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example/01_gemm/gemm_xdl_fp64.cpp

@@ -47,13 +47,13 @@ using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemmXdl
 //##########|      |      |      |        |        |        |        |   Operation|   Operation|   Operation|              |      |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|   ArrangeOrder|               |               |      PerVector|   PerVector_K1|          | Lengths_K0_N_K1|   ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |                |       PerVector|
 //##########|      |      |      |        |        |        |        |            |            |            |              |      |      |      |      |   |     |     |     |     |                |               |               |               |               |               |          |                |               |               |              |               |               |          |                |                |
 #if 1
-             <  F64,   F64,   F64,     F64,     Row,     Col,     Row, PassThrough, PassThrough, PassThrough,   GemmDefault,   256,   128,   128,     4,  4,   16,   16,    4,    4,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              4,              4,      true,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              4,              4,      true,               7,               1>;
+             <  F64,   F64,   F64,     F64,     Row,     Col,     Row, PassThrough, PassThrough, PassThrough,   GemmDefault,   64,    32,    32,     4,  1,   16,   16,    2,    2,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              1,              1,      true,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              1,              1,      true,               7,               1>;
 using ADataType   = double;
 using BDataType   = double;
 using CDataType   = double;
 using AccDataType = double;
 #else
-            <   F32,   F32,   F32,     F32,     Row,     Col,     Row, PassThrough, PassThrough, PassThrough,   GemmDefault,   256,   128,   128,     4,  4,   16,   16,    4,    4,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              4,              4,      true,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              4,              4,      true,               7,               1>;
+            <   F32,   F32,   F32,     F32,     Row,     Col,     Row, PassThrough, PassThrough, PassThrough,   GemmDefault,   64,    32,    32,     4,  1,   16,   16,    2,    2,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              1,              1,      true,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              1,              1,      true,               7,               1>;
 using ADataType   = float;
 using BDataType   = float;
 using CDataType   = float;
@@ -64,6 +64,23 @@ using AccDataType = float;
 using ReferenceGemmInstance = ck::tensor_operation::host::
     ReferenceGemm<ADataType, BDataType, CDataType, AccDataType, AElementOp, BElementOp, CElementOp>;
 
+template <typename DataType>
+std::ostream& void show_2d_matrix(std::ostream& os, Tensor<DataType>& matrix)
+{
+    os << "[" << std::endl;
+    for(int x = 0; x < matrix.mDesc.GetLengths()[0]; x++)
+    {
+        os << "[";
+        for(int y = 0; y < matrix.mDesc.GetLengths()[1]; y++)
+        {
+            os << std::setw(4) << static_cast<float>(matrix(x, y));
+        }
+        os << "]" << std::endl;
+    }
+    os << "]";
+    return os;
+}
+
 int main(int argc, char* argv[])
 {
     bool do_verification = 0;
@@ -144,8 +161,8 @@ int main(int argc, char* argv[])
         break;
     default:
         // a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
-        b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
         a_m_k.GenerateTensorValue(GeneratorTensor_1<ADataType>{1});
+        b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
         // b_k_n.GenerateTensorValue(GeneratorTensor_1<BDataType>{1});
     }
 
@@ -208,13 +225,12 @@ int main(int argc, char* argv[])
 
         ref_invoker.Run(ref_argument);
 
-#if 0
+#if 1
         {
-            LogRangeAsType<AccDataType>(std::cout << "a : ", a_m_k.mData, ",") << std::endl;
-            LogRangeAsType<AccDataType>(std::cout << "b: ", b_k_n.mData, ",") << std::endl;
-            LogRangeAsType<AccDataType>(std::cout << "c_device: ", c_m_n_device_result.mData, ",") << std::endl;
-            LogRangeAsType<AccDataType>(std::cout << "c_host  : ", c_m_n_host_result.mData, ",")
-                << std::endl;
+            show_2d_matrix(std::cout << "a : ", a_m_k) << std::endl;
+            show_2d_matrix(std::cout << "b: ", b_k_n) << std::endl;
+            show_2d_matrix(std::cout << "c_device: ", c_m_n_device_result) << std::endl;
+            show_2d_matrix(std::cout << "c_host  :", c_m_n_host_result) << std::endl;
         }
 #endif
         ck::utils::check_err(c_m_n_device_result.mData, c_m_n_host_result.mData);

example/09_convnd_fwd/convnd_fwd_xdl_fp64.cpp

@@ -49,14 +49,14 @@ using DeviceConvNDFwdInstance = ck::tensor_operation::device::
         ConvFwdDefault,     // ConvForwardSpecialization
         NumDimSpatial,      // NumDimSpatial
         256,                // BlockSize
-        128,                // MPerBlock
-        128,                // NPerBlock
+        64,                // MPerBlock
+        64,                // NPerBlock
         4,                  // K0PerBlock
         2,                  // K1
         16,                 // MPerXDL
         16,                 // NPerXDL
-        4,                  // MXdlPerWave
-        4,                  // NXdlPerWave
+        2,                  // MXdlPerWave
+        2,                  // NXdlPerWave
         S<4, 64, 1>,        // ABlockTransferThreadClusterLengths_K0_M_K1
         S<1, 0, 2>,         // ABlockTransferThreadClusterArrangeOrder
         S<1, 0, 2>,         // ABlockTransferSrcAccessOrder

include/ck/tensor_operation/gpu/warp/xdlops_gemm.hpp

@@ -25,7 +25,7 @@ enum struct MfmaInstr
     mfma_f32_16x16x8bf16,
     mfma_i32_32x32x8i8,
     mfma_i32_16x16x16i8,
-    mfma_f64_16x16x4f64,
+    mfma_f64_16x16x4f64
 };
 
 template <MfmaInstr instr>

library/include/ck/library/reference_tensor_operation/cpu/reference_gemm.hpp

@@ -63,8 +63,8 @@ struct ReferenceGemm : public device::BaseOperator
                     AccDataType v_a;
                     AccDataType v_b;
 
-                    arg.a_element_op_(v_a, static_cast<const float>(arg.a_m_k_(m, k)));
-                    arg.b_element_op_(v_b, static_cast<const float>(arg.b_k_n_(k, n)));
+                    arg.a_element_op_(v_a, static_cast<const AccDataType>(arg.a_m_k_(m, k)));
+                    arg.b_element_op_(v_b, static_cast<const AccDataType>(arg.b_k_n_(k, n)));
 
                     v_acc += v_a * v_b;
                 }