I’m James Reinders and as I've travelled around talking to programmers about parallel programming I’ve come up with a set of rules of thumb; recurring themes about what makes programmers more ...

Parallel programming exploits the capabilities of multicore systems by dividing computational tasks into concurrently executed subtasks. This approach is fundamental to maximising performance and ...

So obviously a program that produces thousands of tasks of available parallelism will scale a lot better tan one that only produces two tasks. So focus programming to tasks, not to threads.

Current programming languages cannot use the full potential power of manycore chips. Keyvan Azadbakht studied the formal programming language ABS and extended the programming model and analysis ...

How much parallelism this is depends on the experience and knowledge of the programmer. Over the years many projects have been developed that try to automatically catch problems related to locking.

One size does not fit all, and it never will. Parallel programming looks to level the playing field by leveraging multicore hardware.

Parallel Programming in Python This repository offers a collection of Python examples and exercises focused on parallel programming. It covers various concurrency models, including threading, ...