Parallelism in .NET – Part 11, Divide and Conquer via Parallel.Invoke
Many algorithms are easily written to work via recursion. For example, most data-oriented tasks where a tree of data must be processed are much more easily handled by starting at the root, and recursively “walking†the tree. Some algorithms work this way on flat data structures, such as arrays, as well. This is a form of divide and conquer: an algorithm design which is based around breaking up a set of work recursively, “dividing†the total work in each recursive step, and “conquering†the work when the remaining work is small enough to be solved easily.
Recursive algorithms, especially ones based on a form of divide and conquer, are often a very good candidate for parallelization.
Parallelism in .NET – Part 10, Cancellation in PLINQ and the Parallel class
Many routines are parallelized because they are long running processes. When writing an algorithm that will run for a long period of time, its typically a good practice to allow that routine to be cancelled. I previously discussed terminating a parallel loop from within, but have not demonstrated how a routine can be cancelled from the caller’s perspective. Cancellation in PLINQ and the Task Parallel Library is handled through a new, unified cooperative cancellation model introduced with .NET 4.0.
Parallelism in .NET – Part 9, Configuration in PLINQ and TPL
Parallel LINQ and the Task Parallel Library contain many options for configuration. Although the default configuration options are often ideal, there are times when customizing the behavior is desirable. Both frameworks provide full configuration support.
Parallelism in .NET – Part 8, PLINQ’s ForAll Method
Parallel LINQ extends LINQ to Objects, and is typically very similar. However, as I previously discussed, there are some differences. Although the standard way to handle simple Data Parellelism is via Parallel.ForEach, it’s possible to do the same thing via PLINQ.
PLINQ adds a new method unavailable in standard LINQ which provides new functionality…
