[GitHub] [incubator-tvm] icemelon9 commented on a change in pull request #5752: Make batch matrix multiplication on GPU tunable

[GitBox <gi...@apache.org>]

icemelon9 commented on a change in pull request #5752:
URL: https://github.com/apache/incubator-tvm/pull/5752#discussion_r437695904



##########
File path: topi/python/topi/cuda/batch_matmul.py
##########
@@ -51,55 +62,73 @@ def _schedule(op):
             C = s.outputs[0].output(0)
 
         b, y, x = s[C].op.axis
-        y_bn = get_max_power2_factor(M, 64)
-        x_bn = get_max_power2_factor(N, 64)
-        by, y = s[C].split(y, y_bn)
-        bx, x = s[C].split(x, x_bn)
-        y_nthreads = min(y_bn, 8)
-        x_nthreads = min(x_bn, 8)
-        ty, yi = s[C].split(y, nparts=y_nthreads)
-        tx, xi = s[C].split(x, nparts=x_nthreads)
-        thread_x = te.thread_axis((0, x_nthreads), "threadIdx.x")
-        thread_y = te.thread_axis((0, y_nthreads), "threadIdx.y")
+
+        cfg.define_split("tile_y", y, num_outputs=3)
+        cfg.define_split("tile_x", x, num_outputs=3)
+        cfg.define_knob("auto_unroll_max_step", [8, 16, 32, 64])
+        target = tvm.target.Target.current()
+        if target.target_name in ['nvptx', 'rocm']:
+            # llvm-based backends cannot do non-explicit unrolling
+            cfg.define_knob("unroll_explicit", [1])
+        else:
+            cfg.define_knob("unroll_explicit", [0, 1])
+
+        if cfg.is_fallback:

Review comment:
       I think you still need to add `"unroll_explicit"` in the fallback cfg.




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