1 files changed, 85 insertions, 0 deletions
diff --git a/doc/source/reference/c-api/data_memory.rst b/doc/source/reference/c-api/data_memory.rst
index 2084ab5d0..ec32223bd 100644
--- a/doc/source/reference/c-api/data_memory.rst
+++ b/doc/source/reference/c-api/data_memory.rst
@@ -159,3 +159,88 @@ A better technique would be to use a ``PyCapsule`` as a base object:
         return NULL;
     }
     ...
+
+Memory Allocation
+-----------------
+
+Note that since Python 3.6 (or newer), the builtin ``tracemalloc`` module can be used to
+track allocations inside NumPy. NumPy places its CPU memory allocations into the 
+``np.lib.tracemalloc_domain`` domain.
+For additional information, check: `https://docs.python.org/3/library/tracemalloc.html`.
+
+Here is an example on how to use ``np.lib.tracemalloc_domain``:
+
+.. code-block:: python
+
+"""
+   The goal of this example is to show how to trace memory
+   from an application that has NumPy and non-NumPy sections.
+   We only select the sections using NumPy related calls.
+"""
+
+import tracemalloc
+import numpy as np
+
+# Flag to determine if we select NumPy domain
+use_np_domain = True
+
+nx = 300
+ny = 500
+
+# Start to trace memory
+tracemalloc.start()
+
+# Section 1
+# ---------
+
+# NumPy related call
+a = np.zeros((nx,ny))
+
+# non-NumPy related call
+b = [i**2 for i in range(nx*ny)]
+
+snapshot1 = tracemalloc.take_snapshot()
+# We filter the snapshot to only select NumPy related calls
+np_domain = np.lib.tracemalloc_domain
+dom_filter = tracemalloc.DomainFilter(inclusive=use_np_domain,
+                                      domain=np_domain)
+snapshot1 = snapshot1.filter_traces([dom_filter])
+top_stats1 = snapshot1.statistics('traceback')
+
+print("================ SNAPSHOT 1 =================")
+for stat in top_stats1:
+    print(f"{stat.count} memory blocks: {stat.size / 1024:.1f} KiB")
+    print(stat.traceback.format()[-1])
+
+# Clear traces of memory blocks allocated by Python
+# before moving to the next section.
+tracemalloc.clear_traces()
+
+# Section 2
+#----------
+
+# We are only using NumPy
+c = np.sum(a*a)
+
+snapshot2 = tracemalloc.take_snapshot()
+top_stats2 = snapshot2.statistics('traceback')
+
+print()
+print("================ SNAPSHOT 2 =================")
+for stat in top_stats2:
+    print(f"{stat.count} memory blocks: {stat.size / 1024:.1f} KiB")
+    print(stat.traceback.format()[-1])
+
+tracemalloc.stop()
+
+print()
+print("============================================")
+print("\nTracing Status : ", tracemalloc.is_tracing())
+
+try:
+    print("\nTrying to Take Snapshot After Tracing is Stopped.")
+    snap = tracemalloc.take_snapshot()
+except Exception as e:
+    print("Exception : ", e)
+
+...