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Scientific Computing with Python

You're reading from   Scientific Computing with Python High-performance scientific computing with NumPy, SciPy, and pandas

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Length 392 pages
Edition 2nd Edition
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Authors (4):
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Olivier Verdier Olivier Verdier
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Olivier Verdier
Jan Erik Solem Jan Erik Solem
Author Profile Icon Jan Erik Solem
Jan Erik Solem
Claus Führer Claus Führer
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Claus Führer
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
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Table of Contents (23) Chapters Close

Preface 1. Getting Started 2. Variables and Basic Types FREE CHAPTER 3. Container Types 4. Linear Algebra - Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Series and Dataframes - Working with Pandas 11. Communication by a Graphical User Interface 12. Error and Exception Handling 13. Namespaces, Scopes, and Modules 14. Input and Output 15. Testing 16. Symbolic Computations - SymPy 17. Interacting with the Operating System 18. Python for Parallel Computing 19. Comprehensive Examples 20. About Packt 21. Other Books You May Enjoy 22. References

18.4 Summary

In this chapter, we saw how to execute copies of the same script on different processors in parallel. Message passing allows the communication between these different processes. We saw point-to-point communication and the two different distribution type collective communications one-to-all and all-to-one. The commands presented in this chapter are provided by the Python module mpi4py, which is a Python wrapper to realize the MPI standard in C.

Having worked through this chapter, you are now able to work on your own scripts for parallel programming and you will find that we described only the most essential commands and concepts here. Grouping processes and tagging information are only two of those concepts that we left out. Many of these concepts are important for special and challenging applications, which are far too particular for this introduction.

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