MLBEDSW-7220: Updated uncascaded memory calculation
- The uncascaded SRAM usage for an op in the cascade builder did not
take into account that OFM will be reusing the IFM for elementwise ops
and resulted in wrong values for the uncascaded memory.
- Changed code to use the _estimate_sram_usage since this
function does the calucation correctly.
Change-Id: I681bcf6e45ee869bbfb92306869b18ee4a838325
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
diff --git a/ethosu/vela/cascade_builder.py b/ethosu/vela/cascade_builder.py
index 3a3026f..0e651b9 100644
--- a/ethosu/vela/cascade_builder.py
+++ b/ethosu/vela/cascade_builder.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2021-2022 Arm Limited and/or its affiliates <open-source-office@arm.com>
+# SPDX-FileCopyrightText: Copyright 2021-2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
#
# SPDX-License-Identifier: Apache-2.0
#
@@ -222,7 +222,6 @@
break
# Get the size of the FeatureMap buffers between current and neighbouring Ops
- op_full_ifm = current_op.ifm_size_in_bytes()
op_full_ofm = current_op.ofm_size_in_bytes()
_, op_ifm_buffer = buffers.get_buffer(producer, current_op, ref_cost)
@@ -230,7 +229,7 @@
op_weight_buffer = sum(tens.storage_size() for tens in ref_cost[current_op].buffered_weight_tensors)
# Calculate the uncascaded memory requirement for current Op
- uncascaded_sram_usage = op_full_ifm + op_full_ofm + self.non_local_mem_usage.get(current_op, 0)
+ uncascaded_sram_usage = self._estimate_sram_usage(current_op, fallback_cost[current_op])
# Add current Op to cascade
ops_in_cascade.append(current_op)