Parallel Computation: Models And Methods

The first seven chapters use R for probability simulation and computation, including random number generation, numerical and Monte Carlo integration, and finding limiting distributions of Markov Chains with both discrete and continuous states. Applications include coverage probabilities of binomial confidence intervals, estimation of disease prevalence from screening tests, parallel redundancy for improved reliability of systems, and various kinds of genetic modeling.

Computing has moved away from a focus on performance-centric serial computation, instead towards energy-efficient parallel computation. This provides continued performance increases without increasing clock frequencies, and overcomes the thermal and power limitations of the dark-silicon era. As the number of parallel cores increases, we transition into the many-core computing era.

Computing has moved away from a focus on performance-centric serial computation, instead towards energy-efficient parallel computation. This provides continued performance increases without increasing clock frequencies, and overcomes the thermal and power limitations of the dark-silicon era. As the number of parallel cores increases, we transition into the many-core computing era.

This volume provides insight into modelling and ultimate limit computation of complex structures, with their components represented by solid deformable bodies. The book examines practically all the important questions of current interests for nonlinear solid mechanics: plasticity, damage, large deformations, contact, dynamics, instability, localisation and failure, discrete models, multi-scale, multi-physics and parallel computing, with special attention given to finite element solution methods.