1. Parallel Programming in.NET Kevin Luty

2.  History of Parallelism  Benefits of Parallel Programming and Designs  What to Consider  Defining Types of Parallelism  Design Patterns and Practices  Tools  Supporting Libraries Agenda

3.  Hardware  1960-1970’s see parallel hardware in supercomputers  Early 1980’s – super computer built with 64 8086/8087 microprocessors  Late 1980’s – Cluster computing power  Moore’s Law  Amdahl’s Law  Most recently – # of cores over clock speeds History of Parallelism

4.  Moore’s Law Moore’s Law

5. Amdahl’s Law

6.  Hardware  1960-1970’s sees parallel hardware in supercomputers  Early 1980’s – super computer built with 64 8086/8087 microprocessors  Late 1980’s – Cluster computing power  Moore’s Law  Amdahl’s Law  Most recently – # of cores over clock speeds History of Parallelism

7.  Software  One processor means sequential programs  Few APIs that promote/make use of parallel programming  1990’s – No standards were created for parallel programming  By 2000 – Message Passing Interface (MPI), POSIX threads (pthreads), Open Mulitprocessing (OpenMP) History of Parallelism

8.  Task Parallel Library (TPL) for.NET  Hardware capabilities  Easy to write, PLINQ  You can use all the cores!  Timing  Tools available for debugging  Cost Effective Benefits of Parallel Programming

9.  Define:  What needs to be done?  What data is being modified?  Current state?  Cost  Synchronization vs. Asynchronization  Output = What pattern is best What To Consider

10.  Parallelism – Programming with multiple threads, where it is expected that threads will execute at the same time on multiple processors. Its goal is to increase throughput. Defining Types of Parallelism

11.  Data Parallelism – When there is a lot of data, and the same operations must be performed on each piece of data  Task Parallelism – There are many different operations that can run simultaneously Defining Types of Parallelism

13.  Perform the same independent operation for each element  Most common problem is not noticing dependencies  How to notice dependencies  Shared variables  Using properties of an object Parallel Loops

15.  Helpful Properties of TPL .Break and.Stop  CancellationToken  MaxDegreeOfParallelism  Exception Handling  ExceptionAggregate Parallel Loops

16.  Partitioning  Oversubscription and Undersubscription Parallel Loops

17.  Making use of Parallel Loops  Makes use of unshared, local variables  Multiple inputs, single output Parallel Aggregation

18.  Simple Example: Parallel Aggregation

19.  Data Parallelism  Also known as Fork/Join Pattern  Uses System.Threading.Task namespace  TaskFactory  Invoke  Wait/WaitAny/WaitAll  StartNew  Handling Exceptions Parallel Tasks

20.  Handling Exceptions  Exceptions are deferred until Task is done  AggregateException  CancellationTokenSource  Can also cancel tasks outside of a Task Parallel Tasks

21.  Work Stealing Parallel Tasks

22.  Seen like an assembly line Pipelines

23.  Uses BlockingCollection  CompleteAdding  Most problems in this design due to starvation/blocking Pipelines

24.  Future dependencies  Wait/WaitAny/WaitAll  Sequential/Parallel Example Futures

26.  Model-View-ViewModel Futures

27.  Continuous Task adding  Complete Small Tasks then Larger Tasks  Binary Trees and Sorting Dynamic Task Parallelism

28. .NET Performance Profiler (Red-Gate)  JustTrace (Telerik)  GlowCode (Electric Software)  Performance Profiler (Visual Studio 2010 Ultimate)  Concurrency Visualizer  CPU Performance  Memory Management Tools

29.  Task Parallel Library  PLINQ (Parallel Language Integrated Query)  Easy to learn  Rx (Reactive Extensions) Supportive Libraries for.NET

30.  http://en.wikipedia.org/wiki/Moore%27s_law http://en.wikipedia.org/wiki/Moore%27s_law  Campbell, Colin, et al. Parallel Programming with Microsoft.NET: Design Patterns for Decomposition and Coordination on Multicore Architectures. Microsoft, 2010. Print.  Data Parallelism (n.d.). In Wikipedia. Retrieved from http://en.wikipedia.org/wiki/Data_parallelism http://en.wikipedia.org/wiki/Data_parallelism  Hillar, Gaston C. Professional Parallel Programming with C#: Master Parallel Extensions with.NET 4. Indiana: Wiley. 2011. Print.  Rx Extensions (n.d.). In Microsoft. Retrieved from http://msdn.microsoft.com/en-us/data/gg577609.aspx. http://msdn.microsoft.com/en-us/data/gg577609.aspx  T. G. Mattson, B. A. Sanders, and B. L. Massingill. Patterns for Parallel Programming. Addison-Wesley, 2004. References