Coverart for item
The Resource Introduction to HPC with MPI for data science, Frank Nielsen, (electronic book)

Introduction to HPC with MPI for data science, Frank Nielsen, (electronic book)

Label
Introduction to HPC with MPI for data science
Title
Introduction to HPC with MPI for data science
Statement of responsibility
Frank Nielsen
Creator
Author
Subject
Language
eng
Summary
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 parts the first part covers high performance computing using C++ with the Message Passing Interface (MPI) standard followed by a second part providing high-performance data analytics on computer clusters. In the first part, the fundamental notions of blocking versus non-blocking point-to-point communications, global communications (like broadcast or scatter) and collaborative computations (reduce), with Amdalh and Gustafson speed-up laws are described before addressing parallel sorting and parallel linear algebra on computer clusters. The common ring, torus and hypercube topologies of clusters are then explained and global communication procedures on these topologies are studied. This first part closes with the MapReduce (MR) model of computation well-suited to processing big data using the MPI framework. In the second part, the book focuses on high-performance data analytics. Flat and hierarchical clustering algorithms are introduced for data exploration along with how to program these algorithms on computer clusters, followed by machine learning classification, and an introduction to graph analytics. This part closes with a concise introduction to data core-sets that let big data problems be amenable to tiny data problems. Exercises are included at the end of each chapter in order for students to practice the concepts learned, and a final section contains an overall exam which allows them to evaluate how well they have assimilated the material covered in the book
Member of
Cataloging source
GW5XE
http://library.link/vocab/creatorName
Nielsen, Frank
Dewey number
004.1/1
Illustrations
illustrations
Index
index present
LC call number
QA76.88
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Undergraduate topics in computer science,
http://library.link/vocab/subjectName
High performance computing
Label
Introduction to HPC with MPI for data science, Frank Nielsen, (electronic book)
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
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
Control code
SPR939528764
Dimensions
unknown
Extent
1 online resource (xxxiii, 282 pages)
File format
unknown
Form of item
online
Isbn
9783319219035
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-21903-5
Other physical details
color illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
Label
Introduction to HPC with MPI for data science, Frank Nielsen, (electronic book)
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
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
Control code
SPR939528764
Dimensions
unknown
Extent
1 online resource (xxxiii, 282 pages)
File format
unknown
Form of item
online
Isbn
9783319219035
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-21903-5
Other physical details
color illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote

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