Authors: Jakub Kurzak, David A. Bader, Jack Dongarra
The hybrid/heterogeneous nature of future microprocessors and large high-
performance computing systems will result in a reliance on two major types of
components: multicore/manycore central processing units and special purpose
hardware/massively parallel accelerators. While these technologies have
numerous benefits, they also pose substantial performance challenges for
developers, including scalability, software tuning, and programming issues.
Researchers at the Forefront Reveal Results from Their Own State-of-the-Art Work
Edited by some of the top researchers in the field and with contributions from
a variety of international experts, Scientific Computing with Multicore and
Accelerators focuses on the architectural design and implementation of multicore
and manycore processors and accelerators, including graphics processing units
(GPUs) and the Sony Toshiba IBM (STI) Cell Broadband Engine (BE) currently used
in the Sony PlayStation 3. The book explains how numerical libraries, such
as LAPACK, help solve computational science problems; explores the emerging
area of hardware-oriented numerics; and presents the design of a fast Fourier
transform (FFT) and a parallel list ranking algorithm for the Cell BE. It covers
stencil computations, auto-tuning, optimizations of a computational kernel,
sequence alignment and homology, and pairwise computations. The book also
evaluates the portability of drug design applications to the Cell BE and
illustrates how to successfully exploit the computational capabilities of GPUs
for scientific applications. It concludes with chapters on dataflow frameworks,
the Charm++ programming model, scan algorithms, and a portable intracore
communication framework.
Explores the New Computational Landscape of Hybrid Processors
By offering insight into the process of constructing and effectively using
the technology, this volume provides a thorough and practical introduction
to the area of hybrid computing. It discusses introductory concepts and simple
examples of parallel computing, logical and performance debugging for parallel
computing, and advanced topics and issues related to the use and building of
many applications.
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