diff --git a/cmake/external/cutlass.cmake b/cmake/external/cutlass.cmake
index eee868900b585445721195d13af06a5640e43b5b..822b71c71d31db07b79a2a72eb1cf977c7c1ab07 100644
--- a/cmake/external/cutlass.cmake
+++ b/cmake/external/cutlass.cmake
@@ -34,7 +34,14 @@ ExternalProject_Add(
   PREFIX ${CUTLASS_PREFIX_DIR}
   UPDATE_COMMAND ""
   CONFIGURE_COMMAND ""
-  BUILD_COMMAND ""
+  BUILD_COMMAND
+    mkdir -p
+    ${CMAKE_SOURCE_DIR}/paddle/phi/kernels/sparse/gpu/cutlass/build/generated/gemm
+    && ${PYTHON_EXECUTABLE} -B
+    ${CMAKE_SOURCE_DIR}/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_generator.py
+    "${THIRD_PARTY_PATH}/cutlass/src/extern_cutlass/tools/library/scripts/"
+    "${CMAKE_SOURCE_DIR}/paddle/phi/kernels/sparse/gpu/cutlass/build"
+    "${CMAKE_CUDA_COMPILER_VERSION}"
   INSTALL_COMMAND ""
   TEST_COMMAND "")
 
diff --git a/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_generator.py b/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_generator.py
new file mode 100644
index 0000000000000000000000000000000000000000..49c6e5975181a0e50a7f87ccf2c6fe16a8cea669
--- /dev/null
+++ b/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_generator.py
@@ -0,0 +1,250 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import sys
+
+sys.path.append(sys.argv[1])
+from gather_gemm_scatter_manifest import GatherGemmScatterManifest
+from gather_gemm_scatter_operation import GatherGemmScatterOperation
+from generator import (
+    ComplexTransform,
+    CudaToolkitVersionSatisfies,
+    EpilogueFunctor,
+    GemmKind,
+    SwizzlingFunctor,
+    TensorDescription,
+)
+from library import (
+    DataType,
+    LayoutType,
+    MathInstruction,
+    MathOperation,
+    OpcodeClass,
+    TileDescription,
+)
+from manifest import GeneratorTarget
+
+
+def CreateGatherGemmScatterOperator(
+    manifest,
+    layouts,
+    tile_descriptions,
+    data_type,
+    alignment_constraints,
+    complex_transforms=None,
+    epilogue_functor=EpilogueFunctor.LinearCombination,
+    swizzling_functor=SwizzlingFunctor.Identity8,
+):
+    # To use StreamK decomposition for basic GEMMs, set `swizzling_functor = SwizzlingFunctor.StreamK`
+
+    if complex_transforms is None:
+        complex_transforms = [
+            (ComplexTransform.none, ComplexTransform.none),
+        ]
+
+    element_a, element_b, element_c, element_epilogue = data_type
+
+    operations = []
+
+    # by default, only generate the largest tile and largest alignment
+    # if manifest.kernel_filter == '':
+    #  tile_descriptions = [tile_descriptions[0],]
+    #  alignment_constraints = [alignment_constraints[0],]
+
+    for layout in layouts:
+        for tile_description in tile_descriptions:
+            for alignment in alignment_constraints:
+                for complex_transform in complex_transforms:
+
+                    alignment_c = min(8, alignment)
+
+                    A = TensorDescription(
+                        element_a, layout[0], alignment, complex_transform[0]
+                    )
+                    B = TensorDescription(
+                        element_b, layout[1], alignment, complex_transform[1]
+                    )
+                    C = TensorDescription(element_c, layout[2], alignment_c)
+
+                    new_operation = GatherGemmScatterOperation(
+                        GemmKind.Universal,
+                        tile_description.minimum_compute_capability,
+                        tile_description,
+                        A,
+                        B,
+                        C,
+                        element_epilogue,
+                        epilogue_functor,
+                        swizzling_functor,
+                    )
+
+                    manifest.append(new_operation)
+                    operations.append(new_operation)
+
+    return operations
+
+
+def GenerateSM70_TensorOp_884(manifest, cuda_version):
+
+    if not CudaToolkitVersionSatisfies(cuda_version, 10, 1):
+        return
+
+    layouts = [
+        (LayoutType.RowMajor, LayoutType.RowMajor, LayoutType.RowMajor),
+    ]
+
+    math_instructions = [
+        MathInstruction(
+            [8, 8, 4],
+            DataType.f16,
+            DataType.f16,
+            DataType.f32,
+            OpcodeClass.TensorOp,
+            MathOperation.multiply_add,
+        ),
+        MathInstruction(
+            [8, 8, 4],
+            DataType.f16,
+            DataType.f16,
+            DataType.f16,
+            OpcodeClass.TensorOp,
+            MathOperation.multiply_add,
