.NET Parallel Programming

All about Async/Await, System.Threading.Tasks, System.Collections.Concurrent, System.Linq, and more…

Chunk partitioning vs range partitioning in PLINQ
If you look in the PLINQ samples in the December 2007 CTP, you'll see a parallel implementation of Luke Hoban's LINQ ray tracer.  The sample parallelizes the ray tracer by changing very few lines of code.   Luke's original query started as follows: from y in Enumerable.Range(0, screenHeight)For our sample, we've changed that to:
New “Parallel Computing” dev center on MSDN
There's a new Parallel Computing developer center on MSDN: "Microsoft’s Parallel Computing developer center is dedicated to providing information, ideas, community, and technology to developers to make it easier to write programs that perform and scale well on parallel hardware."  Check it out!  There are already a plethora of
PLINQ changes since the MSDN Magazine article
I posted about changes we've made to the Task Parallel Library since we published the MSDN Magazine article outlining its design.  In this post, I'll do the same thing for PLINQ.  Most of the October 2007 article on PLINQ is still accurate.   After all, PLINQ is largely an implementation of the .NET Standard Query Operators
Task Parallel Library changes since the MSDN Magazine article
Back in the October 2007 issue of MSDN Magazine, we published an article on the beginning stages of what has become the Task Parallel Library (TPL) that's part of the Parallel Extensions to the .NET Framework.  While the core of the library and the principles behind it have remained the same, as with any piece of software in the earl
CTP Quality
Community Technology Preview (CTP) releases from Microsoft typically provide early looks at the technologies a team is working on.  Frequently, CTP quality is nowhere near what folks might expect from Beta releases and the like, and that's ok.  The idea is to give all of you in the community a look at what we're working on, giving yo
Welcome to the Parallel Extensions team blog!
Software is headed for a fundamental change.  Over the last 30 years, developers have relied on exponential growth in computing power in order to dream big.  Your cool new application is too slow today?  No problem, just wait two years and everyone will have computers that run twice as fast.  But as Herb Sutter wrote, &ldqu