void calculate(compType& accuVal, compType currVal)
+    {
+        if(isnan(currVal))
+            accuVal = currVal;
+        else
+            opReduce{}(accuVal, currVal);
+    };
+
+    // The method is called when the opReduce is indexable and the user asked for indices
+    __device__ static inline void
+    calculate(compType& accuVal, compType currVal, int& accuIndex, int currIndex)
+    {
+        if(isnan(currVal))
+        {
+            accuVal   = currVal;
+            accuIndex = currIndex;
+        }
+        else
+        {
+            bool changed = false;
+
+            opReduce{}(accuVal, currVal, changed);
+
+            if(changed)
+                accuIndex = currIndex;
+        }
+    };
+};
+
+}; // namespace detail
+}; // end of namespace ck
+
+#endif

composable_kernel/include/utility/static_buffer.hpp

@@ -55,6 +55,98 @@ struct StaticBuffer : public StaticallyIndexedArray<T, N>
     __host__ __device__ static constexpr bool IsDynamicBuffer() { return false; }
 };
 
+template <AddressSpaceEnum_t BufferAddressSpace,
+          typename T,
+          index_t N,
+          bool InvalidElementUseNumericalZeroValue>
+struct StaticBufferV2 : public StaticallyIndexedArray<T, N>
+{
+    using type = T;
+    using base = StaticallyIndexedArray<T, N>;
+
+    using VecBaseType = typename T::d1_t;
+
+    __host__ __device__ static constexpr index_t GetVectorSize()
+    {
+        return sizeof(typename T::type) / sizeof(VecBaseType);
+    }
+
+    static constexpr index_t vector_size = GetVectorSize();
+
+    VecBaseType invalid_element_value_ = VecBaseType{0};
+
+    T invalid_vec_value_ = T{0};
+
+    __host__ __device__ constexpr StaticBufferV2() : base{} {}
+
+    __host__ __device__ constexpr StaticBufferV2(VecBaseType invalid_element_value)
+        : base{},
+          invalid_vec_value_{invalid_element_value},
+          invalid_element_value_{invalid_element_value}
+    {
+    }
+
+    __host__ __device__ static constexpr AddressSpaceEnum_t GetAddressSpace()
+    {
+        return BufferAddressSpace;
+    }
+
+    template <index_t I>
+    __host__ __device__ constexpr auto& GetVector(Number<I> vec_id)
+    {
+        return this->At(vec_id);
+    }
+
+    template <index_t I>
+    __host__ __device__ constexpr const auto& GetVector(Number<I> vec_id) const
+    {
+        return this->At(vec_id);
+    }
+
+    template <index_t I>
+    __host__ __device__ constexpr auto& GetElement(Number<I> i, bool)
+    {
+        constexpr auto vec_id  = Number<i / vector_size>{};
+        constexpr auto vec_off = Number<i % vector_size>{};
+
+        return this->At(vec_id).template AsType<VecBaseType>()(vec_off);
+    }
+
+    template <index_t I>
+    __host__ __device__ constexpr auto GetElement(Number<I> i, bool is_valid_element) const
+    {
+        constexpr auto vec_id  = Number<i / vector_size>{};
+        constexpr auto vec_off = Number<i % vector_size>{};
+
+        if constexpr(InvalidElementUseNumericalZeroValue)
+        {
+            return is_valid_element ? this->At(vec_id).template AsType<VecBaseType>()[vec_off]
+                                    : VecBaseType{0};
+        }
+        else
+        {
+            return is_valid_element ? this->At(vec_id).template AsType<VecBaseType>()[vec_off]
+                                    : invalid_element_value_;
+        }
+    }
+
+    template <index_t I>
+    __host__ __device__ constexpr auto operator[](Number<I> i) const
+    {
+        return GetElement(i, true);
+    }
+
+    template <index_t I>
+    __host__ __device__ constexpr auto& operator()(Number<I> i)
+    {
+        return GetElement(i, true);
+    }
+
+    __host__ __device__ static constexpr bool IsStaticBuffer() { return true; }
+
+    __host__ __device__ static constexpr bool IsDynamicBuffer() { return false; }
+};
+
 template <AddressSpaceEnum_t BufferAddressSpace, typename T, index_t N>
 __host__ __device__ constexpr auto make_static_buffer(Number<N>)
 {

composable_kernel/src/kernel_wrapper/gridwise_generic_reduction_first_call_blockwise_reduce_all_dims.cpp

