Dave Campbell: SQL Server Data Services and the Future of Data in the Cloud
Description
Continuing our exploration of the
Parallel Computing Platform and the folks who think it up and build it, we sit down with software developers Joe Duffy (he wrote the original Parallel LINQ Think Week paper that Bill Gates
read and obviously enjoyed!) and Igor Ostrovsky (he spends his time implementing PLINQ and associated technologies) to deeply dig into how PLINQ works and what makes it tick from a parallel processing point of view.
Lots of whiteboarding and great conversation in this one, as is usual with the people helping to shape our general purpose parallel computing development platform.
Enjoy.
Low res file here.
Lots of whiteboarding and great conversation in this one, as is usual with the people helping to shape our general purpose parallel computing development platform.
Enjoy.
Low res file here.
Share
Download
Download this episode
- Low Quality MP4 (332.6 MB)
- High Quality MP4 (734.6 MB)
- Mid Quality MP4 (512.8 MB)
- Mid Quality WMV (1.1 GB)
- MP3 (28.4 MB)
- WMV (192.0 B)
More episodes in this series
John Lam and Martin Maly: Deep DLR
Related episodes
Parallel Computing Platform: Overview and Future Directions
Stephen Toub - Implementing Parallel Patterns using .NET 4
Parallel LINQ with code samples
Wes Dyer and Stephen Toub: Rx and Px - Working Together
deCast - Introducing parallelism into your applications
Parallel Computing TechTalk (nur der VS2010 Teil)
Task Parallel Library: Task Results
10-4 Episode 6: Parallel Extensions
Technical Summit 2008: Steve Teixeira on Parallel Computing
Using the Parallel Extensions to the .NET Framework
The Discussion
-
gaurav.net Awesome..
Dwnldin999.... -
staceyw Great. Thanks again Joe, Igor, and Charles.
Forcing tasks (i.e. Charles question) on many cores explicitly actually has a simple use case. Correctness debugging. If my code is tricky in terms of the delegate bodies, I may want to ensure all tasks perform on different Procs, even if the library feels 1 thread is enouph. Because your race bugs will not show up using 1 proc or even 1 thread passed around on many procs. -
ymasuda_ Despite difficult theme of parallel algorithm computing, this talk delivered developers friendly knowledge of parallel data management. Supercomputing database language parsers and engines may have this I/O capability, and .NET languages are bound to constitute parallel processing algorithms. For developers business investment, given Parallel language and processors should have to expose extensibility points where .NET developers consider .NET Remoting and Web Services as an area of distributed computing and extensible execution stack to include parallel.
Likewise Windows kernel level thread context management, PLINQ may supply fine granular data access management for managed Threads, on the other hand Windows Clustering and Virtualization may take up supervisor on clustering nodes, and Web Farm and Data Grid may do load balancer similarly.
Development partners should be thankful for fine logical explanation of new ideas PLINQ. -
littleguru Thanks for this video guys!
-
sokhaty Good video. Too short apparently to cover the subject deep enough
General suggestion to the PLINQ team - please do provide programmers with extra knobs and switches to fine tune parallel execution flow.
Based on personal experience with SQL optimizers including the parallel ones, out of five more or less complex queries one would need a hint to run correctly.
I wouldn't expect PLINQ be any different in this regard, especially considering that it will work on data that won't have any statistics associated with them.