Code clean up (#20)

* tuning para,

* testing on v100

* add fp16

* remove deprecated tensor descriptor

* sync with miopen

* update build script
Co-authored-by: Jing Zhang <jizhan@amd.com>

composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer.hpp

@@ -8,53 +8,9 @@
 #include "blockwise_generic_tensor_slice_copy.hpp"
 #include "threadwise_generic_tensor_slice_copy.hpp"
 #include "blockwise_gemm.hpp"
-#include "convolution_common.hpp"
 
 namespace ck {
 
-template <ConvolutionDirection>
-struct make_wei_e_k_global_desc_v4r1;
-
-template <>
-struct make_wei_e_k_global_desc_v4r1<ConvolutionDirection::Forward>
-{
-    template <typename WeiDesc>
-    __device__ constexpr auto operator()(WeiDesc) const
-    {
-        constexpr auto I1 = Number<1>{};
-        constexpr auto I3 = Number<3>{};
-
-        return reorder_tensor_descriptor_given_upper2lower(
-            unfold_tensor_descriptor(WeiDesc{}, I1, I3), Sequence<1, 0>{});
-    }
-};
-
-template <>
-struct make_wei_e_k_global_desc_v4r1<ConvolutionDirection::BackwardWeight>
-{
-    template <typename WeiDesc>
-    __device__ constexpr auto operator()(WeiDesc) const
-    {
-        constexpr auto I0 = Number<0>{};
-        constexpr auto I1 = Number<1>{};
-        constexpr auto I2 = Number<2>{};
-        constexpr auto I3 = Number<3>{};
-
-        constexpr auto wei_k_c_y_x_global_desc = WeiDesc{};
-
-        constexpr index_t K = wei_k_c_y_x_global_desc.GetLength(I0);
-        constexpr index_t C = wei_k_c_y_x_global_desc.GetLength(I1);
-        constexpr index_t Y = wei_k_c_y_x_global_desc.GetLength(I2);
-        constexpr index_t X = wei_k_c_y_x_global_desc.GetLength(I3);
-
-        return transform_tensor_descriptor(
-            unfold_tensor_descriptor(wei_k_c_y_x_global_desc, I2, I3),
-            make_tuple(Merge<Sequence<C, Y * X>>{}, PassThrough<K>{}),
-            make_tuple(Sequence<1, 2>{}, Sequence<0>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}));
-    }
-};
-
 template <index_t GridSize,
           index_t BlockSize,
           typename Float,
@@ -66,18 +22,17 @@ template <index_t GridSize,
           typename ConvDilations,
           typename LeftPads,
           typename RightPads,
-          ConvolutionDirection ConvDirection,
           index_t BPerBlock,
           index_t KPerBlock,
           index_t EPerBlock,
           index_t GemmNRepeat,
-          index_t GemmMPerThreadSubC,
-          index_t GemmNPerThreadSubC,
+          index_t GemmMPerThread,
+          index_t GemmNPerThread,
+          index_t GemmKPerThread,
           index_t GemmMLevel0Cluster,
           index_t GemmNLevel0Cluster,
           index_t GemmMLevel1Cluster,
           index_t GemmNLevel1Cluster,
-          index_t GemmKPerThreadLoop,
           index_t GemmDataPerReadA,
           index_t GemmDataPerReadB,
           typename InBlockCopySubLengths_E_N1_B_N2,
@@ -107,18 +62,13 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
 
         constexpr auto True = integral_constant<bool, true>{};
 
-        static_assert(ConvDirection == ConvolutionDirection::Forward ||
-                          ConvDirection == ConvolutionDirection::BackwardWeight,
-                      "wrong! this kernel only support convolution forward and backward-weight");
-
         // this is a mess
         // TODO: find more elegent way of specifying (or calculating) performance parameters
         constexpr index_t N1 = GemmNRepeat;
-        constexpr index_t N2 = GemmNPerThreadSubC;
+        constexpr index_t N2 = GemmNPerThread;
 