+/*******************************************************************************
+ *
+ * MIT License
+ *
+ * Copyright (c) 2021 Advanced Micro Devices, Inc.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ *
+ *******************************************************************************/
+#include "config.hpp"
+#include "number.hpp"
+#include "sequence.hpp"
+#include "tensor_descriptor_helper.hpp"
+#include "data_type_enum_helper.hpp"
+#include "reduction_common.hpp"
+#include "gridwise_generic_2d_reduction_blockwise.hpp"
+
+using namespace ck;
+
+using srcDataType =
+    typename get_datatype_from_enum<static_cast<DataTypeEnum_t>(CK_PARAM_SRC_DATATYPE)>::type;
+using dstDataType =
+    typename get_datatype_from_enum<static_cast<DataTypeEnum_t>(CK_PARAM_DST_DATATYPE)>::type;
+using compType =
+    typename get_datatype_from_enum<static_cast<DataTypeEnum_t>(CK_PARAM_REDUCE_COMPTYPE)>::type;
+
+constexpr index_t BlockSize = CK_PARAM_BLOCKSIZE; // tunable
+
+constexpr index_t srcDims = CK_PARAM_IN_DIMS;
+
+constexpr ReduceTensorOp_t op          = static_cast<ReduceTensorOp_t>(CK_PARAM_REDUCE_OP);
+constexpr NanPropagation_t nanPropaOpt = CK_PARAM_NAN_PROPAGATE == 0
+                                             ? NanPropagation_t::NOT_PROPAGATE_NAN
+                                             : NanPropagation_t::PROPAGATE_NAN;
+constexpr ReduceTensorIndices_t reduceIndicesOpt = CK_PARAM_REDUCE_INDICES == 0
+                                                       ? ReduceTensorIndices_t::NO_INDICES
+                                                       : ReduceTensorIndices_t::FLATTENED_INDICES;
+
+constexpr bool src2d_need_padding = static_cast<bool>(CK_PARAM_SRC2D_PADDING);
+constexpr bool dst1d_need_padding = static_cast<bool>(CK_PARAM_DST1D_PADDING);
+
+constexpr bool indexable    = reduce_binary_operator<compType, op>::indexable;
+constexpr bool need_indices = indexable && (reduceIndicesOpt != ReduceTensorIndices_t::NO_INDICES);
+
+constexpr index_t GredAccessesPerThreadInBlock = CK_PARAM_ACCESSES_PER_THREAD_INBLOCK; // tunable
+
+// helper functions using variadic template arguments
+template <index_t... Ns>
+__device__ static auto make_tuple_from_array_and_index_seq(const int* lengths, Sequence<Ns...>)
+{
+    return make_tuple(static_cast<index_t>(lengths[Ns])...);
+};
+
+template <index_t arraySize>
+__device__ static auto make_tuple_from_array(const int* lengths, Number<arraySize>)
+{
+    static_assert(arraySize >= 1 && arraySize <= 6, "The tensor should have 1 to 6 dimensions");
+
+    constexpr auto index_seq = typename arithmetic_sequence_gen<0, arraySize, 1>::type{};
+
+    return make_tuple_from_array_and_index_seq(lengths, index_seq);
+};
+
+template <index_t... Ns>
+__device__ static constexpr auto make_tuple_from_seq(Sequence<Ns...>)
+{
+    return make_tuple(Ns...);
+};
+
+extern "C" __global__ void gridwise_generic_reduce_1_prepare(int GridSize,
+                                                             int BlkGroupSize,
+                                                             int inLength0,
+                                                             int inLength1,
+                                                             int inLength2,
+                                                             int inLength3,
+                                                             int inLength4,
+                                                             int inLength5,
+                                                             int inStride0,
+                                                             int inStride1,
+                                                             int inStride2,
+                                                             int inStride3,
+                                                             int inStride4,
+                                                             int inStride5,
+                                                             void* __restrict__ ws_global)
+{
+    (void)GridSize;
+    (void)BlkGroupSize;
+
+    void* p_src2dDesc = ws_global;
+    void* p_dst1dDesc = static_cast<char*>(ws_global) + 2048;
+
+    const int srcLengths[6] = {inLength0, inLength1, inLength2, inLength3, inLength4, inLength5};
+    const int srcStrides[6] = {inStride0, inStride1, inStride2, inStride3, inStride4, inStride5};
