[MetaSchedule] AutoBind rule and MutateThreadBinding

include/tvm/meta_schedule/mutator.h

@@ -119,13 +119,21 @@ class Mutator : public runtime::ObjectRef {
    * \return The created mutator.
    */
   TVM_DLL static Mutator MutateParallel(int64_t max_jobs_per_core);
-  /*! \brief Create a Mutator that mutates auto unroll step */
+  /*!
+   * \brief Create a Mutator that mutates auto unroll step
+   * \return The mutator created
+   */
   TVM_DLL static Mutator MutateUnroll();
   /*!
    * \brief Create a Mutator that mutates the outcome of SampleComputeLocation
    * \return The mutator created
    */
   TVM_DLL static Mutator MutateComputeLocation();
+  /*!
+   * \brief Create a Mutator that mutates auto thread binding.
+   * \return The mutator created
+   */
+  TVM_DLL static Mutator MutateThreadBinding();
   /*!
    * \brief Create a mutator with customized methods on the python-side.
    * \param f_initialize_with_tune_context The packed function of `InitializeWithTuneContext`.

include/tvm/meta_schedule/postproc.h

@@ -144,10 +144,10 @@ class Postproc : public runtime::ObjectRef {
   TVM_DLL static Postproc RewriteReductionBlock();
   /*!
    * \brief Create a postprocessor that adds thread binding to unbound blocks
-   * \param max_threadblock The max number of threadblocks in the cuda device.
+   * \param max_threadblocks The max number of threadblocks in the cuda device.
    * \return The postprocessor created.
    */
-  TVM_DLL static Postproc RewriteUnboundBlock(int max_threadblock);
+  TVM_DLL static Postproc RewriteUnboundBlock(int max_threadblocks);
   /*!
    * \brief Create a postprocessor that applies tensorization to annotated blocks
    * \param vectorize_init_loop Whether or not vectorize the initialization loop produced by

include/tvm/meta_schedule/schedule_rule.h

@@ -212,6 +212,13 @@ class ScheduleRule : public runtime::ObjectRef {
                                                          int max_vectorize_extent,         //
                                                          Array<Integer> unroll_max_steps,  //
                                                          bool unroll_explicit);
+  /*!
+   * \brief Auto bind loops around the block to BlockIdx and ThreadIdx
+   * \param max_threadblocks The maximum number of threadblock on GPU
+   * \param thread_extents Candidates of thread axis extent.
+   * \return The schedule rule created
+   */
+  TVM_DLL static ScheduleRule AutoBind(int max_threadblocks, Array<Integer> thread_extents);
   /*!
    * \brief Create a schedule rule with customized methods on the python-side.
    * \param f_initialize_with_tune_context The packed function of `InitializeWithTuneContext`.

python/tvm/meta_schedule/mutator/__init__.py

@@ -22,5 +22,6 @@
 from .mutator import Mutator, PyMutator
 from .mutate_compute_location import MutateComputeLocation
 from .mutate_tile_size import MutateTileSize
+from .mutate_thread_binding import MutateThreadBinding
 from .mutate_parallel import MutateParallel
 from .mutate_unroll import MutateUnroll

python/tvm/meta_schedule/mutator/mutate_thread_binding.py

@@ -0,0 +1,32 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+"""Mutator that mutates the thread binding extent"""
+from tvm._ffi.registry import register_object
+
+from .. import _ffi_api
+from .mutator import Mutator
+
+
+@register_object("meta_schedule.MutateThreadBinding")
+class MutateThreadBinding(Mutator):
+    """Mutator that mutates the binding extent"""
+
+    def __init__(self) -> None:
+        """Mutator that mutates the binding extent"""
+        self.__init_handle_by_constructor__(
+            _ffi_api.MutateThreadBinding,  # type: ignore # pylint: disable=no-member
+        )

python/tvm/meta_schedule/postproc/rewrite_unbound_block.py

@@ -17,6 +17,7 @@
 """A postprocessor that adds thread binding to unbound blocks"""
 
 from tvm._ffi.registry import register_object
+
 from .. import _ffi_api
 from .postproc import Postproc
 
@@ -25,8 +26,8 @@
 class RewriteUnboundBlock(Postproc):
     """A postprocessor that adds thread binding to unbound blocks"""
 
-    def __init__(self, max_threadblock: int = 256) -> None:
+    def __init__(self, max_threadblocks: int = 256) -> None:
         self.__init_handle_by_constructor__(
             _ffi_api.PostprocRewriteUnboundBlock,  # type: ignore # pylint: disable=no-member
-            max_threadblock,
+            max_threadblocks,
         )

python/tvm/meta_schedule/schedule_rule/__init__.py

@@ -20,6 +20,7 @@
 blocks in a schedule. See also PostOrderApply.
 """
 from .add_rfactor import AddRFactor
+from .auto_bind import AutoBind
 from .auto_inline import AutoInline
 from .cross_thread_reduction import CrossThreadReduction
 from .multi_level_tiling import MultiLevelTiling, MultiLevelTilingWithIntrin, ReuseType

python/tvm/meta_schedule/schedule_rule/auto_bind.py

@@ -0,0 +1,49 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+"""Auto-bind Rule that binds blocks to threads if needed"""
+from typing import List, Optional
+
+from tvm._ffi import register_object
+
+from .. import _ffi_api
+from .schedule_rule import ScheduleRule
+
+
+@register_object("meta_schedule.AutoBind")
+class AutoBind(ScheduleRule):
+    """Auto bind loops around the block to BlockIdx and ThreadIdx
+
+    Parameters
+    ----------
+    max_threadblocks: int
+        The maximum number of threadblock on GPU.
+    thread_extents: Optional[List[int]]
+        Candidates of thread axis extent.
+    """
+
+    def __init__(
+        self,
+        max_threadblocks: int = 256,
+        thread_extents: Optional[List[int]] = None,
+    ) -> None:
+        if thread_extents is None:
+            thread_extents = [32, 64, 128, 256, 512, 1024]
+        self.__init_handle_by_constructor__(
+            _ffi_api.ScheduleRuleAutoBind,  # type: ignore # pylint: disable=no-member
+            max_threadblocks,
+            thread_extents,
+        )

