High-Performance Computing on Complex Environments

  • 9h 29m
  • Emmanuel Jeannot, Julius Zilinskas
  • John Wiley & Sons (US)
  • 2014

With recent changes in multicore and general-purpose computing on graphics processing units, the way parallel computers are used and programmed has drastically changed. It is important to provide a comprehensive study on how to use such machines written by specialists of the domain. The book provides recent research results in high-performance computing on complex environments, information on how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems, detailed studies on the impact of applying heterogeneous computing practices to real problems, and applications varying from remote sensing to tomography. The content spans topics such as Numerical Analysis for Heterogeneous and Multicore Systems; Optimization of Communication for High Performance Heterogeneous and Hierarchical Platforms; Efficient Exploitation of Heterogeneous Architectures, Hybrid CPU+GPU, and Distributed Systems; Energy Awareness in High-Performance Computing; and Applications of Heterogeneous High-Performance Computing.

  • Covers cutting-edge research in HPC on complex environments, following an international collaboration of members of the ComplexHPC
  • Explains how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems
  • Twenty-three chapters and over 100 illustrations cover domains such as numerical analysis, communication and storage, applications, GPUs and accelerators, and energy efficiency

About the Editors

Emmanuel Jeannot is a Senior Research Scientist at INRIA. He received his PhD in computer science from Ecole Normale Superieur de Lyon. His main research interests are processes placement, scheduling for heterogeneous environments and grids, data redistribution, algorithms and models for parallel machines.

Julius Zilinskas is a Principal Researcher and a Head of Department at Vilnius University in Vilnius, Lithuania. His research interests include parallel computing, optimization, data analysis and visualization.

In this Book

  • Summary of the Open European Network for High-Performance Computing in Complex Environments
  • On the Impact of the Heterogeneous Multicoreand Many-Core Platformson Iterative Solution Methods and Preconditioning Techniques
  • Efficient Numerical Solution of 2D Diffusion Equation on Multicore Computers
  • Parallel Algorithms for Parabolic Problems on Graphs in Neuroscence
  • An Overview of Topology Mapping Algorithms and Techniques in High-Performance Computing
  • Optimization of Collective Communication for Heterogeneous HPC Platforms
  • Effective Data Access Patterns on Massively Parallel Processors
  • Scalable Storage I/O Software for Blue Gene Architectures
  • Fair Resource Sharing for Dynamic Scheduling of Workflows on Heterogeneous Systems
  • Systematic Mapping of Reed–Solomon Erasure Codes on Heterogeneous Multicore Architectures
  • Heterogeneous Parallel Computing Platforms and Tools for Compute-Intensive Algorithms: A Case Study
  • Efficient Application of Hybrid Parallelism in Electromagnetism Problems
  • Design and Optimization of Scientific Applications for Highly Heterogeneous and Hierarchical HPC Platforms Using Functional Computation Perfo mance Models
  • Efficient Multilevel Load Balancing on Heterogeneous CPU + GPU Systems
  • The All-Pair Shortest-Path Problem in Shared-Memory Heterogeneous Systems
  • Resource Management for HPC on the Cloud
  • Resource Discovery in Large-Scale Grid Systems
  • Energy-Aware Approaches for HPC Systems
  • Strategies for Increased Energy Awareness in Cloud Federations
  • Enabling Network Security in HPC Systems Using Heterogeneous CMPs
  • Toward a High-Performance Distributed Cbir System for Hyperspectral Remote Sensing Data: A Case Study in Jungle Computing
  • Taking Advantage of Heterogeneous Platforms in Image and Video Processing
  • Real-Time Tomographic Reconstruction Through CPU + CPU Coprocessing


Rating 5.0 of 6 users Rating 5.0 of 6 users (6)
Rating 4.7 of 60 users Rating 4.7 of 60 users (60)
Rating 4.7 of 51 users Rating 4.7 of 51 users (51)