Introduction to HPC with MPI for data science. (2016)

• Record Type: Book
• Further Information: Note: Frank Nielsen.
• Authors: Nielsen, Frank
• 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.
• Publisher Details: Cham : Springer
• Publication Date: 2016
• Extent: 1 online resource (xxxiii, 282 pages), color illustrations
• Subjects: 004.1/1; Computer science; High performance computing; High performance computing; Computer Science; Programming Techniques; Computer Science; Engineering & Applied Sciences; Computers -- Programming -- General; Computer programming / software development; Electronic books
• Languages: English
• ISBNs: 9783319219035; 3319219030; 3319219022; 9783319219028
• Related ISBNs: 9783319219028
• Notes: Note: Includes bibliographical references and index.; Note: Online resource; title from PDF title page (SpringerLink, viewed February 15, 2016).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.