Hojjat Adeli and Sanjay Kumar
Networking of personal computers and workstations is becoming commonplace in academic and industrial environments. A cluster of workstations provides engineers with a familiar, cost-effective environment for high performance computing. However, workstations often have no dedicated link and communicate slowly on a local area network (LAN), such as the Ethernet. Thus, to effectively harness the parallel processing or distributed computing capabilities of workstations, new algorithms need to be developed with a higher computation-to-communication ratio.
Distributed Computer-Aided Engineering presents distributed algorithms for three fundamental areas: finite element analysis, design optimization, and visualization - providing a new direction in high performance structural engineering computing.
Networking of personal computers and workstations is becoming commonplace in academic and industrial environments. A cluster of workstations provides engineers with a familiar, cost-effective environment for high performance computing. However, workstations often have no dedicated link and communicate slowly on a local area network (LAN), such as the Ethernet. Thus, to effectively harness the parallel processing or distributed computing capabilities of workstations, new algorithms need to be developed with a higher computation-to-communication ratio.Distributed Computer-Aided Engineering presents distributed algorithms for three fundamental areas: finite element analysis, design optimization, and visualization - providing a new direction in high performance structural engineering computing.
IntroductionDistributed Finite Element Analysis on a Network of WorkstationsImplementation of Distributed Algorithms for Finite Element Analysis on a Network of WorkstationsDistributed Genetic Algorithms for Design OptimizationDistributed Genetic Algorithms on a Cluster of WorkstationsConcurrent Structural Optimization on Massively Parallel ComputersConcurrent Animation of Seismic Response of Large Structures in a Heterogeneous Computing EnvironmentNew Directions and Final ThoughtsReferences
A cluster of workstations provides engineers with a familiar, cost-effective environment for high performance computing. However, workstations often have no dedicated link and communicate slowly on a local area network (LAN), such as the Ethernet. Thus, to effectively harness the parallel processing or distributed computing capabilities of workstations, new algorithms need to be developed with a higher computation-to-communication ratio. Distributed Computer-Aided Engineering presents distributed algorithms for three fundamental areas: finite element analysis, design optimization, and visualization - providing a new direction in high performance structural engineering computing.
A cluster of workstations provides engineers with a familiar, cost-effective environment for high performance computing. This title presents distributed algorithms for three fundamental areas: finite element analysis, design optimization, and visualization - providing a fresh direction in high performance structural engineering computing.
Über den Autor
Hojjat Adeli and Sanjay Kumar
Inhaltsverzeichnis
IntroductionDistributed Finite Element Analysis on a Network of WorkstationsImplementation of Distributed Algorithms for Finite Element Analysis on a Network of WorkstationsDistributed Genetic Algorithms for Design OptimizationDistributed Genetic Algorithms on a Cluster of WorkstationsConcurrent Structural Optimization on Massively Parallel ComputersConcurrent Animation of Seismic Response of Large Structures in a Heterogeneous Computing EnvironmentNew Directions and Final ThoughtsReferences
Klappentext
Introduction to Distributed Computing.- Distributed Finite Element Analysis on a Network of Workstations-Algorithms.- Distributed Finite Element Analysis on a Network of Workstations-Implementation and Application.- Genetic Algorithms.- Distributed Genetic Algorithms for Design Optimization.- Minimum Weight Design of Large Structures on a Network of Workstations.- Concurrent Design Optimization on Massively Parallel Computers.- References.
