MLBEDSW-4219: Add tensor allocation info to summary
Added the theoretically minimum max memory usage and
the allocator overhead to the Vela summary.
Signed-off-by: erik.andersson@arm.com <erik.andersson@arm.com>
Change-Id: If373dfeaac50d6f8b56554d435bf22af2c3acda3
diff --git a/ethosu/vela/tensor_allocation.py b/ethosu/vela/tensor_allocation.py
index 621073a..b2ea7de 100644
--- a/ethosu/vela/tensor_allocation.py
+++ b/ethosu/vela/tensor_allocation.py
@@ -142,6 +142,17 @@
print()
+def calculate_allocation_efficiency(lrs):
+ lr_set = set(lrs.ranges.values())
+
+ size_at_time = [0] * (1 + max(lr.end_time for lr in lr_set))
+ for lr in lr_set:
+ for t in range(lr.start_time, lr.end_time + 1):
+ size_at_time[t] += lr.size
+
+ return max(size_at_time)
+
+
def allocate_tensors(
nng,
sg,
@@ -199,6 +210,7 @@
print_allocation(lrs, mem_area, mem_type_set, sg, verbose_allocation)
if mem_area == MemArea.Sram:
+ sg.min_mem_usage = calculate_allocation_efficiency(lrs)
# Mark Sram usage for all subgraphs
for sg_ in nng.subgraphs:
mark_sram_used_for_cascaded_passes(sg_, lrs)