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Parallel Programming in .NET

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Parallel Programming in .NET

  1. 1. Sankarsan Bose 11th July 2010
  2. 2.  Concurrency  Parallel Programming  Parallel Extensions in .NET 4.0  Coordination Data Structures  Task Parallelism  Parallel Loop /Data Parallelism  Parallel LINQ
  3. 3. Concurrency
  4. 4. • Perform multiple Program A Program B computations What in overlapping time Step 1 T periods Step1 I Step2 M E • Responsive UI Step2 • Asynchronous Why Processing Step3 Step3 • Better performance(??) Concurrency is almost everywhere….. OS,Database,Web Servers,GUI programs, File processing….
  5. 5. Program Concurrent Concurrent Concurrent Component 1 Component 2 Component N Read/Write Shared Memory Shared Memory Model of Concurrency
  6. 6. OS Process Thread 1 Thread 2 Thread N Read/Write Shared Memory Operating System View
  7. 7. Managed Program in CLR App Domain Managed Managed Managed Thread 1 Thread 2 Thread N Read/Write Shared Memory .NET Common Language Runtime View
  8. 8. Create ThreadStart delegate with the method to be executed Create instance of Thread class with the ThreadStart delegate Start the thread execution
  9. 9.  Synchronization Issues  Race Condition  Deadlock  Dependency on Memory Model & Hardware Architecture  Debugging becomes complicated
  10. 10. Demo1
  11. 11. Run Suspend Thread1 Thread1 Suspend Thread2 Thread2 Run Single Core Program Processor
  12. 12. Run Thread1 Thread1 Core1 Run Thread2 Thread2 Core2 Program Multi Core Processor Concurrency - Perform multiple computations in overlapping time periods Parallel - Perform multiple computations simultaneously
  13. 13. Parallel Programming
  14. 14.  No more increase in clock speed  Increase in number of processors  Sequential programs won’t scale  Parallel Programming  To leverage hardware advances Source: PDC 09 Patterns of Parallel Programming Workshop
  15. 15.  Decompose the program into parts e.g. methods, statements etc.  Identify the parts which can be executed in parallel  Assign each part to separate tasks  Perform the tasks in parallel on different cores  Each task is likely to perform different actions
  16. 16.  Partition the input data into multiple chunks  Perform action on each chunk in parallel on different cores  Merge the output results  Can be scaled up with more processors as data volume grows
  17. 17. To develop applications for the multicore processors we need  Design  Identify parallel parts  Apply correct design patterns  Libraries  Sophisticated synchronization features to avoid deadlocks/race etc.  Thread safe data structures & containers  Language/API support for common parallel programming patterns to achieve task/data parallelism.  Tools  For debugging parallel applications  For profiling parallel applications Parallel Extensions in .NET 4.0
  18. 18. Parallel Extensions in .NET 4.0
  19. 19. Integrated Programming Models Programming Models Tooling PLINQ Parallel Task Parallel Parallel Pattern Agents Debugger Library Library Library Toolwindows Data Structures Data Structures Concurrency Runtime Concurrency Runtime ThreadPool Profiler Task Scheduler Concurrency Task Scheduler Analysis Resource Manager Resource Manager Operating System Threads Key: Managed Library Native Library Tools Source: PDC 08 Daniel Moth’s Presentation
  20. 20. Thread-safe collections Phased Operation ConcurrentStack<T> ConcurrentQueue<T> ConcurrentDictionary<TKey,TValue> Locks Work exchange BlockingCollection<T> IProducerConsumerCollection<T> Initialization LazyInit<T> Source: PDC 08 Daniel Moth’s Presentation
  21. 21. Demo2
  22. 22. Demo3
  23. 23.  APIs provided under System.Threading & Sytem.Threading.Tasks  Behind the scenes uses CLR Thread Pool  Uses sophisticated algorithms to assign number of threads to maximize performance  More programmatic control than thread or work item  Create/Start Tasks  Return result values from tasks  Chain Multiple Tasks  Nested & Child Tasks  Exception Handling
