Introduction to High Performance Computing for Scientists and Engineers  book cover
1st Edition

Introduction to High Performance Computing for Scientists and Engineers

ISBN 9781439811924
Published July 2, 2010 by CRC Press
356 Pages 143 B/W Illustrations

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Book Description

Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the authors gained a unique perspective on the requirements and attitudes of users as well as manufacturers of parallel computers.

The text first introduces the architecture of modern cache-based microprocessors and discusses their inherent performance limitations, before describing general optimization strategies for serial code on cache-based architectures. It next covers shared- and distributed-memory parallel computer architectures and the most relevant network topologies. After discussing parallel computing on a theoretical level, the authors show how to avoid or ameliorate typical performance problems connected with OpenMP. They then present cache-coherent nonuniform memory access (ccNUMA) optimization techniques, examine distributed-memory parallel programming with message passing interface (MPI), and explain how to write efficient MPI code. The final chapter focuses on hybrid programming with MPI and OpenMP.

Users of high performance computers often have no idea what factors limit time to solution and whether it makes sense to think about optimization at all. This book facilitates an intuitive understanding of performance limitations without relying on heavy computer science knowledge. It also prepares readers for studying more advanced literature.

Read about the authors’ recent honor: Informatics Europe Curriculum Best Practices Award for Parallelism and Concurrency

Table of Contents

Modern Processors
Stored-program computer architecture
General-purpose cache-based microprocessor architecture
Memory hierarchies
Multicore processors
Multithreaded processors
Vector processors

Basic Optimization Techniques for Serial Code
Scalar profiling
Common sense optimizations
Simple measures, large impact
The role of compilers
C++ optimizations

Data Access Optimization
Balance analysis and lightspeed estimates
Storage order
Case study: The Jacobi algorithm
Case study: Dense matrix transpose
Algorithm classification and access optimizations
Case study: Sparse matrix-vector multiply

Parallel Computers
Taxonomy of parallel computing paradigms
Shared-memory computers
Distributed-memory computers
Hierarchical (hybrid) systems

Basics of Parallelization
Why parallelize?
Parallel scalability

Shared-Memory Parallel Programming with OpenMP
Short introduction to OpenMP
Case study: OpenMP-parallel Jacobi algorithm
Advanced OpenMP: Wavefront parallelization

Efficient OpenMP Programming
Profiling OpenMP programs
Performance pitfalls
Case study: Parallel sparse matrix-vector multiply

Locality Optimizations on ccNUMA Architectures
Locality of access on ccNUMA
Case study: ccNUMA optimization of sparse MVM
Placement pitfalls
ccNUMA issues with C++

Distributed-Memory Parallel Programming with MPI
Message passing
A short introduction to MPI
Example: MPI parallelization of a Jacobi solver

Efficient MPI Programming
MPI performance tools
Communication parameters
Synchronization, serialization, contention
Reducing communication overhead
Understanding intranode point-to-point communication

Hybrid Parallelization with MPI and OpenMP
Basic MPI/OpenMP programming models
MPI taxonomy of thread interoperability
Hybrid decomposition and mapping
Potential benefits and drawbacks of hybrid programming

Appendix A: Topology and Affinity in Multicore Environments
Appendix B: Solutions to the Problems



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Georg Hager is a senior research scientist in the high performance computing group of the Erlangen Regional Computing Center at the University of Erlangen-Nuremberg in Germany.

Gerhard Wellein leads the high performance computing group of the Erlangen Regional Computing Center and is a professor in the Department for Computer Science at the University of Erlangen-Nuremberg in Germany.


Georg Hager and Gerhard Wellein have developed a very approachable introduction to high performance computing for scientists and engineers. Their style and description is easy to read and follow. … This book presents a balanced treatment of the theory, technology, architecture, and software for modern high performance computers and the use of high performance computing systems. The focus on scientific and engineering problems makes this both educational and unique. I highly recommend this timely book for scientists and engineers. I believe this book will benefit many readers and provide a fine reference.
—From the Foreword by Jack Dongarra, University of Tennessee, Knoxville, USA