Inhaltsangabe
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.
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