Enabling Parallelism for Productivity Programmers
Tuesday, March 29, 2011 – 5:37 PMI got to spend some time on the beautiful UC Berkeley campus today, giving a talk as part of the Par Lab Seminar Series and got away from rainy Redmond… will it ever end?! More to the point I had some interesting conversations with some of the faculty and students about enabling programmers to be more successful with parallel programming and came away with some thoughts about extending the work we’ve already done and maybe adding some more work to cover data parallelism (GPUs). I asked a question on Stack overflow a few weeks back and got a great answer in the form of a paper published in 1986 describing data parallel programming on the Connection Machine; Hillis & Steele [1986], "Data Parallel Algorithms".
Abstract
Helping productivity programmers develop applications that run well on multicore hardware is one of major challenges to broad adoption of parallel programming. This talk covers some of the work going on at Microsoft to enable Windows developers write applications that target today’s multicore architectures. It gives an overview of the new frameworks, language features added in Visual Studio 2010 to support parallel programming and the patterns they enable.
Some other useful links based on the content of the talk:
Patterns books and code
Visual Studio links
- Python Tools: http://pytools.codeplex.com/
- async and await: http://msdn.microsoft.com/vstudio/async.aspx
Technical Computing Labs “Dryad” links
David Patterson’s An Overview of the UC Berkeley Par Lab deck.
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