diff --git a/loopy/statistics.py b/loopy/statistics.py
index 3d44826bb47026c11ff28d95b1fa758bda9206f4..31cc94e733dc10ff2e26d9fb8d0ff28d757b4975 100755
--- a/loopy/statistics.py
+++ b/loopy/statistics.py
@@ -362,7 +362,7 @@ class ToCountMap(object):
def to_bytes(self):
"""Convert counts to bytes using data type in map key.
- :return: A :class:`ToCountMap` mapping each original key to a
+ :return: A :class:`ToCountMap` mapping each original key to an
:class:`islpy.PwQPolynomial` with counts in bytes rather than
instances.
@@ -404,7 +404,7 @@ class ToCountMap(object):
def sum(self):
"""Add all counts in ToCountMap.
- :return: A :class:`islpy.PwQPolynomial` or :class:`int` containing the
+ :return: An :class:`islpy.PwQPolynomial` or :class:`int` containing the
sum of counts.
"""
@@ -462,17 +462,17 @@ class CountGranularity:
"""Strings specifying whether an operation should be counted once per
*work-item*, *sub-group*, or *work-group*.
- .. attribute :: WORKITEM
+ .. attribute:: WORKITEM
A :class:`str` that specifies that an operation should be counted
once per *work-item*.
- .. attribute :: SUBGROUP
+ .. attribute:: SUBGROUP
A :class:`str` that specifies that an operation should be counted
once per *sub-group*.
- .. attribute :: WORKGROUP
+ .. attribute:: WORKGROUP
A :class:`str` that specifies that an operation should be counted
once per *work-group*.
@@ -503,11 +503,13 @@ class Op(Record):
.. attribute:: count_granularity
A :class:`str` that specifies whether this operation should be counted
- once per *work-item*, *sub-group*, or *work-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 work-group sharing local memory. A sub-group is an
+ once per *work-item*, *sub-group*, or *work-group*. The granularities
+ allowed can be found in :class:`CountGranularity`, and may be accessed,
+ e.g., as ``CountGranularity.WORKITEM``. 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 work-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.
@@ -569,11 +571,13 @@ class MemAccess(Record):
.. attribute:: count_granularity
A :class:`str` that specifies whether this operation should be counted
- once per *work-item*, *sub-group*, or *work-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 work-group sharing local memory. A sub-group is an
+ once per *work-item*, *sub-group*, or *work-group*. The granularities
+ allowed can be found in :class:`CountGranularity`, and may be accessed,
+ e.g., as ``CountGranularity.WORKITEM``. 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 work-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.
@@ -1238,12 +1242,17 @@ def get_op_map(knl, numpy_types=True, count_redundant_work=False,
(Likely desirable for performance modeling, but undesirable for code
optimization.)
- :arg subgroup_size: (currently unused) 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.
+ :arg subgroup_size: (currently unused) An :class:`int`, :class:`string`
+ ``'guess'``, or *None* 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, if this fails an error will be raised. If a :class:`string`
+ ``'guess'`` is passed as the subgroup_size, get_mem_access_map will
+ attempt to find the sub-group size using the device and, if
+ unsuccessful, will make a wild guess.
:return: A :class:`ToCountMap` of **{** :class:`Op` **:**
:class:`islpy.PwQPolynomial` **}**.
@@ -1345,16 +1354,17 @@ 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. 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, if this fails an error will be raised. 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 size using the
- device and, if unsuccessful, will make a wild guess.
+ :arg subgroup_size: An :class:`int`, :class:`string` ``'guess'``, or
+ *None* 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, if this fails
+ an error will be raised. If a :class:`string` ``'guess'`` is passed as
+ the subgroup_size, get_mem_access_map will attempt to find the
+ sub-group size using the device and, if unsuccessful, will make a wild
+ guess.
:return: A :class:`ToCountMap` of **{** :class:`MemAccess` **:**
:class:`islpy.PwQPolynomial` **}**.
@@ -1574,15 +1584,21 @@ def get_synchronization_map(knl, subgroup_size=None):
:arg knl: A :class:`loopy.LoopKernel` whose barriers are to be counted.
- :arg subgroup_size: (currently unused) 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.
+ :arg subgroup_size: (currently unused) An :class:`int`, :class:`string`
+ ``'guess'``, or *None* 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, if this fails an error will be raised. If a :class:`string`
+ ``'guess'`` is passed as the subgroup_size, get_mem_access_map will
+ attempt to find the sub-group size using the device and, if
+ unsuccessful, will make a wild guess.
- :return: A dictionary mapping each type of synchronization event to a
- :class:`islpy.PwQPolynomial` holding the number of events per work-item.
+ :return: A dictionary mapping each type of synchronization event to an
+ :class:`islpy.PwQPolynomial` holding the number of events per
+ work-item.
Possible keys include ``barrier_local``, ``barrier_global``
(if supported by the target) and ``kernel_launch``.
@@ -1794,7 +1810,8 @@ def get_synchronization_poly(knl):
"""Count the number of synchronization events each work-item encounters in
a loopy kernel.
- get_synchronization_poly is deprecated. Use get_synchronization_map instead.
+ get_synchronization_poly is deprecated. Use get_synchronization_map
+ instead.
"""
warn_with_kernel(knl, "deprecated_get_synchronization_poly",