By Frank Nielsen
This mild creation to excessive functionality Computing (HPC) for Data
technological know-how utilizing the Message Passing Interface (MPI) ordinary has been
designed as a primary direction for undergraduates on parallel programming on
disbursed reminiscence types, and calls for merely easy programming notions.
into elements the 1st half covers excessive functionality computing utilizing
C++ with the Message Passing Interface (MPI) average by way of a
second half supplying high-performance information analytics on desktop
In the 1st half, the elemental notions of blockading
versus 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 sooner than addressing
parallel sorting and parallel linear algebra on laptop clusters. The
common ring, torus and hypercube topologies of clusters are then
explained and international verbal exchange tactics 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.
the second one half, the ebook makes a speciality of high-performance info analytics.
Flat and hierarchical clustering algorithms are brought for facts
exploration in addition to easy methods to software those algorithms on desktop
clusters, by way of computing device studying class, and an
introduction to graph analytics. This half closes with a concise
introduction to info core-sets that permit substantial info difficulties be amenable to
tiny information problems.
Exercises are incorporated on the finish of every
chapter to ensure that scholars to perform the techniques discovered, and a
final part includes an total examination which permits them to judge how
good they've got assimilated the cloth coated within the book.
Read or Download Introduction to HPC with MPI for Data Science (Undergraduate Topics in Computer Science) PDF
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