Add auto_optimize to SDFG API

dace/sdfg/sdfg.py

@@ -2463,6 +2463,38 @@ def simplify(self, validate=True, validate_all=False, verbose=False):
         from dace.transformation.passes.simplify import SimplifyPass
         return SimplifyPass(validate=validate, validate_all=validate_all, verbose=verbose).apply_pass(self, {})
 
+    def auto_optimize(self,
+                      device: dtypes.DeviceType,
+                      validate: bool = True,
+                      validate_all: bool = False,
+                      symbols: Dict[str, int] = None,
+                      use_gpu_storage: bool = False):
+        """
+        Runs a basic sequence of transformations to optimize a given SDFG to decent
+        performance. In particular, performs the following:
+            
+            * Simplify
+            * Auto-parallelization (loop-to-map)
+            * Greedy application of SubgraphFusion
+            * Tiled write-conflict resolution (MapTiling -> AccumulateTransient)
+            * Tiled stream accumulation (MapTiling -> AccumulateTransient)
+            * Collapse all maps to parallelize across all dimensions
+            * Set all library nodes to expand to ``fast`` expansion, which calls
+              the fastest library on the target device
+
+        :param device: the device to optimize for.
+        :param validate: If True, validates the SDFG after all transformations
+                         have been applied.
+        :param validate_all: If True, validates the SDFG after every step.
+        :param symbols: Optional dict that maps symbols (str/symbolic) to int/float
+        :param use_gpu_storage: If True, changes the storage of non-transient data to GPU global memory.
+        :note: Operates in-place on the given SDFG.
+        :note: This function is still experimental and may harm correctness in
+               certain cases. Please report an issue if it does.
+        """
+        from dace.transformation.auto.auto_optimize import auto_optimize
+        auto_optimize(device, validate, validate_all, symbols, use_gpu_storage)
+
     def _initialize_transformations_from_type(
         self,
         xforms: Union[Type, List[Type], 'dace.transformation.PatternTransformation'],