The state of the art of high-performance computing

Prominent researchers from around the world have gathered to
present the state-of-the-art techniques and innovations in
high-performance computing (HPC), including:

* Programming models for parallel computing: graph-oriented
programming (GOP), OpenMP, the stages and transformation (SAT)
approach, the bulk-synchronous parallel (BSP) model, Message
Passing Interface (MPI), and Cilk

* Architectural and system support, featuring the code tiling
compiler technique, the MigThread application-level migration and
checkpointing package, the new prefetching scheme of atomicity, a
new "receiver makes right" data conversion method, and lessons
learned from applying reconfigurable computing to HPC

* Scheduling and resource management issues with heterogeneous
systems, bus saturation effects on SMPs, genetic algorithms for
distributed computing, and novel task-scheduling algorithms

* Clusters and grid computing: design requirements, grid
middleware, distributed virtual machines, data grid services and
performance-boosting techniques, security issues, and open
issues

* Peer-to-peer computing (P2P) including the proposed search
mechanism of hybrid periodical flooding (HPF) and routing protocols
for improved routing performance

* Wireless and mobile computing, featuring discussions of
implementing the Gateway Location Register (GLR) concept in 3G
cellular networks, maximizing network longevity, and comparisons of
QoS-aware scatternet scheduling algorithms

* High-performance applications including partitioners, running
Bag-of-Tasks applications on grids, using low-cost clusters to meet
high-demand applications, and advanced convergent architectures and
protocols

High-Performance Computing: Paradigm and Infrastructure is an
invaluable compendium for engineers, IT professionals, and
researchers and students of computer science and applied
mathematics.

MINYI GUO received his PhD from the University of Tsukuba, Japan. He is currently an Associate Professor in the Department of Computer Software at the University of Aizu, Japan. In addition, Dr. Guo is Editor in Chief of the International Journal of Embedded Systems, and has written and edited books in the area of parallel and distributed computing, as well as embedded and ubiquitous computing.

Prominent researchers from around the world have gathered to present the state-of-the-art techniques and innovations in high-performance computing (HPC), including:

• Programming models for parallel computing: graph-oriented programming (GOP), OpenMP, the stages and transformation (SAT) approach, the bulk-synchronous parallel (BSP) model, Message Passing Interface (MPI), and Cilk
• Architectural and system support, featuring the code tiling compiler technique, the MigThread application-level migration and checkpointing package, the new prefetching scheme of atomicity, a new "receiver makes right" data conversion method, and lessons learned from applying reconfigurable computing to HPC
• Scheduling and resource management issues with heterogeneous systems, bus saturation effects on SMPs, genetic algorithms for distributed computing, and novel task-scheduling algorithms
• Clusters and grid computing: design requirements, grid middleware, distributed virtual machines, data grid services and performance-boosting techniques, security issues, and open issues
• Peer-to-peer computing (P2P) including the proposed search mechanism of hybrid periodical flooding (HPF) and routing protocols for improved routing performance
• Wireless and mobile computing, featuring discussions of implementing the Gateway Location Register (GLR) concept in 3G cellular networks, maximizing network longevity, and comparisons of QoS-aware scatternet scheduling algorithms
• High-performance applications including partitioners, running Bag-of-Tasks applications on grids, using low-cost clusters to meet high-demand applications, and advanced convergent architectures and protocols

High-Performance Computing: Paradigm and Infrastructure is an invaluable compendium for engineers, IT professionals, and researchers and students of computer science and applied mathematics.

Contributors.

PART 1. PROGRAMMING MODEL.

1. ClusterGOP: A High-Level Programming Environment for Clusters (Fan Chan, Jiannong Cao and Minyi Guo).

1.1 Introduction.

1.2 GOP Model and ClusterGOP Architecture.

1.3 VisualGOP.

1.4 The ClusterGOP Library.

1.5 MPMD Programming Support.

1.6 Programming Using ClusterGOP.

1.7 Summary.

2. The Challenge of Providing A High-Level Programming Model for High-Performance Computing (Barbara Chapman).

2.1 Introduction.

2.2 HPC Architectures.

2.3 HPC Programming Models: The First Generation.

2.4 The Second generation of HPC Programming Models.

2.5 OpenMP for DMPs.

2.6 Experiments with OpenMP on DMPs.

2.7 Conclusions.

3. SAT: Toward Struct…