+        ),
+    ]
+
+    min_cc = 70
+    max_cc = 75
+
+    alignment_constraints = [8, 4, 2, 1]
+
+    for math_inst in math_instructions:
+        tile_descriptions = [
+            TileDescription(
+                [256, 128, 32], 2, [4, 2, 1], math_inst, min_cc, max_cc
+            ),
+            TileDescription(
+                [128, 256, 32], 2, [2, 4, 1], math_inst, min_cc, max_cc
+            ),
+            TileDescription(
+                [128, 128, 32], 2, [2, 2, 1], math_inst, min_cc, max_cc
+            ),
+            TileDescription(
+                [256, 64, 32], 2, [4, 1, 1], math_inst, min_cc, max_cc
+            ),
+            TileDescription(
+                [64, 256, 32], 2, [1, 4, 1], math_inst, min_cc, max_cc
+            ),
+            TileDescription(
+                [64, 128, 32], 2, [2, 2, 1], math_inst, min_cc, max_cc
+            ),
+            TileDescription(
+                [128, 64, 32], 2, [2, 2, 1], math_inst, min_cc, max_cc
+            ),
+            TileDescription(
+                [64, 64, 32], 2, [2, 2, 1], math_inst, min_cc, max_cc
+            ),
+        ]
+
+        data_type = [
+            math_inst.element_a,
+            math_inst.element_b,
+            math_inst.element_accumulator,
+            math_inst.element_accumulator,
+        ]
+
+        CreateGatherGemmScatterOperator(
+            manifest,
+            layouts,
+            tile_descriptions,
+            data_type,
+            alignment_constraints,
+        )
+
+        # Avoid emitting two kernels if the accumulator type does not differ from the input type (e.g. F16 accumulation)
+        if math_inst.element_a != math_inst.element_accumulator:
+
+            data_type_mixed = [
+                math_inst.element_a,
+                math_inst.element_b,
+                math_inst.element_a,
+                math_inst.element_accumulator,
+            ]
+
+            CreateGatherGemmScatterOperator(
+                manifest,
+                layouts,
+                tile_descriptions,
+                data_type_mixed,
+                alignment_constraints,
+            )
+
+
+def GenerateSM70(manifest, cuda_version):
+    GenerateSM70_TensorOp_884(manifest, cuda_version)
+
+
+class KernelCfg:
+    def __init__(
+        self,
+        architectures,
+        build_dir,
+        cuda_version,
+        curr_build_dir,
+        disable_full_archs_compilation,
+        filter_by_cc,
+        generator_target,
+        ignore_kernels,
+        interface_dir,
+        kernel_filter_file,
+        kernels,
+        operations,
+        selected_kernel_list,
+    ):
+        self.architectures = architectures
+        self.build_dir = build_dir
+        self.cuda_version = cuda_version
+        self.curr_build_dir = curr_build_dir
+        self.disable_full_archs_compilation = disable_full_archs_compilation
+        self.filter_by_cc = filter_by_cc
+        self.generator_target = generator_target
+        self.ignore_kernels = ignore_kernels
+        self.interface_dir = interface_dir
+        self.kernel_filter_file = kernel_filter_file
+        self.kernels = kernels
+        self.operations = operations
+        self.selected_kernel_list = selected_kernel_list
+
+
+if __name__ == "__main__":
+
+    args = KernelCfg(
+        architectures='70',
+        build_dir=sys.argv[2],
+        cuda_version=sys.argv[3],
+        curr_build_dir=sys.argv[2],
+        disable_full_archs_compilation=False,
+        filter_by_cc='True',
+        generator_target='library',
+        ignore_kernels='',
+        interface_dir=None,
+        kernel_filter_file=None,
+        kernels='',
+        operations='all',
+        selected_kernel_list=None,
+    )
+    manifest = GatherGemmScatterManifest(args)
+
+    GenerateSM70(manifest, args.cuda_version)
+
+    manifest.emit(GeneratorTarget.Library)
diff --git a/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_manifest.py b/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_manifest.py
new file mode 100644
index 0000000000000000000000000000000000000000..1cb48af13a1208789d938305c8022d4f8a4fca6e
--- /dev/null
+++ b/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_manifest.py
@@ -0,0 +1,101 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import shutil
+
+from gather_gemm_scatter_operation import (
+    EmitGatherGemmScatterConfigurationLibrary,
+)
+from library import OperationKind, OperationKindNames
+from manifest import EmitOperationKindLibrary, GeneratorTarget, Manifest
