The problems will require to execute a number of independent operations, that operate on shared data. There shall be several threads launched at the beginning, and each thread shall execute a lot of ...

Tasks are the most basic unit of parallel programming. An increasing number of programming languages (including Java and C++) are moving from older thread-based approaches to more modern task-based ...

Hybrid memory is a parallel programming model that combines shared memory and distributed memory. This model is suitable for applications that have both high and low degrees of data locality ...

Parallel programming is a technique that allows multiple tasks to run simultaneously on different processors or cores. It can improve game development by increasing performance, scalability, and ...

We present Navigational Programming (NavP) - a distributed parallel programming methodology based on the principles of migrating computations and multithreading. The four major steps of NavP are: (1) ...

Parallel programming lets us use resources more effectively -- such as CPU cores or communication channels. There are several good options for parallel code (including Parallel.ForEachAsync and ...

This section covers popular programming environments such as pthreads and OpenMP. Next the course discusses the development of parallel programs for distributed address space. The focus in this part ...

In the last few years, geometric semantic genetic programming has incremented its popularity, obtaining interesting results on several real life applications. Nevertheless, the large size of the ...