GridwiseGemm with direct c wirteout parameterized.

Added few template parameters deciding on store access pattern.
Right now it's designed to be warp raked.

include/ck/tensor_operation/gpu/device/impl/device_gemm_xdl_direct_c_write_out.hpp

@@ -12,7 +12,8 @@
 #include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
 #include "ck/tensor_operation/gpu/device/device_gemm.hpp"
 #include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
-#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_direct_c_write_out.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_direct_c_write_out_roofline.hpp"
+// #include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_direct_c_write_out.hpp"
 #include "ck/host_utility/device_prop.hpp"
 #include "ck/host_utility/kernel_launch.hpp"
 
@@ -56,6 +57,9 @@ template <typename ALayout,
           index_t BBlockTransferSrcScalarPerVector,
           index_t BBlockTransferDstScalarPerVector_BK1,
           bool BBlockLdsExtraN,
+          typename CThreadTransferDstAccessOrder,
+          index_t CThreadTransferDstVectorDim,
+          index_t CThreadTransferDstScalarPerVector,
           LoopScheduler LoopSched     = make_default_loop_scheduler(),
           PipelineVersion PipelineVer = PipelineVersion::v2>
 struct DeviceGemm_Xdl_DirectCWriteOut : public DeviceGemm<ALayout,
@@ -381,6 +385,9 @@ struct DeviceGemm_Xdl_DirectCWriteOut : public DeviceGemm<ALayout,
                                            BBlockTransferDstScalarPerVector_BK1,
                                            false,
                                            BBlockLdsExtraN,
+                                           CThreadTransferDstAccessOrder,
+                                           CThreadTransferDstVectorDim,
+                                           CThreadTransferDstScalarPerVector,
                                            LoopSched,
                                            PipelineVer>;
 

include/ck/tensor_operation/gpu/device/impl/device_grouped_gemm_xdl_splitk_direct_c_write_out.hpp

@@ -17,7 +17,8 @@
 #include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
 #include "ck/tensor_operation/gpu/device/device_grouped_gemm_splitk.hpp"
 #include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
-#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_splitk_direct_c_write_out.hpp"
+// #include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_splitk_direct_c_write_out.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_splitk_direct_c_write_out_roofline.hpp"
 
 namespace ck {
 namespace tensor_operation {

include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_splitk_direct_c_write_out_roofline.hpp

@@ -751,8 +751,6 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_splitk_direct_c_write_out
             // N3 - mfma_instr.num_input_blks
             // N4 - mfma_instr.group_size
             // {M0, N0, 1, 1, 1, 4, 1, 4}
-            // constexpr auto c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4 =
-            //     blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_N2_N3_N4();
 
             // c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4 is only used to get lengths
             constexpr auto c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4 =