  24. 24. Constructor - public Task( Action action ) Action delegate - public delegate void Action() Lambda Expression without input parameter and returning nothing Create an explicit instance of Action delegate and pass it to task constructor Start the Tasks
  25. 25. Class: public class Task<TResult> : Task Constructor: public Task( Func<TResult> function ) Delegate: public delegate TResult Func<out TResult>() Lambda Expression without input parameter and returning int Create new instance of Func delegate with no input parameter and returning int We have instantiated & started two tasks which expected to return integer value The property Result stores the return value
  26. 26. Class: public Task ContinueWith( Action<Task> continuationAction ) Instantiate a Task with Action delegate Create an Action delegate with a task object as input and returning nothing. Call ContinueWith method and pass the Action delegate created Start the Task. After this task completes it will Continue With the execution of Action a2 automatically
  27. 27. This is a lambda expression and Task t1 will execute this statements Task t11 is created while Task T1 is executing. This is a Nested Task Task t12 is created while Task T1 is executing but with AttachedToParent option. This is a Child Task. Child tasks are very closely synchronized with the parent
  28. 28. Demo4
  29. 29. Method : public static void Invoke( params Action[] actions ) Three Action delegates are created Three Action delegates will be invoked possibly in Parallel
  30. 30. Demo5
  31. 31. Method : public static ParallelLoopResult For( int fromInclusive, int toExclusive, Action<int> body ) Upper & Lower Bounds of the For Loop Loop Counter Statement executed in the loop When a For() loop has a small body, it might perform more slowly Slower performance is caused by the overhead involved in partitioning the data and the cost of invoking a delegate on each loop iteration.
  32. 32. Method : public static ParallelLoopResult ForEach<TSource>( IEnumerable<TSource> source, Action<TSource> body ) Int Array with values from 0 to 100000 Loop iteration variable Loop Body
  33. 33. Demo6
  34. 34.  Language-Integrated Query (LINQ) was introduced in the .NET Framework version 3.0  Querying on any System.Collections.IEnumerable or System.Collections.Generic.IEnumerable data source  Parallel LINQ (PLINQ) is a parallel implementation of the LINQ pattern  PLINQ tries to make full use of all the processors on the system  Partitions the data source into segments  Executes the query on each segment on separate worker threads in parallel on multiple processors
  35. 35. Method : public static ParallelQuery<TSource> AsParallel<TSource>( this IEnumerable<TSource> source ) Method : public static void ForAll<TSource>( this ParallelQuery<TSource> source, Action<TSource> action ) Instructs to execute the LINQ query in Parallel Invokes in parallel the specified action for each element in the source.
  36. 36. Demo7
  37. 37.  PLINQ, the goal is to maximize performance while maintaining correctness  In some cases, correctness requires the order of the source sequence to be preserved  Ordering can be computationally expensive  PLINQ by default does not preserve the order of the source sequence  To turn on order-preservation the AsOrdered operator is to be used on the source sequence
  38. 38. Method : public static ParallelQuery AsOrdered( this ParallelQuery source ) Instructs to execute the LINQ query in Parallel by preserving order
  39. 39. Demo8
  40. 40. Thank You
  41. 41. http://msdn.microsoft.com/en-us/library/dd460693.aspx http://channel9.msdn.com/pdc2008/TL26/ http://www.ademiller.com/blogs/tech/2009/11/pdc-patterns- of-parallel-programming-workshop/ Concurrent Programming on Windows by Joe Duffy
  42. 42. Additional Slides
  43. 43. This is like a pointer to function which accepts nothing and returns nothing Accepts delegate D as input M2 has no parameter & return value An instance of delegate D or a pointer to method M2 Call to M1 with delegate instance d1 as a parameter. Call to M1 with Lambda Expression Lambda Expression is an anonymous method (input parameters) => (statement)

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