From fc1f12dd0da69c7ed90bda82319c0213b868212a Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Thu, 3 Sep 2020 13:19:43 +0200
Subject: [PATCH] [Analysis] introduce dataflow_performance to extract key perf
info
---
.../fpgadataflow/dataflow_performance.py | 75 +++++++++++++++++++
1 file changed, 75 insertions(+)
create mode 100644 src/finn/analysis/fpgadataflow/dataflow_performance.py
diff --git a/src/finn/analysis/fpgadataflow/dataflow_performance.py b/src/finn/analysis/fpgadataflow/dataflow_performance.py
new file mode 100644
index 000000000..6f19254d6
--- /dev/null
+++ b/src/finn/analysis/fpgadataflow/dataflow_performance.py
@@ -0,0 +1,75 @@
+# 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.util.fpgadataflow import is_fpgadataflow_node
+
+
+def dataflow_performance(model):
+ """Extract key performance indicators from given model with dataflow nodes.
+
+ Preconditions:
+ - model consists of fpgadataflow nodes
+ - model has cycle estimates annotated (see AnnotateCycles transformation)
+ - nodes have unique names (see GiveUniqueNodeNames)
+
+ Returns:
+ - max_cycles : number of cycles for slowest node
+ - max_cycles_node_name : name of slowest node
+ - critical_path_cycles : total expected latency from input to output
+ """
+ latency_at_node_output = {}
+ max_cycles = 0
+ max_node_name = ""
+
+ for node in model.graph.node:
+ if is_fpgadataflow_node(node) is True:
+ inst = getCustomOp(node)
+ node_cycles = inst.get_nodeattr("cycles_estimate")
+ if node_cycles > max_cycles:
+ max_cycles = node_cycles
+ max_node_name = node.name
+ if node.name not in latency_at_node_output:
+ # calculate based on input(s)
+ predecessors = model.find_direct_predecessors(node)
+ if predecessors is None:
+ # no predecessors, node is first node
+ max_pred_latency = 0
+ else:
+ # find max of any of predecessors
+ pred_latencies = map(
+ lambda x: latency_at_node_output[x.name], predecessors
+ )
+ max_pred_latency = max(pred_latencies)
+ latency_at_node_output[node.name] = node_cycles + max_pred_latency
+ critical_path_cycles = max(latency_at_node_output.values())
+ return {
+ "critical_path_cycles": critical_path_cycles,
+ "max_cycles": max_cycles,
+ "max_cycles_node_name": max_node_name,
+ }
--
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