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authorSebastian Berg <sebastian@sipsolutions.net>2020-03-17 18:28:18 -0500
committerSebastian Berg <sebastian@sipsolutions.net>2020-03-18 09:20:19 -0500
commit1400cea851cfffac0345d7fa21ca0bcf5c874885 (patch)
tree3253664144951e3d10d8c2889ad7a44f00ef679c /doc/source/reference
parent950f8a92d87c37e5f3c5aeab8aabe79a0eb3405e (diff)
downloadnumpy-1400cea851cfffac0345d7fa21ca0bcf5c874885.tar.gz
Further DOC-Fixup base don Ross' review
Diffstat (limited to 'doc/source/reference')
-rw-r--r--doc/source/reference/global_state.rst32
1 files changed, 16 insertions, 16 deletions
diff --git a/doc/source/reference/global_state.rst b/doc/source/reference/global_state.rst
index 9cbe03f97..2a163390e 100644
--- a/doc/source/reference/global_state.rst
+++ b/doc/source/reference/global_state.rst
@@ -32,31 +32,31 @@ Madvise Hugepage on Linux
-------------------------
When working with very large arrays on modern Linux kernels,
-you can experience a significant speedup when transparent
-hugepage is enabled.
-The current system policy for transparent hugepages can be
-seen by::
+you can experience a significant speedup when
+`transparent hugepage <https://www.kernel.org/doc/html/latest/admin-guide/mm/transhuge.html>`_
+is used.
+The current system policy for transparent hugepages can be seen by::
cat /sys/kernel/mm/transparent_hugepage/enabled
-on most kernels. When set to ``madvise`` NumPy will typically
-use hugepages for a performance boost. This behaviour can
-be set through the environment variable::
+When set to ``madvise`` NumPy will typically use hugepages for a performance
+boost. This behaviour can be modified by setting the environment variable::
NUMPY_MADVISE_HUGEPAGE=0
-or ``1`` for enabling it. When not set, the default is to use
-madvise on Kernels 4.6 and newer. These kernels presumably
-experience a large speedup when set.
+or setting it to ``1`` to always enable it. When not set, the default
+is to use madvise on Kernels 4.6 and newer. These kernels presumably
+experience a large speedup with hugepage support.
This flag is checked at import time.
-Interoperability
-===============
+Interoperability-Related Options
+================================
The array function protocol which allows array-like objects to
hook into the NumPy API is currently enabled by default.
-It can be disabled using::
+This option exists since NumPy 1.16 and is enabled by default since
+NumPy 1.17. It can be disabled using::
NUMPY_EXPERIMENTAL_ARRAY_FUNCTION=0
@@ -64,8 +64,8 @@ See also :py:meth:`numpy.class.__array_function__` for more information.
This flag is checked at import time.
-Debugging
-=========
+Debugging-Related Options
+=========================
Relaxed Strides Checking
------------------------
@@ -82,4 +82,4 @@ debug option can be interesting for testing code written
in C which iterates through arrays that may or may not be
contiguous in memory.
Most users will have no reason to change these, for details
-please see the :ref:`memory layout <memory-layout>`_ documentation.
+please see the `memory layout <memory-layout>`_ documentation.