-        static_assert((N1 * N2 * BPerBlock) %
-                              (GemmNPerThreadSubC * GemmNLevel0Cluster * GemmNLevel1Cluster) ==
-                          0,
+        static_assert(
+            (N1 * N2 * BPerBlock) % (GemmNPerThread * GemmNLevel0Cluster * GemmNLevel1Cluster) == 0,
             "wrong!");
 
         constexpr auto in_n_c_hi_wi_global_desc  = InGlobalDesc{};
@@ -240,7 +190,10 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
         //     It is constructed differently, depending on whether forward or backward weight
         //       convolution
         constexpr auto wei_e_k_global_desc =
-            make_wei_e_k_global_desc_v4r1<ConvDirection>{}(wei_k_c_y_x_global_desc);
+            transform_tensor_descriptor(unfold_tensor_descriptor(wei_k_c_y_x_global_desc, I2, I3),
+                                        make_tuple(Merge<Sequence<C, Y * X>>{}, PassThrough<K>{}),
+                                        make_tuple(Sequence<1, 2>{}, Sequence<0>{}),
+                                        make_tuple(Sequence<0>{}, Sequence<1>{}));
 
         //     block tensor in LDS memory, dst of blockwise copy
         //     be careful of LDS alignment
@@ -290,30 +243,29 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
             in_e_n1_b_n2_block_desc.GetStride(I0));
 
         // sanity check
-        static_assert(KPerBlock % (GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster) ==
-                          0,
+        static_assert(KPerBlock % (GemmMPerThread * GemmMLevel0Cluster * GemmMLevel1Cluster) == 0,
                       "wrong!");
 
         constexpr index_t GemmMRepeat =
-            KPerBlock / (GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster);
+            KPerBlock / (GemmMPerThread * GemmMLevel0Cluster * GemmMLevel1Cluster);
 
         // c_thread_mtx definition: this is a mess
         // TODO:: more elegent way of defining c_thread_mtx
         constexpr auto c_k0k1_n1n2_thread_mtx_desc = make_ConstantMatrixDescriptor_packed(
-            Number<GemmMRepeat * GemmMPerThreadSubC>{}, Number<GemmNRepeat * GemmNPerThreadSubC>{});
+            Number<GemmMRepeat * GemmMPerThread>{}, Number<GemmNRepeat * GemmNPerThread>{});
 
         const auto blockwise_gemm = BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2<
             BlockSize,
             decltype(a_e_k_block_mtx_desc),
             decltype(b_e_n1bn2_block_mtx_desc),
             decltype(c_k0k1_n1n2_thread_mtx_desc),
-            GemmMPerThreadSubC,
-            GemmNPerThreadSubC,
+            GemmMPerThread,
+            GemmNPerThread,
+            GemmKPerThread,
             GemmMLevel0Cluster,
             GemmNLevel0Cluster,
             GemmMLevel1Cluster,
             GemmNLevel1Cluster,
-            GemmKPerThreadLoop,
             GemmDataPerReadA,
             GemmDataPerReadB>{};
 
@@ -432,13 +384,13 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer
 
         // copy output: register to global memory
         {
-            constexpr index_t K1 = GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster;
+            constexpr index_t K1 = GemmMPerThread * GemmMLevel0Cluster * GemmMLevel1Cluster;
             constexpr index_t K0 = K / K1;
 
             // define output tensor descriptor for threadwise copy
             //     thread output tensor, src of threadwise copy
             constexpr auto out_k0_k1_n1_b_n2_thread_desc = make_native_tensor_descriptor_packed(
-                Sequence<GemmMRepeat, GemmMPerThreadSubC, N1, 1, N2>{});
+                Sequence<GemmMRepeat, GemmMPerThread, N1, 1, N2>{});
 
             //     global output tensor
             constexpr auto out_n0_n1_n2_k0_k1_ho_wo_global_desc = transform_tensor_descriptor(

composable_kernel/include/tensor_operation/blockwise_gemm.hpp

@@ -18,11 +18,11 @@ template <index_t BlockSize,
           typename ThreadMatrixC,
           index_t MPerThreadSubC,
           index_t NPerThreadSubC,
+          index_t KPerThreadLoop,
           index_t MLevel0ThreadCluster,
           index_t NLevel0ThreadCluster,
           index_t MLevel1ThreadCluster,
           index_t NLevel1ThreadCluster,
-          index_t KPerThreadLoop,
           index_t ThreadGemmADataPerRead_M,
           index_t ThreadGemmBDataPerRead_N>
 struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2