Use tracemalloc for memory measurements.

benchmarks/benchmarks/__init__.py

@@ -5,7 +5,9 @@
 """Common code for benchmarks."""
 
 from os import environ
-import resource
+import tracemalloc
+
+import numpy as np
 
 
 def disable_repeat_between_setup(benchmark_object):
@@ -61,27 +63,34 @@ class TrackAddedMemoryAllocation:
         AVD's detection threshold and be treated as 'signal'. Results
         smaller than this value will therefore be returned as equal to this
         value, ensuring fractionally small noise / no noise at all.
+        Defaults to 1.0
 
-    """
+    RESULT_ROUND_DP : int
+        Number of decimal places of rounding on result values (in Mb).
+        Defaults to 1
 
-    RESULT_MINIMUM_MB = 5.0
+    """
 
-    @staticmethod
-    def process_resident_memory_mb():
-        return resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / 1024.0
+    RESULT_MINIMUM_MB = 1.0
+    RESULT_ROUND_DP = 1
 
     def __enter__(self):
-        self.mb_before = self.process_resident_memory_mb()
+        tracemalloc.start()
         return self
 
     def __exit__(self, *_):
-        self.mb_after = self.process_resident_memory_mb()
+        _, peak_mem_bytes = tracemalloc.get_traced_memory()
+        tracemalloc.stop()
+        # Save peak-memory allocation, scaled from bytes to Mb.
+        self._peak_mb = peak_mem_bytes * (2.0**-20)
 
     def addedmem_mb(self):
         """Return measured memory growth, in Mb."""
-        result = self.mb_after - self.mb_before
+        result = self._peak_mb
         # Small results are too vulnerable to noise being interpreted as signal.
         result = max(self.RESULT_MINIMUM_MB, result)
+        # Rounding makes results easier to read.
+        result = np.round(result, self.RESULT_ROUND_DP)
         return result
 
     @staticmethod