A distributed parallel genetic algorithm for solving optimal growth models
Computational Economics - Special issue: genetic algorithms
Parallel computing in economics, finance and decision-making
Parallel Computing - Special issue on parallel computing in economics, finance and decision-making
Computational Economics - Computational Studies at Stanford
Parallel Krylov Methods for Econometric Model Simulation
Computational Economics - Special issue on computational studies at Cambridge
Maximum Likelihood Estimation Using Parallel Computing: An Introduction to MPI
Computational Economics
Handbook of Parallel Computing and Statistics (Statistics, Textbooks and Monographs)
Handbook of Parallel Computing and Statistics (Statistics, Textbooks and Monographs)
User-Friendly Parallel Computations with Econometric Examples
Computational Economics
High Performance Linux Clusters: With OSCAR, Rocks, openMosix, and MPI (Nutshell Handbooks)
High Performance Linux Clusters: With OSCAR, Rocks, openMosix, and MPI (Nutshell Handbooks)
A Parallel Implementation of the Simplex Function Minimization Routine
Computational Economics
Comparative parallel execution of SWAT hydrological model on multicore and grid architectures
International Journal of Web and Grid Services
Heterogeneous Computing in Economics: A Simplified Approach
Computational Economics
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The nature of computing is changing and it poses both challenges and opportunities for economists. Instead of increasing clock speed, future microprocessors will have "multi-cores" with separate execution units. "Threads" or other multi-processing techniques that are rarely used today are required to take full advantage of them. Beyond one machine, it has become easy to harness multiple computers to work in clusters. Besides dedicated clusters, they can be made up of unused lab computers or even your colleagues' machines. Finally, grids of computers spanning the Internet are now becoming a reality.