High Performance Computing

Regular price €117.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Gene Wagenbreth
A01=John Levesque
application porting for supercomputers
Array Syntax
Author_Gene Wagenbreth
Author_John Levesque
Cache Line
Category=UKC
Clo Ck
Clock Cycle
communication bottlenecks
compilers
Computational Intensity
computer hardware
DDR2
distributed memory systems
ENDDO ENDDO
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
general purpose graphics processing unit
GPGPU
Hardware Counter
high performance computing
HPC
Larger Processor Counts
Load Imbalance
massively parallel processor
Memory Bandwidth
message passing interface
MIMD
MPI
MPI Application
MPI Program
MPI Task
MPP
multicore architectures
Multicore Node
Multicore Socket
multiple data units
multiple instruction
Nth Column
Oating Point Operation
OMP
OpenMP Region
parallel algorithm optimisation
parallel programming
performance tuning techniques
Prefetch Instructions
Processor Counts
scientific computing
shared memory parallelism
thread-level parallelism
Vector Length
vector processor programming
vectorization
Weak Scaling

Product details

  • ISBN 9781420077056
  • Weight: 620g
  • Dimensions: 156 x 234mm
  • Publication Date: 14 Dec 2010
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

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.

John Levesque works in the Chief Technology Office at Cray Inc., where he is responsible for application performance on Cray’s HPC systems. He is also director of Cray’s Supercomputing Center of Excellence at the Oak Ridge National Laboratory (ORNL). ORNL was the first site to install a Petaflop Cray XT5 system, Jaguar; as of June 2010, it is the fastest computer in the world according to the TOP500 list.
For the past 40 years, Mr. Levesque has optimized scientific application programs for successful HPC systems. He is an expert in application tuning and compiler analysis of scientific applications.

Gene Wagenbreth is a senior system programmer in the Information Sciences Institute at the University of Southern California, where he is applying GPGPU technology in sparse matrix solvers, image tomography, and real-time computational fluid dynamics. He also presents courses on the use and programming of GPUs.
Since the 1970s, Mr. Wagenbreth has worked with most of the highest performance computers, including Cray models, other vector processors, hypercubes, and clusters. He has worked with shared and distributed memory computers using MPI, OpenMP, pthreads, and other techniques. He has also applied parallel processing in numerous fields, including seismic analysis, reservoir simulation, weather forecasting, and battlefield simulations.

More from this author