commit 3438c929528583bc019055ad7057c08271b0cee7
author erik.andersson@arm.com <erik.andersson@arm.com> Wed Mar 24 10:32:09 2021 +0100
committer erik.andersson@arm.com <erik.andersson@arm.com> Tue Mar 30 09:20:00 2021 +0200
tree ea0f8af0e5f23e567c6d31f4f7c639a0e94f6dbf
parent 9bb1e2ed361286769c362f002910d1dbd1736b05

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

ethosu/vela/nn_graph.py

diff --git a/ethosu/vela/nn_graph.py b/ethosu/vela/nn_graph.py
index c45d0e3..1973487 100644
--- a/ethosu/vela/nn_graph.py
+++ b/ethosu/vela/nn_graph.py
@@ -154,6 +154,7 @@
 
         self.memory_used = {}
         self.memory_used_per_type = {}
+        self.min_mem_usage = 0
 
     def __str__(self):
         return "<nng.Subgraph '%s',  n_passes=%d, n_cascaded_passes=%d>" % (

ethosu/vela/stats_writer.py

diff --git a/ethosu/vela/stats_writer.py b/ethosu/vela/stats_writer.py
index d867368..3d92d2c 100644
--- a/ethosu/vela/stats_writer.py
+++ b/ethosu/vela/stats_writer.py
@@ -223,6 +223,7 @@
     bandwidths,
     batch_size,
     memory_used,
+    min_mem_usage,
     num_passes,
     num_cascaded_passes,
     n_operations=0,
@@ -265,6 +266,11 @@
         aug_label = label + " used"
 
         print(f"Total {aug_label:25}          {memory_used[mem_area] / 1024.0:12.2f} KiB", file=f)
+        if mem_area == MemArea.Sram and min_mem_usage:
+            mem_used = memory_used[[mem_area for mem_area, _ in mem_area_labels if "SRAM" in mem_area][0]] / 1024.0
+            fraction = (mem_used - min_mem_usage / 1024.0) / (min_mem_usage / 1024.0)
+            print(f"Theoretical minimum SRAM usage{min_mem_usage/1024.0:23.2F} KiB", file=f)
+            print(f"Allocator overhead{100*fraction:35.2F} %", file=f)
 
     print(file=f)
     print(f"{num_passes:d} passes fused into {num_cascaded_passes:d}", file=f)
@@ -353,6 +359,7 @@
     n_cascaded_passes = sum(len(sg.cascaded_passes) for sg in nng.subgraphs)
     n_operations = sum(len(ps.ops) for sg in nng.subgraphs for ps in sg.passes)
     cpu_operations = sum((ps.ops for sg in nng.subgraphs for ps in sg.passes if ps.placement == PassPlacement.Cpu), [])
+    min_mem_usage = max(sg.min_mem_usage for sg in nng.subgraphs)
     return print_performance_metrics_for_strat(
         arch,
         nng.name,
@@ -361,6 +368,7 @@
         nng.bandwidths,
         nng.batch_size,
         nng.memory_used,
+        min_mem_usage,
         n_passes,
         n_cascaded_passes,
         n_operations,

ethosu/vela/tensor_allocation.py

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)