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@@ -28,7 +28,7 b' With these components, it is possible to perform all aspects of a parallel' | |||
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28 | 28 | computation interactively. This type of workflow is particularly relevant in |
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29 | 29 | scientific and numerical computing where algorithms, code and data are |
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30 | 30 | continually evolving as the user/developer explores a problem. The broad |
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31 | treads in computing (commodity clusters, multicore, cloud computing, etc.) | |
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31 | threads in computing (commodity clusters, multicore, cloud computing, etc.) | |
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32 | 32 | make these capabilities of IPython particularly relevant. |
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33 | 33 | |
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34 | 34 | While IPython is a cross platform tool, it has particularly strong support for |
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