+
+
+class GatherGemmScatterEmitOperationKindLibrary(EmitOperationKindLibrary):
+    def __init__(self, generated_path, kind, args):
+        super().__init__(generated_path, kind, args)
+        self.emitters = {
+            OperationKind.Gemm: EmitGatherGemmScatterConfigurationLibrary
+        }
+        self.header_template = "#pragma once\n#ifdef PADDLE_WITH_CUTLASS\n"
+        self.entry_template = ""
+        self.configuration_prototype_template = ""
+        self.configuration_template = ""
+        self.epilogue_template = "#endif"
+
+    def __enter__(self):
+        self.operation_path = os.path.join(
+            self.generated_path, OperationKindNames[self.kind]
+        )
+        os.mkdir(self.operation_path)
+
+        self.top_level_path = os.path.join(
+            self.operation_path,
+            "all_%s_operations.h" % OperationKindNames[self.kind],
+        )
+
+        self.top_level_file = open(self.top_level_path, "w")
+        self.top_level_file.write(self.header_template)
+
+        self.source_files = [
+            self.top_level_path,
+        ]
+
+        return self
+
+    def emit(self, configuration_name, operations):
+        with self.emitters[self.kind](
+            self.operation_path, configuration_name
+        ) as configuration_emitter:
+            for operation in operations:
+                configuration_emitter.emit(operation)
+
+            self.source_files.append(configuration_emitter.configuration_path)
+
+        self.configurations.append(configuration_name)
+        self.top_level_file.write(
+            '#include "'
+            + self.operation_path
+            + '/'
+            + configuration_name
+            + '.h"\n'
+        )
+
+
+class GatherGemmScatterManifest(Manifest):
+    def emit(self, target=GeneratorTarget.Library):
+
+        operation_emitters = {
+            GeneratorTarget.Library: GatherGemmScatterEmitOperationKindLibrary
+        }
+
+        generated_path = os.path.join(self.curr_build_dir, 'generated')
+
+        # create generated/
+        if os.path.exists(generated_path):
+            shutil.rmtree(generated_path)
+
+        os.mkdir(generated_path)
+
+        source_files = []
+
+        # for each operation kind, emit initializer for all configurations
+        for operation_kind, configurations in self.operations.items():
+            with operation_emitters[target](
+                generated_path, operation_kind, self.args
+            ) as operation_kind_emitter:
+                for configuration_name, operations in configurations.items():
+                    operation_kind_emitter.emit(configuration_name, operations)
+
+                source_files += operation_kind_emitter.source_files
diff --git a/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_operation.py b/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_operation.py
new file mode 100644
index 0000000000000000000000000000000000000000..1b2296b8c44541fe3932ef73af06a3fb0d7a2337
--- /dev/null
+++ b/paddle/phi/kernels/sparse/gpu/cutlass/gather_gemm_scatter_operation.py
@@ -0,0 +1,320 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import enum
+import os.path
+
+from gemm_operation import (
+    EmitGemmConfigurationLibrary,
+    EmitGemmInstance,
+    EpilogueFunctor,
+    GemmOperation,
+    SwizzlingFunctor,
+)
+from library import (
+    ComplexTransformTag,
+    DataTypeSize,
+    DataTypeTag,
+    EpilogueFunctorTag,
+    GemmKind,
+    LayoutTag,
+    LayoutType,
+    MathOperationTag,
+    OpcodeClassTag,
+    SubstituteTemplate,
+    SwizzlingFunctorTag,
+)
+
+
+class EmitGatherGemmScatterInstance(EmitGemmInstance):
+    def __init__(self, operation_suffix=''):
+        self.operation_suffix = operation_suffix
+        self.includes = [
+            "cutlass/cutlass.h",
+            "cutlass/numeric_types.h",
+            "cutlass/arch/arch.h",
+            "cutlass/arch/mma.h",
+            "cutlass/layout/matrix.h",
+            "cutlass/gemm/device/gemm.h",
+            "cutlass/gemm/device/gemm_universal_adapter.h",
+            "cutlass/gemm/kernel/default_gemm_universal.h",
+        ]
+        self.builtin_epilogue_functor_template = """
+    ${epilogue_functor}<
+      ${element_c},
+      ${epilogue_vector_length},
+      ${element_accumulator},
+      ${element_epilogue}
+    >
+"""
+        self.gemm_template = """
+// Gemm operator ${operation_name}
+struct ${operation_name} {
+  using Gemm =
+    cutlass::gemm::device::GemmUniversal<
+      ${element_a},
