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Introduction to HPC with MPI for Data Science

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Cover of 'Introduction to HPC with MPI for Data Science'

Table of Contents

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    Book Overview
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    Chapter 1 A Glance at High Performance Computing (HPC)
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    Chapter 2 Introduction to MPI: The Message Passing Interface
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    Chapter 3 Topology of Interconnection Networks
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    Chapter 4 Parallel Sorting
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    Chapter 5 Parallel Linear Algebra
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    Chapter 6 The MapReduce Paradigm
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    Chapter 7 Partition-Based Clustering with k -Means
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    Chapter 8 Hierarchical Clustering
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    Chapter 9 Supervised Learning: Practice and Theory of Classification with the k -NN Rule
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    Chapter 10 Fast Approximate Optimization in High Dimensions with Core-Sets and Fast Dimension Reduction
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    Chapter 11 Parallel Algorithms for Graphs
Attention for Chapter 9: Supervised Learning: Practice and Theory of Classification with the k -NN Rule
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