diff --git a/src/finn/custom_op/fpgadataflow/__init__.py b/src/finn/custom_op/fpgadataflow/__init__.py
index a688898f4a43b33fd3f07cda12144b84829e451f..c4800011fe2c944fa877b12d0247795beda4a5e6 100644
--- a/src/finn/custom_op/fpgadataflow/__init__.py
+++ b/src/finn/custom_op/fpgadataflow/__init__.py
@@ -88,6 +88,8 @@ class HLSCustomOp(CustomOp):
             "res_hls": ("s", False, ""),
             "res_synth": ("s", False, ""),
             "rtlsim_so": ("s", False, ""),
+            # partitioning info
+            "partition_id": ("i", False, 0),
             # input and output FIFO depths
             "inFIFODepth": ("i", False, 2),
             "outFIFODepth": ("i", False, 2),
@@ -219,7 +221,6 @@ class HLSCustomOp(CustomOp):
         self.code_gen_dict["$CLKPERIOD$"] = [str(clk)]
         self.code_gen_dict["$EXTRA_DIRECTIVES$"] = self.ipgen_extra_directives()
 
-
         template = self.ipgentcl_template
 
         for key in self.code_gen_dict:
@@ -235,7 +236,7 @@ class HLSCustomOp(CustomOp):
     def ipgen_extra_directives(self):
         "Return a list of extra tcl directives for HLS synthesis."
         return []
-        
+
     def ipgen_singlenode_code(self):
         """Builds the bash script for ip generation using the IPGenBuilder from
         finn.util.fpgadataflow."""
diff --git a/src/finn/transformation/fpgadataflow/floorplan.py b/src/finn/transformation/fpgadataflow/floorplan.py
new file mode 100644
index 0000000000000000000000000000000000000000..1d9a51875499d77f384c03f54009a9dd1001dea0
--- /dev/null
+++ b/src/finn/transformation/fpgadataflow/floorplan.py
@@ -0,0 +1,80 @@
+# Copyright (c) 2020, Xilinx
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# * Redistributions of source code must retain the above copyright notice, this
+#   list of conditions and the following disclaimer.
+#
+# * Redistributions in binary form must reproduce the above copyright notice,
+#   this list of conditions and the following disclaimer in the documentation
+#   and/or other materials provided with the distribution.
+#
+# * Neither the name of FINN nor the names of its
+#   contributors may be used to endorse or promote products derived from
+#   this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+from finn.custom_op.registry import getCustomOp
+from finn.transformation import Transformation
+from finn.util.basic import get_by_name
+
+
+class Floorplan(Transformation):
+    """Perform Floorplanning of the dataflow design. Separate DMAs into their own
+    partitions IDs, and TODO: split the design into sections of defined size"""
+
+    def __init__(self, limits=None):
+        super().__init__()
+        self.resource_limits = limits
+
+    def apply(self, model):
+        target_partition_id = 0
+        # we currently assume that all dataflow nodes belonging to the same partition
+        # are connected to each other and there is a single input/output to/from each.
+        all_nodes = list(model.graph.node)
+        df_nodes = list(
+            filter(lambda x: get_by_name(x.attribute, "backend") is not None, all_nodes)
+        )
+        dma_nodes = list(filter(lambda x: x.op_type == "IODMA", df_nodes))
+
+        non_dma_nodes = list(filter(lambda x: x not in dma_nodes, df_nodes))
+        dyn_tlastmarker_nodes = list(
+            filter(
+                lambda x: x.op_type == "TLastMarker"
+                and getCustomOp(x).get_nodeattr("DynIters") == "true",
+                non_dma_nodes,
+            )
+        )
+
+        non_dma_nodes = list(
+            filter(lambda x: x not in dyn_tlastmarker_nodes, non_dma_nodes)
+        )
+
+        for node in dma_nodes:
+            node_inst = getCustomOp(node)
+            node_inst.set_nodeattr("partition_id", target_partition_id)
+            target_partition_id += 1
+
+        for node in dyn_tlastmarker_nodes:
+            node_inst = getCustomOp(node)
+            node_inst.set_nodeattr("partition_id", target_partition_id)
+            target_partition_id += 1
+
+        for node in non_dma_nodes:
+            # TODO: implement proper floorplanning; for now just a single partition
+            node_inst = getCustomOp(node)
+            node_inst.set_nodeattr("partition_id", target_partition_id)
+
+        return (model, False)