+      ${layout_a},
+      ${element_b},
+      ${layout_b},
+      ${element_c},
+      ${layout_c},
+      ${element_accumulator},
+      ${opcode_class},
+      ${arch},
+      cutlass::gemm::GemmShape<${threadblock_shape_m}, ${threadblock_shape_n}, ${threadblock_shape_k}>,
+      cutlass::gemm::GemmShape<${warp_shape_m}, ${warp_shape_n}, ${warp_shape_k}>,
+      cutlass::gemm::GemmShape<${instruction_shape_m}, ${instruction_shape_n}, ${instruction_shape_k}>,
+      ${epilogue_functor},
+      ${swizzling_functor},
+      ${stages},
+      ${align_a},
+      ${align_b},
+      ${math_operation},
+      ${transform_a},
+      ${transform_b},
+      true, // gather a
+      false, // gather b
+      true // scatter d
+    >;
+};
+"""
+
+    def instance_template(self):
+        return ""
+
+    def emit(self, operation):
+
+        threadblock_shape = operation.tile_description.threadblock_shape
+        warp_count = operation.tile_description.warp_count
+
+        warp_shape = [
+            threadblock_shape[idx] // warp_count[idx] for idx in range(3)
+        ]
+
+        transpose_layouts = {
+            LayoutType.ColumnMajor: LayoutType.ColumnMajor,
+            LayoutType.RowMajor: LayoutType.RowMajor,
+        }
+
+        if (
+            operation.A.layout in transpose_layouts.keys()
+            and operation.B.layout in transpose_layouts.keys()
+            and operation.C.layout in transpose_layouts.keys()
+        ):
+
+            instance_layout_A = transpose_layouts[operation.A.layout]
+            instance_layout_B = transpose_layouts[operation.B.layout]
+            instance_layout_C = transpose_layouts[operation.C.layout]
+
+            gemm_template = self.gemm_template
+        else:
+            instance_layout_A, instance_layout_B, instance_layout_C = (
+                operation.A.layout,
+                operation.B.layout,
+                operation.C.layout,
+            )
+
+            gemm_template = self.gemm_template_interleaved
+
+        # Support built-in epilogue functors or user-defined functions
+        if isinstance(operation.epilogue_functor, enum.Enum):
+
+            epilogue_vector_length = (
+                min(
+                    operation.C.alignment * DataTypeSize[operation.C.element],
+                    128,
+                )
+                // DataTypeSize[operation.C.element]
+            )
+
+            values = {
+                'epilogue_vector_length': str(epilogue_vector_length),
+                'element_epilogue': str(
+                    DataTypeTag[operation.element_epilogue]
+                ),
+                'epilogue_functor': EpilogueFunctorTag[
+                    operation.epilogue_functor
+                ],
+            }
+            epilogue_functor = SubstituteTemplate(
+                self.builtin_epilogue_functor_template, values
+            )
+        else:
+            epilogue_functor = self.epilogue_functor.emit_declaration()
+
+        values = {
+            'operation_name': operation.procedural_name(),
+            'operation_suffix': self.operation_suffix,
+            'element_a': DataTypeTag[operation.A.element],
+            'layout_a': LayoutTag[instance_layout_A],
+            'element_b': DataTypeTag[operation.B.element],
+            'layout_b': LayoutTag[instance_layout_B],
+            'element_c': DataTypeTag[operation.C.element],
+            'layout_c': LayoutTag[instance_layout_C],
+            'element_accumulator': DataTypeTag[operation.accumulator_type()],
+            'opcode_class': OpcodeClassTag[
+                operation.tile_description.math_instruction.opcode_class
+            ],
+            'arch': "cutlass::arch::Sm%d" % operation.arch,
+            'threadblock_shape_m': str(
+                operation.tile_description.threadblock_shape[0]
+            ),
+            'threadblock_shape_n': str(
+                operation.tile_description.threadblock_shape[1]
+            ),
+            'threadblock_shape_k': str(
+                operation.tile_description.threadblock_shape[2]
+            ),
+            'warp_shape_m': str(warp_shape[0]),
+            'warp_shape_n': str(warp_shape[1]),
+            'warp_shape_k': str(warp_shape[2]),
+            'instruction_shape_m': str(
+                operation.tile_description.math_instruction.instruction_shape[0]
+            ),
+            'instruction_shape_n': str(
+                operation.tile_description.math_instruction.instruction_shape[1]
+            ),
