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"Ask not what your compiler can do for you, ask what you can do for
your compiler." --John Levesque, Director of Cray's Supercomputing
Centers of Excellence The next decade of computationally intense
computing lies with more powerful multi/manycore nodes where
processors share a large memory space. These nodes will be the
building block for systems that range from a single node
workstation up to systems approaching the exaflop regime. The node
itself will consist of 10's to 100's of MIMD (multiple instruction,
multiple data) processing units with SIMD (single instruction,
multiple data) parallel instructions. Since a standard, affordable
memory architecture will not be able to supply the bandwidth
required by these cores, new memory organizations will be
introduced. These new node architectures will represent a
significant challenge to application developers. Programming for
Hybrid Multi/Manycore MPP Systems attempts to briefly describe the
current state-of-the-art in programming these systems, and proposes
an approach for developing a performance-portable application that
can effectively utilize all of these systems from a single
application. The book starts with a strategy for optimizing an
application for multi/manycore architectures. It then looks at the
three typical architectures, covering their advantages and
disadvantages. The next section of the book explores the other
important component of the target-the compiler. The compiler will
ultimately convert the input language to executable code on the
target, and the book explores how to make the compiler do what we
want. The book then talks about gathering runtime statistics from
running the application on the important problem sets previously
discussed. How best to utilize available memory bandwidth and
virtualization is covered next, along with hybridization of a
program. The last part of the book includes several major
applications, and examines future hardware advancements and how the
application developer may prepare for those advancements.
High Performance Computing: Programming and Applications presents
techniques that address new performance issues in the programming
of high performance computing (HPC) applications. Omitting tedious
details, the book discusses hardware architecture concepts and
programming techniques that are the most pertinent to application
developers for achieving high performance. Even though the text
concentrates on C and Fortran, the techniques described can be
applied to other languages, such as C++ and Java. Drawing on their
experience with chips from AMD and systems, interconnects, and
software from Cray Inc., the authors explore the problems that
create bottlenecks in attaining good performance. They cover
techniques that pertain to each of the three levels of parallelism:
1. Message passing between the nodes 2. Shared memory parallelism
on the nodes or the multiple instruction, multiple data (MIMD)
units on the accelerator 3. Vectorization on the inner level After
discussing architectural and software challenges, the book outlines
a strategy for porting and optimizing an existing application to a
large massively parallel processor (MPP) system. With a look toward
the future, it also introduces the use of general purpose graphics
processing units (GPGPUs) for carrying out HPC computations. A
companion website at www.hybridmulticoreoptimization.com contains
all the examples from the book, along with updated timing results
on the latest released processors.
High Performance Computing: Programming and Applications presents
techniques that address new performance issues in the programming
of high performance computing (HPC) applications. Omitting tedious
details, the book discusses hardware architecture concepts and
programming techniques that are the most pertinent to application
developers for achieving high performance. Even though the text
concentrates on C and Fortran, the techniques described can be
applied to other languages, such as C++ and Java. Drawing on their
experience with chips from AMD and systems, interconnects, and
software from Cray Inc., the authors explore the problems that
create bottlenecks in attaining good performance. They cover
techniques that pertain to each of the three levels of parallelism:
Message passing between the nodes Shared memory parallelism on the
nodes or the multiple instruction, multiple data (MIMD) units on
the accelerator Vectorization on the inner level After discussing
architectural and software challenges, the book outlines a strategy
for porting and optimizing an existing application to a large
massively parallel processor (MPP) system. With a look toward the
future, it also introduces the use of general purpose graphics
processing units (GPGPUs) for carrying out HPC computations. A
companion website at www.hybridmulticoreoptimization.com contains
all the examples from the book, along with updated timing results
on the latest released processors.
This scarce antiquarian book is a selection from Kessinger
Publishing's Legacy Reprint Series. Due to its age, it may contain
imperfections such as marks, notations, marginalia and flawed
pages. Because we believe this work is culturally important, we
have made it available as part of our commitment to protecting,
preserving, and promoting the world's literature. Kessinger
Publishing is the place to find hundreds of thousands of rare and
hard-to-find books with something of interest for everyone
This scarce antiquarian book is a selection from Kessinger
Publishing's Legacy Reprint Series. Due to its age, it may contain
imperfections such as marks, notations, marginalia and flawed
pages. Because we believe this work is culturally important, we
have made it available as part of our commitment to protecting,
preserving, and promoting the world's literature. Kessinger
Publishing is the place to find hundreds of thousands of rare and
hard-to-find books with something of interest for everyone!
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