Elements of Parallel Computing
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€248.00
A01=Eric Aubanel
Address Space
algorithm
Author_Eric Aubanel
Bellman Ford Algorithm
Boundary Vertices
Cache Block
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Category=PBC
Category=UB
Category=UKC
Category=UKG
Category=UMB
Cellular Automata
Convex Hull
Eikonal Equation
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Execution Time
FMM
Ghost Elements
Graham Scan
graph
Load Balance
matrix
Matrix Vector Multiplication
memory
merge
Merge Sort
multiplication
Parallel Algorithm Design
Parallel Computing
Parallel Decomposition
Parallel Loop
Parallel Programs
Planar Convex Hull
Prefix Sum
Sequential Algorithms
shared
Single Source Shortest Path
sort
SPMD Programming
task
Task Graph
vector
Product details
- ISBN 9781138470873
- Weight: 453g
- Dimensions: 178 x 254mm
- Publication Date: 28 Sep 2017
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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Created to help scientists and engineers write computer code, this practical book addresses the important tools and techniques that are necessary for scientific computing, but which are not yet commonplace in science and engineering curricula. This book contains chapters summarizing the most important topics that computational researchers need to know about. It leverages the viewpoints of passionate experts involved with scientific computing courses around the globe and aims to be a starting point for new computational scientists and a reference for the experienced. Each contributed chapter focuses on a specific tool or skill, providing the content needed to provide a working knowledge of the topic in about one day. While many individual books on specific computing topics exist, none is explicitly focused on getting technical professionals and students up and running immediately across a variety of computational areas.
Eric Aubanel is a Professor in the Faculty of Computer Science at the University of New Brunswick, Fredericton , C anada. His area of research is High Performance Computing. He is part of the IBM Center for Advanced Studies - Atlantic and associated with the Atlantic Computational Excellence Network (ACEnet). His research is funded by NSERC.