+            'instruction_shape_k': str(
+                operation.tile_description.math_instruction.instruction_shape[2]
+            ),
+            'epilogue_functor': epilogue_functor,
+            'swizzling_functor': SwizzlingFunctorTag[
+                operation.swizzling_functor
+            ],
+            'stages': str(operation.tile_description.stages),
+            'align_a': str(operation.A.alignment),
+            'align_b': str(operation.B.alignment),
+            'transform_a': ComplexTransformTag[operation.A.complex_transform],
+            'transform_b': ComplexTransformTag[operation.B.complex_transform],
+            'math_operation': MathOperationTag[
+                operation.tile_description.math_instruction.math_operation
+            ],
+        }
+
+        return SubstituteTemplate(gemm_template, values)
+
+
+class EmitGatherGemmScatterConfigurationLibrary(EmitGemmConfigurationLibrary):
+    def __init__(self, operation_path, configuration_name):
+        self.configuration_name = configuration_name
+        self.configuration_path = os.path.join(
+            operation_path, "%s.h" % configuration_name
+        ).replace('\\', '/')
+
+        self.instance_emitter = {
+            GemmKind.Universal: EmitGatherGemmScatterInstance,
+        }
+
+        self.gemm_kind_wrappers = {
+            GemmKind.Universal: 'GemmUniversalOperation',
+        }
+
+        self.wmma_guard_start = (
+            "#if defined(CUTLASS_ARCH_WMMA_SM${sm_number}_ENABLED)"
+        )
+
+        self.separator = """
+///////////////////////////////////////////////////////////////////////////////////////////////////
+
+"""
+
+        self.header_template = """
+/*
+  Generated by gemm_operation.py - Do not edit.
+*/
+#pragma once
+#ifdef PADDLE_WITH_CUTLASS
+"""
+
+        self.namespace_template = """
+namespace phi {
+namespace sparse {
+"""
+        self.epilogue_template = """
+}  // namespace sparse
+}  // namespace phi
+#endif
+"""
+
+    def __exit__(self, exception_type, exception_value, traceback):
+
+        # Write includes
+        for incl, _ in self.includes.items():
+            include_statement = "#include \"%s\"\n" % incl
+            self.configuration_file.write(include_statement)
+
+        self.configuration_file.write(self.separator)
+        self.configuration_file.write(self.namespace_template)
+
+        # Write instance definitions in top-level namespace
+        for instance_definition in self.instance_definitions:
+            self.configuration_file.write(instance_definition)
+
+        for instance_wrapper in self.instance_wrappers:
+            self.configuration_file.write(instance_wrapper)
+
+        self.configuration_file.write(self.epilogue_template)
+        self.configuration_file.close()
+
+
+class GatherGemmScatterOperation(GemmOperation):
+    # cutlass transpose A and B in the library.py, so we transpose it back here
+    def __init__(
+        self,
+        gemm_kind,
+        arch,
+        tile_description,
+        A,
+        B,
+        C,
+        element_epilogue,
+        epilogue_functor=EpilogueFunctor.LinearCombination,
+        swizzling_functor=SwizzlingFunctor.Identity8,
+    ):
+
+        super().__init__(
+            gemm_kind,
+            arch,
+            tile_description,
+            A,
+            B,
+            C,
+            element_epilogue,
+            epilogue_functor=EpilogueFunctor.LinearCombination,
+            swizzling_functor=SwizzlingFunctor.Identity8,
+        )
+        self.ShortLayoutTypeNames = {
+            LayoutType.ColumnMajor: 't',
+            LayoutType.ColumnMajorInterleaved2: 't2',
+            LayoutType.ColumnMajorInterleaved32: 't32',
+            LayoutType.ColumnMajorInterleaved64: 't64',
+            LayoutType.RowMajor: 'n',
+            LayoutType.RowMajorInterleaved2: 'n2',
+            LayoutType.RowMajorInterleaved32: 'n32',
+            LayoutType.RowMajorInterleaved64: 'n64',
+            LayoutType.TensorNHWC: 'nhwc',
+            LayoutType.TensorNDHWC: 'ndhwc',
+            LayoutType.TensorNCHW: 'nchw',
+            LayoutType.TensorNGHWC: 'nghwc',
+            LayoutType.TensorNC32HW32: 'nc32hw32',
+            LayoutType.TensorNC64HW64: 'nc64hw64',
+            LayoutType.TensorC32RSK32: 'c32rsk32',
+            LayoutType.TensorC64RSK64: 'c64rsk64',
+        }
+
+    def layout_name(self):
+        return "%s%s" % (
+            self.ShortLayoutTypeNames[self.A.layout],
+            self.ShortLayoutTypeNames[self.B.layout],
+        )