Introduction to HPC with MPI for Data Science

• Κύριος συγγραφέας: Nielsen, Frank (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Έκδοση: 1st ed. 2016.
• Σειρά: Undergraduate Topics in Computer Science,
• Θέματα: Computer science.; Computer programming.; Computer Science.; Programming Techniques.

This gentle introduction to High Performance Computing (HPC) for Data Science using the Message Passing Interface (MPI) standard has been designed as a first course for undergraduates on parallel programming on distributed memory models, and requires only basic programming notions. Divided into two...

Πίνακας περιεχομένων:

• Preface
• Part 1: High Performance Computing (HPC) with the Message Passing Interface (MPI)
• A Glance at High Performance Computing (HPC)
• Introduction to MPI: The Message Passing Interface
• Topology of Interconnection Networks
• Parallel Sorting
• Parallel Linear Algebra.-The MapReduce Paradigm
• Part 11: High Performance Computing for Data Science
• Partition-based Clustering with k means
• Hierarchical Clustering
• Supervised Learning: Practice and Theory of Classification with k NN rule
• Fast Approximate Optimization to High Dimensions with Core-sets and Fast Dimension Reduction
• Parallel Algorithms for Graphs
• Appendix A: Written Exam
• Appendix B: SLURM: A resource manager and job scheduler on clusters of machines
• Appendix C: List of Figures
• Appendix D: List of Tables
• Appendix E: Index.