Parallel Computer Architecture

Learn Distributed Java Applications at Scale, Parallel Programming, Distributed Computing & Cloud Software Architecture

Programming-oriented course on effectively using modern computers to solve scientific computing problems arising in the physical/engineering sciences and other fields. Provides an introduction to efficient serial and parallel computing using Fortran 90, OpenMP, MPI, and Python, and software development tools such as version control, Makefiles, and debugging.

The 12 revised full papers were carefully reviewed and selected from 95 submissions. The papers deal with the following topics: business process modelling; IT service management; interoperability and service-oriented architecture; project management software; scheduling and estimating; software metrics; requirements elicitation and specification; software and systems integration among others.

A unique investigation of the state of the art in design, architectures, and implementations of advanced computational infrastructures and the applications they support
Emerging large-scale adaptive scientific and engineering applications are requiring an increasing amount of computing and storage resources to provide new insights into complex systems. Due to their runtime adaptivity, these applications exhibit complicated behaviors that are highly dynamic, heterogeneous, and unpredictable―and therefore require full-fledged computational infrastructure support for problem solving, runtime management, and dynamic partitioning/balancing.