Read e-book online Introduction to HPC with MPI for Data Science PDF

By Frank Nielsen

ISBN-10: 3319219022

ISBN-13: 9783319219028

ISBN-10: 3319219030

ISBN-13: 9783319219035

This light creation to excessive functionality Computing (HPC) for facts technological know-how utilizing the Message Passing Interface (MPI) general has been designed as a primary direction for undergraduates on parallel programming on dispensed reminiscence versions, and calls for simply uncomplicated programming notions.

Divided into components the 1st half covers excessive functionality computing utilizing C++ with the Message Passing Interface (MPI) general via a moment half offering high-performance information analytics on desktop clusters.

In the 1st half, the elemental notions of blocking off as opposed to non-blocking point-to-point communications, worldwide communications (like broadcast or scatter) and collaborative computations (reduce), with Amdalh and Gustafson speed-up legislation are defined prior to addressing parallel sorting and parallel linear algebra on desktop clusters. the typical ring, torus and hypercube topologies of clusters are then defined and worldwide conversation methods on those topologies are studied. this primary half closes with the MapReduce (MR) version of computation well-suited to processing huge facts utilizing the MPI framework.

In the second one half, the e-book specializes in high-performance information analytics. Flat and hierarchical clustering algorithms are brought for information exploration in addition to how one can application those algorithms on laptop clusters, by means of computing device studying type, and an creation to graph analytics. This half closes with a concise creation to facts core-sets that permit colossal facts difficulties be amenable to tiny information problems.

Exercises are incorporated on the finish of every bankruptcy to ensure that scholars to perform the techniques discovered, and a last part includes an total examination which permits them to judge how good they've got assimilated the cloth coated within the book.

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Extra info for Introduction to HPC with MPI for Data Science

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25 ..... 29 ..... 32 ..... 70 ..... 1 What is High Performance Computing (HPC)? High Performance Computing, or HPC for short, is an area encompassing among others the various paradigms of parallel programming, their related programming languages and application programming interfaces (APIs), the dedicated software tools, the international specialized conferences (ACM/IEEE Super-Computing, or SC for short), etc. Loosely speaking, HPC is both the scientific and technical fields of study of “Super-Computers” (SCs).

The chosen topology for the interconnection network affects the efficiency of communications, but also implies a corresponding hardware cost. 1 displays common topologies for the interconnection network. We distinguish between the bus interconnection and the complete graph interconnection network. Messages can be exchanged point-to-point (for example, using the bus of the complete graph) or by being routed using intermediate nodes. 2 depicts schematically the evolution of computer architectures over the last decades: as manufacturing processes like lithography have improved 6 See the -O option argument of g++.

Thus super-linear speedups can be observed for large data sets, simply by allowing all data to be stored in the local memory (RAM) of the processors. 3 Gustafson’s Law: Scaled Speedup, Increasing Data Size with Resources Gustafson’s law [2] characterizes the impact of data parallelism, challenging Amdahl’s law by offering a novel viewpoint. In this setting, we no longer assume that the data size is constant, but rather that it depends on the number of processors P (the available resources). 7 Speedup 15 time, due to the intrinsic serial code).

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Introduction to HPC with MPI for Data Science by Frank Nielsen


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