python/tvm/meta_schedule/testing/conv2d_winograd_cpu.py

@@ -131,7 +131,7 @@ def conv2d_winograd_cpu(
             vh, vw, p_3, co_1, r_a_1, r_b_1 = T.axis.remap(
                 "SSSSRR", [i0_7, i1_7, i2_5, i3_5, i4_2, i5_1]
             )
-            T.block_attr({"schedule_rule": "meta_schedule.winograd_inverse"})
+            T.block_attr({"schedule_rule": "meta_schedule.winograd_inverse.llvm"})
             T.reads(
                 [
                     inverse[vh, vw, p_3, co_1],

python/tvm/meta_schedule/testing/conv2d_winograd_cuda.py

@@ -132,7 +132,7 @@ def conv2d_winograd_cuda(  # type: ignore
             vh, vw, p_3, co_1, r_a_1, r_b_1 = T.axis.remap(
                 "SSSSRR", [i0_7, i1_7, i2_5, i3_5, i4_2, i5_1]
             )
-            T.block_attr({"schedule_rule": "meta_schedule.winograd_inverse"})
+            T.block_attr({"schedule_rule": "meta_schedule.winograd_inverse.cuda"})
             T.reads(
                 [
                     inverse[vh, vw, p_3, co_1],

python/tvm/meta_schedule/testing/schedule_rule.py

@@ -17,6 +17,7 @@
 """Default schedule rules"""
 from tvm.meta_schedule.schedule_rule import (
     AddRFactor,
+    AutoBind,
     AutoInline,
     CrossThreadReduction,
     MultiLevelTiling,
@@ -28,6 +29,13 @@
 from tvm.target import Target
 
 
+def auto_bind(target: Target) -> ScheduleRule:
+    """Default schedule rules for auto bind"""
+    if target.kind.name == "cuda":
+        return AutoBind(max_threadblocks=256, thread_extents=[32, 64, 128, 256, 512, 1024])
+    raise NotImplementedError(f"{target.kind.name} is not supported")
+
+
 def auto_inline(target: Target) -> ScheduleRule:
     """Default schedule rules for auto inline"""
     if target.kind.name == "llvm":

python/tvm/meta_schedule/tune.py

@@ -156,6 +156,10 @@ def _sch_rules() -> List[ScheduleRule]:
                 unroll_max_steps=[0, 16, 64, 512, 1024],
                 unroll_explicit=True,
             ),
+            M.AutoBind(
+                max_threadblocks=256,
+                thread_extents=[32, 64, 128, 256, 512, 1024],
+            ),
         ]
 
     @staticmethod
@@ -177,7 +181,8 @@ def _mutator_probs() -> Dict[Mutator, float]:
 
         return {
             M.MutateTileSize(): 0.9,
-            M.MutateUnroll(): 0.1,
+            M.MutateUnroll(): 0.08,
+            M.MutateThreadBinding(): 0.02,
         }
 
 
@@ -836,6 +841,7 @@ def tune_relay(
     """
     # pylint: disable=import-outside-toplevel
     from tvm.relay import build as relay_build
+
     from .relay_integration import extract_task_from_relay
 
     # pylint: disable=protected-access, enable=import-outside-toplevel

python/tvm/topi/cuda/conv2d_nhwc_winograd.py

@@ -440,7 +440,7 @@ def nhwc_winograd_cuda(
             bgemm[r_a][r_b][p][co] * A[r_a][vh] * A[r_b][vw], axis=[r_a, r_b]
         ),
         name="inverse",
-        attrs={"schedule_rule": "meta_schedule.winograd_inverse"},
+        attrs={"schedule_rule": "meta_schedule.winograd_inverse.cuda"},
     )
 
     # Output

python/tvm/topi/cuda/conv2d_winograd.py

@@ -152,7 +152,7 @@ def winograd_cuda(cfg, data, kernel, strides, padding, dilation, out_dtype, pre_
             bgemm[r_a][r_b][co][p] * A[r_a][vh] * A[r_b][vw], axis=[r_a, r_b]
         ),
         name="inverse",
-        attrs={"schedule_rule": "meta_schedule.winograd_inverse"},
+        attrs={"schedule_rule": "meta_schedule.winograd_inverse.cuda"},
     )
 
     # output

python/tvm/topi/nn/conv2d.py

@@ -1096,6 +1096,11 @@ def _conv2d_winograd_nhwc_impl(
         bgemm = auto_scheduler.rewrite_compute_body(bgemm, auto_scheduler_rewritten_layout)
 
     # inverse transform
+    if target is not None:
+        target_kind = "meta_schedule.winograd_inverse." + target.kind.name
+    else:
+        target_kind = "None"
+
     r_a = te.reduce_axis((0, alpha), "r_a")
     r_b = te.reduce_axis((0, alpha), "r_b")
     inverse = te.compute(
@@ -1106,7 +1111,7 @@ def _conv2d_winograd_nhwc_impl(
         name="inverse",
         attrs={
             "auto_scheduler_simplify_const_tensor_indices": ["vh", "vw", "r_a", "r_b"],
-            "schedule_rule": "meta_schedule.winograd_inverse",
+            "schedule_rule": target_kind,
         },
         # the attrs are necessary hints for the auto-scheduler
     )