+
+    const auto tupleSrcLengths = make_tuple_from_array(srcLengths, Number<srcDims>{});
+    const auto tupleSrcStrides = make_tuple_from_array(srcStrides, Number<srcDims>{});
+    const auto tupleDstLengths = make_tuple(1);
+    const auto tupleDstStrides = make_tuple(1);
+
+    const auto srcDesc = make_naive_tensor_descriptor(tupleSrcLengths, tupleSrcStrides);
+    auto dstDesc       = make_naive_tensor_descriptor(tupleDstLengths, tupleDstStrides);
+
+    const auto one_dim_srcDesc = transform_tensor_descriptor(
+        srcDesc,
+        make_tuple(make_merge_transform(tupleSrcLengths)),
+        make_tuple(typename arithmetic_sequence_gen<0, srcDims, 1>::type{}),
+        make_tuple(Sequence<0>{}));
+
+    auto src2dDesc = transform_tensor_descriptor(
+        one_dim_srcDesc,
+        make_tuple(make_unmerge_transform(make_tuple(1, one_dim_srcDesc.GetLength(Number<0>{})))),
+        make_tuple(Sequence<0>{}),
+        make_tuple(Sequence<0, 1>{}));
+
+    constexpr int invariantLen = 1;
+    const auto toReduceLen     = src2dDesc.GetLength(Number<1>{});
+
+    constexpr auto copySliceLen = BlockSize * GredAccessesPerThreadInBlock;
+
+    if constexpr(src2d_need_padding)
+    {
+        const auto srcPad =
+            ((toReduceLen + copySliceLen - 1) / copySliceLen) * copySliceLen - toReduceLen;
+
+        auto src2dDesc_2 =
+            transform_tensor_descriptor(src2dDesc,
+                                        make_tuple(make_pass_through_transform(invariantLen),
+                                                   make_pad_transform(toReduceLen, 0, srcPad)),
+                                        make_tuple(Sequence<0>{}, Sequence<1>{}),
+                                        make_tuple(Sequence<0>{}, Sequence<1>{}));
+        if(get_thread_local_1d_id() == 0)
+            *static_cast<decltype(src2dDesc_2)*>(p_src2dDesc) = src2dDesc_2;
+    }
+    else
+    {
+        if(get_thread_local_1d_id() == 0)
+            *static_cast<decltype(src2dDesc)*>(p_src2dDesc) = src2dDesc;
+    }
+
+    if(get_thread_local_1d_id() == 0)
+        *static_cast<decltype(dstDesc)*>(p_dst1dDesc) = dstDesc;
+};
+
+template <index_t srcDims>
+struct get_ref_desc_types
+{
+    static constexpr auto ref_srcLengths = typename uniform_sequence_gen<srcDims, 8>::type{};
+
+    // don't have to use accurate strides to get an expected referrence type
+    static constexpr auto ref_srcDesc = make_naive_tensor_descriptor(
+        make_tuple_from_seq(ref_srcLengths), make_tuple_from_seq(ref_srcLengths));
+    static constexpr auto ref_dstDesc = make_naive_tensor_descriptor(make_tuple(1), make_tuple(1));
+
+    static constexpr auto ref_one_dim_srcDesc = transform_tensor_descriptor(
+        ref_srcDesc,
+        make_tuple(make_merge_transform(make_tuple_from_seq(ref_srcLengths))),
+        make_tuple(typename arithmetic_sequence_gen<0, srcDims, 1>::type{}),
+        make_tuple(Sequence<0>{}));
+
+    static constexpr auto ref_src2dDesc =
+        transform_tensor_descriptor(ref_one_dim_srcDesc,
+                                    make_tuple(make_unmerge_transform(
+                                        make_tuple(1, ref_one_dim_srcDesc.GetLength(Number<0>{})))),
+                                    make_tuple(Sequence<0>{}),
+                                    make_tuple(Sequence<0, 1>{}));
+
+    static constexpr auto ref_invariantLen = ref_src2dDesc.GetLength(Number<0>{});
+    static constexpr auto ref_toReduceLen  = ref_src2dDesc.GetLength(Number<1>{});
+
+    // used by the BlockWise and MultiBlock method
+    using refType_src2dDesc_padded_34 = decltype(
+        transform_tensor_descriptor(ref_src2dDesc,
+                                    make_tuple(make_pass_through_transform(ref_invariantLen),
+                                               make_pad_transform(ref_toReduceLen, 0, 2)),
+                                    make_tuple(Sequence<0>{}, Sequence<1>{}),
+                                    make_tuple(Sequence<0>{}, Sequence<1>{})));
+
+    using refType_dst1dDesc_padded =
+        decltype(transform_tensor_descriptor(ref_dstDesc,
+                                             make_tuple(make_pad_transform(ref_invariantLen, 0, 2)),
+                                             make_tuple(Sequence<0>{}),
