Multicore computing: algorithms architectures and applications Sanguthevar Rajasekaran & et al eds.

Includes Index

Memory hierarchy for multicore and many-core processors -- FSB: A flexible set-balancing strategy for last-level caches -- The SPARC processor architecture -- The cilk and cilk ++ programming languages -- Multihreading in the PLASMA library -- Efficient Aho-corasick string matching on emerging multicore architectures -- Sorting on a graphics processing unit (GPU) -- Scheduling DAG-structured computations -- Evaluating multicore processors and acceelerators for dense numerical computations -- Sorting on the cell broadband engine -- GPU matrix multiplication -- Backprojection algorithms for multicore and GPU architectures

This book 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.