MPI4PY, NumPy, and SciPy for Enthusiasts
Buch, Englisch, 171 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 3051 g
ISBN: 978-1-4842-2877-7
Verlag: Apress
Once the cluster is built, its power has to be exploited by means of programs to run on it. So, Raspberry Pi Supercomputing and Scientific Programming teaches you to code the cluster with the MPI4PY library of Python 3. Along the way, you will learn the concepts of the Message Passing Interface (MPI) standards and will explore the fundamentals of parallel programming on your inexpensive cluster. This will make this book a great starting point for supercomputing enthusiasts who want to get started with parallel programming.
The book finishes with details of symbolic mathematics and scientific and numerical programming in Python, using SymPi, SciPy, NumPy, and Matplotlib. You’ll see how to process signals and images, carry out calculations using linear algebra, and visualize your results, all using Python code. With the power of a Raspberry Pi supercomputer at your fingertips, data-intensive scientific programming becomes a reality at home.
What You Will Learn
- Discover the essentials of supercomputing
- Build a low-cost cluster of Raspberry Pis at home
- Harness the power of parallel programming and the Message Passing Interface (MPI)
- Use your Raspberry Pi for symbolic, numerical, and scientific programming
Who This Book Is For
Python 3 developers who seek the knowledge of parallel programming, Raspberry Pi enthusiasts, researchers, and the scientific Python community.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Chapter 1: Introduction to Single Board Computers and Raspberry Pi.- Chapter 2: Important Linux Commands and Remote Connectivity.- Chapter 3: Introduction to Python.- Chapter 4: Introduction to Supercomputers.- Chapter 5: Message Passing Interface.- Chapter 6: Building the Supercomputer.- Chapter 7: Overclocking Raspberry Pi.- Chapter 8: Parallel Programming in Python 3.- Chapter 9: Introduction to SciPy Stack and Symbolic Programming.- Chapter 10: Introduction to NumPy.- Chapter 11: Introduction to SciPy.- Chapter 12: Signal Processing with SciPy.- Chapter 13: Image processing with SciPy.- Chapter 14: Matplotlib.