+                                             make_tuple(Sequence<0>{})));
+
+    using refType_src2dDesc = decltype(ref_src2dDesc);
+    using refType_dst1dDesc = decltype(ref_dstDesc);
+};
+
+using refType_src2dDesc = typename get_ref_desc_types<srcDims>::refType_src2dDesc;
+using refType_dst1dDesc = typename get_ref_desc_types<srcDims>::refType_dst1dDesc;
+using refType_src2dDesc_padded_34 =
+    typename get_ref_desc_types<srcDims>::refType_src2dDesc_padded_34;
+using refType_dst1dDesc_padded = typename get_ref_desc_types<srcDims>::refType_dst1dDesc_padded;
+
+template <bool need_padding>
+static __device__ auto get_reduction_src2d_descriptor(const void* p_src2dDesc)
+{
+    if constexpr(need_padding)
+        return (*reinterpret_cast<const refType_src2dDesc_padded_34*>(p_src2dDesc));
+    else
+        return (*reinterpret_cast<const refType_src2dDesc*>(p_src2dDesc));
+};
+
+template <bool need_padding>
+static __device__ auto get_reduction_dst1d_descriptor(const void* p_dst1dDesc)
+{
+    if constexpr(need_padding)
+        return (*reinterpret_cast<const refType_dst1dDesc_padded*>(p_dst1dDesc));
+    else
+        return (*reinterpret_cast<const refType_dst1dDesc*>(p_dst1dDesc));
+};
+
+extern "C" __global__ void gridwise_generic_reduce_1(int origReduceLen,
+                                                     int BlkGroupSize,
+                                                     float alpha,
+                                                     const void* __restrict__ p_src_global,
+                                                     float beta,
+                                                     void* __restrict__ p_dst_global,
+                                                     const void CONSTANT* ws_global,
+                                                     long ws_buf2_bytes_offset,
+                                                     void* __restrict__ indices_global)
+{
+    (void)BlkGroupSize;
+    (void)ws_buf2_bytes_offset;
+
+    const void* p_src2dDesc = cast_pointer_to_generic_address_space(ws_global);
+    const void* p_dst1dDesc = static_cast<const char*>(p_src2dDesc) + 2048;
+
+    const auto src2dDesc = get_reduction_src2d_descriptor<src2d_need_padding>(p_src2dDesc);
+    const auto dst1dDesc = get_reduction_dst1d_descriptor<dst1d_need_padding>(p_dst1dDesc);
+
+    using gridwise_2d_reduce = GridwiseReduction_xy_to_x_blockwise<BlockSize,
+                                                                   srcDataType,
+                                                                   dstDataType,
+                                                                   compType,
+                                                                   decltype(src2dDesc),
+                                                                   decltype(dst1dDesc),
+                                                                   op,
+                                                                   nanPropaOpt,
+                                                                   reduceIndicesOpt,
+                                                                   true,
+                                                                   true,
+                                                                   GredAccessesPerThreadInBlock>;
+
+    constexpr int RunId = need_indices ? 2 : 1;
+    gridwise_2d_reduce::template Run<RunId>(
+        src2dDesc,
+        dst1dDesc,
+        origReduceLen,
+        alpha,
+        static_cast<const srcDataType* const __restrict__>(p_src_global),
+        beta,
+        static_cast<dstDataType* const __restrict__>(p_dst_global),
+        static_cast<const int* const __restrict__>(nullptr),
+        static_cast<int* const __restrict__>(indices_global));
+};

host/driver_offline/CMakeLists.txt

@@ -12,16 +12,19 @@ include_directories(BEFORE
 )
 
 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_BWD_DRIVER_OFFLINE_SOURCE src/conv_bwd_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)
 
 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_bwd_driver_offline ${CONV_BWD_DRIVER_OFFLINE_SOURCE})
 add_executable(conv_wrw_driver_offline ${CONV_WRW_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_nchwc 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(gemm_driver_offline PRIVATE host_tensor)