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URL: http://github.com/ipython/ipython/commit/c2ef334fed4b9315cf526a15786353bd62bf8901

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clarify TaskScheduler.hwm doc · ipython/ipython@c2ef334 · GitHub
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clarify TaskScheduler.hwm doc
changes version inequality to 0.13, where the change happened, and clarifies that the code block is an example for a config file
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docs/source/parallel/parallel_task.txt

Lines changed: 8 additions & 7 deletions
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@@ -386,30 +386,31 @@ weighted: Weighted Two-Bin Random
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Greedy Assignment
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-----------------
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Tasks are assigned greedily as they are submitted. If their dependencies are
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Tasks can be assigned greedily as they are submitted. If their dependencies are
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met, they will be assigned to an engine right away, and multiple tasks can be
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assigned to an engine at a given time. This limit is set with the
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``TaskScheduler.hwm`` (high water mark) configurable:
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``TaskScheduler.hwm`` (high water mark) configurable in your
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:file:`ipcontroller_config.py` config file, with:
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.. sourcecode:: python
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# the most common choices are:
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c.TaskSheduler.hwm = 0 # (minimal latency, default in IPython 0.12)
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c.TaskSheduler.hwm = 0 # (minimal latency, default in IPython < 0.13)
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# or
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c.TaskScheduler.hwm = 1 # (most-informed balancing, default in > 0.12)
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c.TaskScheduler.hwm = 1 # (most-informed balancing, default in 0.13)
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In IPython 0.12,the default is 0, or no-limit. That is, there is no limit to the number of
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In IPython < 0.13, the default is 0, or no-limit. That is, there is no limit to the number of
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tasks that can be outstanding on a given engine. This greatly benefits the
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latency of execution, because network traffic can be hidden behind computation.
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However, this means that workload is assigned without knowledge of how long
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each task might take, and can result in poor load-balancing, particularly for
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submitting a collection of heterogeneous tasks all at once. You can limit this
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effect by setting hwm to a positive integer, 1 being maximum load-balancing (a
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task will never be waiting if there is an idle engine), and any larger number
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being a compromise between load-balance and latency-hiding.
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being a compromise between load-balancing and latency-hiding.
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In practice, some users have been confused by having this optimization on by
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default, and the default value has been changed to 1. This can be slower,
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default, so the default value has been changed to 1 in IPython 0.13. This can be slower,
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but has more obvious behavior and won't result in assigning too many tasks to
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some engines in heterogeneous cases.
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