[SCHEDULE] Fix schedule for big array (apache#1340)

topi/python/topi/cuda/extern.py

@@ -2,15 +2,7 @@
 """Schedule for cudnn and miopen extern op"""
 import tvm
 from .. import generic
-
-def _schedule_output(op, sch):
-    x = op.output(0)
-    fused = sch[x].fuse(*sch[x].op.axis)
-    num_thread = tvm.target.current_target(allow_none=False).max_num_threads
-    bx, tx = sch[x].split(fused, factor=num_thread)
-    sch[x].bind(bx, tvm.thread_axis("blockIdx.x"))
-    sch[x].bind(tx, tvm.thread_axis("threadIdx.x"))
-    return sch
+from .injective import _schedule_injective
 
 
 @generic.schedule_extern.register(["cuda", "gpu"])
@@ -36,5 +28,5 @@ def schedule_extern(outs):
     for out in outs:
         if isinstance(out.op, tvm.tensor.ExternOp):
             continue
-        _schedule_output(out.op, s)
+        _schedule_injective(out.op, s)
     return s

topi/python/topi/cuda/injective.py

@@ -1,15 +1,32 @@
 # pylint: disable=invalid-name, unused-variable,
 """Schedule for composition of injective operator"""
 import tvm
-from .. import generic
+from .. import generic, util
 
 def _schedule_injective(op, sch):
     x = op.output(0)
     fused = sch[x].fuse(*sch[x].op.axis)
     num_thread = tvm.target.current_target(allow_none=False).max_num_threads
-    bx, tx = sch[x].split(fused, factor=num_thread)
-    sch[x].bind(bx, tvm.thread_axis("blockIdx.x"))
-    sch[x].bind(tx, tvm.thread_axis("threadIdx.x"))
+    max_block = 256
+
+    try:
+        const_size = util.get_const_int(util.prod(x.shape))
+        max_block = 256
+        need_block_split = const_size > max_block * num_thread
+    except ValueError:
+        need_block_split = False
+
+    if need_block_split:
+        xo, xi = sch[x].split(fused, factor=num_thread * max_block)
+        bx, tx = sch[x].split(xi, factor=num_thread)
+        sch[x].reorder(bx, tx, xo)
+        sch[x].bind(bx, tvm.thread_axis("blockIdx.x"))
+        sch[x].bind(tx, tvm.thread_axis("threadIdx.x"))
+    else:
+        bx, tx = sch[x].split(fused, factor=num_thread)
+        sch[x].bind(tx, tvm.thread_axis("threadIdx.x"))
+        sch[x].bind(bx, tvm.thread_axis("blockIdx.x"))
+
     return sch
 
 

topi/python/topi/util.py

@@ -2,6 +2,28 @@
 from __future__ import absolute_import as _abs
 import tvm
 
+
+def prod(x):
+    """Get the product of every items in the tuple.
+
+    Parameters
+    ----------
+    x: tuple
+        Input tuple
+
+    Returns
+    -------
+    value : Expr
+        The result value
+    """
+    if not x:
+        return tvm.const(1, "int32")
+    res = x[0]
+    for i in range(1, len(x)):
+        res = res * x[i]
+    return res
+
+
 def get_const_int(expr):
     """Verifies expr is integer and get the constant value.
 

topi/tests/python/test_topi_relu.py

@@ -71,13 +71,18 @@ def _prelu_numpy(x, W):
 def test_relu():
     verify_relu(10, 128)
 
+def test_schedule_big_array():
+    verify_relu(1024 * 100 , 512)
+
+
 def test_leaky_relu():
     verify_leaky_relu(100, 0.1)
 
 def test_prelu():
     verify_prelu((1, 3, 2, 2), (3,))
 
 if __name__ == "__main__":
+    test_schedule_big_array()
     test_relu()
     test_leaky_relu()
     test_prelu()