1. Parallel Extensions A glimpse into the parallel universe By Eric De Carufel Microsoft.NET Solution Architect at Orckestra eric.decarufel@orckestra.com eric@decarufel.net http://blog.decarufel.net

2. Agenda Introduction Overview Library Core TPL (Task Parallel Library) Parallel Linq (PLINQ) Parallel Data Structures Questions

3. Introduction Why do we have to bother?  Moore’s law is over, no more free lunch  Multi cores systems will be more and more available Type of Parallelism  Asynchronous operation (better user experience)  Data parallelism  Task parallelism Options  Manual treading  Thread, ThreadPool, BackgroundWorkerThread  Asynchronous calls  Event driven Problems  Resource sharing  Locking  Non-deterministic sequence of execution  Hard to debug

4. Overview

5. Task Parallel Library (TPL) Lightweight task framework (Task)  Create(Action ) factory method  Wait, WaitAll, WaitAny to catch exception  ContinueWith to chain Tasks together Lazy function call  Future Task scheduler and manager  TaskManager

6. Parallel API Parallel Loops  Parallel.For  Parallel.ForEach Lazy Initialisation  LazyInit Locking  SpinWait  SpinLock CountdownEvent

7. Parallel API Standard for loop  for (int i = 0; i < N; i++) { a[i] = Compute(i); } Parallel for loop  Parallel.For(0, N, i => { a[i] = Compute(i); });

8. Parallel Linq (PLINQ) Parallel Query  AsParallel() Return to sequential execution  AsSequential() Preserve order  AsOrdered() Order doesn’t matter  AsUnordered()

9. Parallel Linq (PLINQ) var query = from c in Customers where c.Name = “Smith” select c; var query = from c in Customers.AsParallel() where c.Name = “Smith” select c;

10. Parallel Data Structures IConcurrentCollection  Add(T item)  Remove(out T item) ConcurrentStack  Push(T item)  TryPop(out T item) ConcurrentQueue  Enqueue(T item)  TryDequeue(out T item) BlockingCollection  Add(T item),  Remove(out T item)  TryAdd(T item),  TryRemove(out T item)

11. CLR Thread Pool: Work-Stealing Worker Thread 1 Worker Thread p Program Thread User Mode Scheduler For Tasks Global Queue Global Queue Local Queue Local Queue Local Queue Local Queue Task 1 Task 2 Task 3 Task 5 Task 4 Task 6

12. Ideas Task stealing Integration into language maybe for later Potentially in parallel Exception Handling Garbage collection Shift from threads to tasks (more than needed) Divide and conquer leads to more parallelism opportunities Use of CPU, GPU or Scale out To get another 100x performance  The Power Wall  The Complexity Wall  The Memory Wall

13. What’s next Visual Studio 2010.NET Framework 4.0 New multi cores computer (4, 16, 32, 64, …) Think parallel!