| 书目名称 | Introduction to HPC with MPI for Data Science |
| 编辑 | Frank Nielsen |
| 视频video | |
| 概述 | Contains numerous exercises and a test exam.Features material that has been used and tested with students.Provides additional material, including source C++/MPI codes and slides for each chapter, on a |
| 丛书名称 | Undergraduate Topics in Computer Science |
| 图书封面 |  |
| 描述 | .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 |
| 出版日期 | Textbook 2016 |
| 关键词 | Data Science; Exploratory analytics and knowledge discovery; High Performance Computing (HPC); Large-sc |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-21903-5 |
| isbn_softcover | 978-3-319-21902-8 |
| isbn_ebook | 978-3-319-21903-5Series ISSN 1863-7310 Series E-ISSN 2197-1781 |
| issn_series | 1863-7310 |
| copyright | Springer International Publishing Switzerland 2016 |
发表于 2025-3-21 16:24:26
