defined work-item, sub-group, and group

loopy/statistics.py

@@ -501,7 +501,12 @@ class Op(Record):
     .. attribute:: count_granularity
 
        A :class:`str` that specifies whether this operation should be counted
-       once per *work-item*, *sub-group*, or *group*.
+       once per *work-item*, *sub-group*, or *group*. A work-item is a single
+       instance of computation executing on a single processor (think 'thread'),
+       a collection of which may be grouped together into a work-group. Each
+       work-group executes on a single compute unit with all work-items within
+       the group sharing local memory. A sub-group is an implementation-dependent
+       grouping of work-items within a work-group, analagous to an NVIDIA CUDA warp.
 
     """
 
@@ -1320,10 +1325,15 @@ def get_mem_access_map(knl, numpy_types=True, count_redundant_work=False,
         (Likely desirable for performance modeling, but undesirable for
         code optimization.)
 
-    :arg subgroup_size: A :class:`int` that specifies the sub-group size. This
-        is used, e.g., when counting a :class:`MemAccess` whose count_granularity
-        specifies that it should only be counted once per sub-group. The default
-        sub-group_size is 32.
+    :arg subgroup_size: A :class:`int` that specifies the sub-group size. An OpenCL
+        sub-group is an implementation-dependent grouping of work-items within a
+        work-group, analagous to an NVIDIA CUDA warp. subgroup_size is used, e.g.,
+        when counting a :class:`MemAccess` whose count_granularity specifies that it
+        should only be counted once per sub-group. If set to None an attempt to find
+        the sub-group size using the device will be made. A :class:`string` 'guess'
+        may also be passed as the subgroup_size, in which case get_mem_access_map
+        will attempt to find the sub-group sizeusing the device and, if
+        unsuccessful, will make a wild guess.
 
     :return: A :class:`ToCountMap` of **{** :class:`MemAccess` **:**
         :class:`islpy.PwQPolynomial` **}**.