Introduction to HPC with MPI for Data Science [E-Book] / by Frank Nielsen.
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...
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Personal Name(s): | Nielsen, Frank, author |
Edition: |
1st ed. 2016. |
Imprint: |
Cham :
Springer International Publishing,
2016
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Physical Description: |
XXXIII, 282 p. 101 illus. in color. online resource. |
Note: |
englisch |
ISBN: |
9783319219035 |
DOI: |
10.1007/978-3-319-21903-5 |
Series Title: |
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Undergraduate Topics in Computer Science
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- 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.