From 7ea6cf872415d925014d0e0d2ad1af6be9073148 Mon Sep 17 00:00:00 2001
From: Lucian Petrica <lucianp@xilinx.com>
Date: Mon, 15 Jun 2020 13:09:37 +0000
Subject: [PATCH] Added floorplanning transform
---
src/finn/custom_op/fpgadataflow/__init__.py | 5 +-
.../transformation/fpgadataflow/floorplan.py | 80 +++++++++++++++++++
2 files changed, 83 insertions(+), 2 deletions(-)
create mode 100644 src/finn/transformation/fpgadataflow/floorplan.py
diff --git a/src/finn/custom_op/fpgadataflow/__init__.py b/src/finn/custom_op/fpgadataflow/__init__.py
index a688898f4..c4800011f 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 000000000..1d9a51875
--- /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)
--
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