Multicore Computing

Regular price €217.00
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
access
Age Group_Uncategorized
Age Group_Uncategorized
Aho-Corasick algorithm
algorithms for the IBM Cell Broadband Engine
architecture and programming model of the NVIDIA Tesla GPU
automatic-update
B01=Lance Fiondella
B01=Mohamed Ahmed
B01=Reda A. Ammar
B01=Sanguthevar Rajasekaran
backprojection algorithm
block
cache
Cache Line
cache optimisation
Cache Sets
Category1=Non-Fiction
Category=UK
Category=UKC
Category=UM
Category=UMB
Category=UMX
Category=UMZ
Category=UYF
challenges in parallel computing
Cilk++ programming
COP=United States
Data Sets
Delivery_Pre-order
design efficient multicore algorithms
design trade-offs among multicore processors
Device Memory Accesses
directed acyclic graphs
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Execution Time
global
Global Memory
GPU Implementation
GPU Kernel
hierarchy
high performance computing
IBM Power5
L2 Cache
Language_English
line
Load Instruction
memory
Memory Transaction
Merge Sort
multi-core
multicore and manycore processors
Multicore Processor
numerical linear algebra
numerical software library
NVIDIA CUDA
PA=Temporarily unavailable
Pacific Northwest National Laboratory
parallel algorithms
parallel string matching techniques
Prefix Sum
Price_€100 and above
processor
programming multicore machines
Proposed Scheduling Method
PS=Active
Quick Sort
Radix Sort
Read Miss
Runtime System
softlaunch
solving big data problems
SPARC architecture
Stack Frames
synthetic aperture radar imaging
Tesla C1060
thread
Thread Block

Product details

  • ISBN 9781439854341
  • Weight: 771g
  • Dimensions: 156 x 234mm
  • Publication Date: 12 Dec 2013
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
Secure checkout Fast Shipping Easy returns

Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the advent of multicore architectures. However, programming multicore machines is much more difficult due to oddities existing in the architectures.

Offering insights into different facets of this area, Multicore Computing: Algorithms, Architectures, and Applications focuses on the architectures, algorithms, and applications of multicore computing. It will help readers understand the intricacies of these architectures and prepare them to design efficient multicore algorithms.

Contributors at the forefront of the field cover the memory hierarchy for multicore and manycore processors, the caching strategy Flexible Set Balancing, the main features of the latest SPARC architecture specification, the Cilk and Cilk++ programming languages, the numerical software library Parallel Linear Algebra Software for Multicore Architectures (PLASMA), and the exact multipattern string matching algorithm of Aho-Corasick. They also describe the architecture and programming model of the NVIDIA Tesla GPU, discuss scheduling directed acyclic graphs onto multi/manycore processors, and evaluate design trade-offs among Intel and AMD multicore processors, IBM Cell Broadband Engine, and NVIDIA GPUs. In addition, the book explains how to design algorithms for the Cell Broadband Engine and how to use the backprojection algorithm for generating images from synthetic aperture radar data.

Sanguthevar Rajasekaran is the UTC Chair Professor of Computer Science and Engineering and director of the Booth Engineering Center for Advanced Technologies at the University of Connecticut. He received a Ph.D. in computer science from Harvard University. He is a fellow of the IEEE and the AAAS and an elected member of the Connecticut Academy of Science and Engineering. His research interests include bioinformatics, parallel algorithms, data mining, randomized computing, computer simulations, and combinatorial optimization.

Lance Fiondella is an assistant professor in the Department of Electrical and Computer Engineering at the University of Massachusetts Dartmouth. He received a Ph.D. in computer science and engineering from the University of Connecticut. His research interests include algorithms, reliability engineering, and risk analysis.

Mohamed Ahmed is a program manager at Microsoft Windows Azure Mobile. He received a PhD in computer science and engineering from the University of Connecticut. His research interests include multi/many-cores technologies, high-performance computing, parallel programming, cloud computing, and GPU programming.

Reda A. Ammar is a professor and the head of the Department of Computer Science and Engineering at the University of Connecticut. He received a PhD in computer science from the University of Connecticut. He is the president of the International Society of Computers and Their Applications and editor-in-chief of the International Journal on Computers and Their Applications. His primary research interests encompass distributed and high-performance computing and real-time systems.