icemelon9 commented on a change in pull request #4158: [PERF] Parallelize
reduction for CPU
URL: https://github.com/apache/incubator-tvm/pull/4158#discussion_r344504236
##
File path: topi/python/topi/x86/reduction.py
##
@@ -0,0 +1,81 @@
+# 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.
+# pylint: disable=invalid-name
+"""x86 declaration and schedules."""
+from __future__ import absolute_import as _abs
+import tvm
+from .. import tag
+from .. import generic
+
+
+def _schedule_reduce(sch, out, is_idx_reduce=False):
+if len(sch[out].op.axis) >= 5:
+fused = sch[out].fuse(sch[out].op.axis[0], sch[out].op.axis[1],
sch[out].op.axis[2])
+sch[out].parallel(fused)
+elif len(sch[out].op.axis) >= 3:
+fused = sch[out].fuse(sch[out].op.axis[0], sch[out].op.axis[1],
sch[out].op.axis[2])
+sch[out].parallel(fused)
+elif len(sch[out].op.axis) >= 1:
+sch[out].parallel(sch[out].op.axis[0])
+
+
+@generic.schedule_reduce.register(["cpu"])
+def schedule_reduce(outs):
+outs = [outs] if isinstance(outs, tvm.tensor.Tensor) else outs
+sch = tvm.create_schedule([x.op for x in outs])
+scheduled_ops = []
+
+def traverse_before_reduce(operator):
+"""Internal travserse function"""
+if isinstance(operator, tvm.tensor.PlaceholderOp):
+return
+if tag.is_injective(operator.tag):
+sch[operator].compute_inline()
+for tensor in operator.input_tensors:
+if tensor.op not in scheduled_ops:
+traverse_before_reduce(tensor.op)
+else:
+raise RuntimeError("Unsupported operator: %s" % operator.tag)
+
+scheduled_ops.append(operator)
+
+def traverse_after_reduce(operator):
+"""Internal travserse function"""
+if tag.is_broadcast(operator.tag):
+if operator not in scheduled_ops:
+generic.schedule_injective_from_existing(sch, operator)
+for tensor in operator.input_tensors:
+traverse_after_reduce(tensor.op)
+elif operator.tag == 'comm_reduce':
+_schedule_reduce(sch, operator, is_idx_reduce=False)
+for tensor in operator.input_tensors:
+if tensor.op not in scheduled_ops:
+traverse_before_reduce(tensor.op)
+elif operator.tag == 'comm_reduce_idx':
+_schedule_reduce(sch, operator, is_idx_reduce=True)
+input_tensors = operator.input_tensors[0].op.input_tensors
+for tensor in input_tensors:
+if tensor.op not in scheduled_ops:
+traverse_before_reduce(tensor.op)
+else:
+raise RuntimeError("Unsupported operator: %s" % operator.tag)
+
+scheduled_ops.append(operator)
+
+traverse_after_reduce(outs[0].op)
+return sch
+
Review comment:
this is necessary
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