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Async and Parallel Programming in F# Matthew Podwysocki Senior Consultant http://codebetter.com/ @mattpodwysocki
Agenda F# in 15 Minutes Why is concurrent programming so hard? What can F# do to help?
...a functional, object-oriented, imperative and explorative programming language for .NET with influences from OCaml, C#, Haskell and Erlang Hi! I’m F#
F# in 15 Minutes – The Facts F# is a general purpose .NETlanguage F# is a multi-paradigm language F# is a statically-typed language
F# in 15 Minutes - The Syntax binding names to values let lets = "Hello World" let (x, y) = (45, 54) let answer = x + y let numbers = [1 .. 10] let odds = [1; 3; 5; 7; 9] let square x = x * x let squareOf4 = square 4
F# in 15 Minutes - The Syntax functions as values fun let square x = x * x let squares = List.map (fun x -> x * x) [1..10] let squares = List.map square [1..10] Operators are functions too!
F# in 15 Minutes – The Syntax |> bringing order to chaos let (|>) x f = f x letsumOfSquares =    List.sum (List.map square [1..10]) letsumOfSquares = [1..10]                     |> List.map square                    |> List.sum <| >> << See also:
F# in 15 Minutes – The Syntax discriminated unions type type Suit = | Spade | Heart | Club | Diamond type Rank = | Ace | King | Queen | Jack             | Value ofint type Card = Card of Suit * Rank Microsoft Confidential
F# in 15 Minutes – The Syntax pattern matching match letcardValue (Card(s,r)) = match r with   | Ace                 -> 11   | King | Queen | Jack -> 10   | Value(x)            -> x let (x, y) = ("x", "y") let [a; b] = [1 ; 2] Microsoft Confidential
Concurrent programming with shared state… Is really hard! Microsoft Confidential
Shared State Gives Us… Race conditions! Obscure error messages! Late night debugging! Locks, mutexes and semaphores, oh my! Microsoft Confidential
How Can F# Help Us? Granularity Purity Immutability Libraries
In Praise of Immutability Immutable objects ... can be relied upon ... can transfer between threads ... can be aliased safely ... lead to (different) optimization opportunities
There is no silver bullet
Concurrency Styles Asynchronous Programming Parallel Programming Data Task Actor Model Concurrency
Asynchronous Programming
publicstaticvoidProcessImagesInBulk() { Console.WriteLine("Processing images...  "); long t0 = Environment.TickCount; NumImagesToFinish = numImages; AsyncCallbackreadImageCallback =  newAsyncCallback(ReadInImageCallback); for (inti = 0; i < numImages; i++)   { ImageStateObject state = newImageStateObject(); state.pixels = newbyte[numPixels]; state.imageNum = i; FileStreamfs = newFileStream(ImageBaseName + i + ".tmp", FileMode.Open, FileAccess.Read, FileShare.Read, 1, true); state.fs = fs; fs.BeginRead(state.pixels, 0, numPixels, readImageCallback,         state);   } boolmustBlock = false; lock (NumImagesMutex)   { if (NumImagesToFinish > 0) mustBlock = true;   } if (mustBlock)   { Console.WriteLine("All worker threads are queued. " + " Blocking until they complete. numLeft: {0}", NumImagesToFinish); Monitor.Enter(WaitObject); Monitor.Wait(WaitObject); Monitor.Exit(WaitObject);   } long t1 = Environment.TickCount; Console.WriteLine("Total time processing images: {0}ms",       (t1 - t0)); } publicstaticvoidReadInImageCallback(IAsyncResultasyncResult) { ImageStateObject state = (ImageStateObject)asyncResult.AsyncState; Streamstream = state.fs; intbytesRead = stream.EndRead(asyncResult); if (bytesRead != numPixels) thrownewException(String.Format         ("In ReadInImageCallback, got the wrong number of " + "bytes from the image: {0}.", bytesRead)); ProcessImage(state.pixels, state.imageNum); stream.Close(); FileStreamfs = newFileStream(ImageBaseName + state.imageNum + ".done", FileMode.Create, FileAccess.Write, FileShare.None,       4096, false); fs.Write(state.pixels, 0, numPixels); fs.Close(); state.pixels = null; fs = null; lock (NumImagesMutex)   { NumImagesToFinish--; if (NumImagesToFinish == 0)     { Monitor.Enter(WaitObject); Monitor.Pulse(WaitObject); Monitor.Exit(WaitObject);     }   } } using System; using System.IO; usingSystem.Threading; usingSystem.Runtime.InteropServices; usingSystem.Runtime.Remoting.Messaging; usingSystem.Security.Permissions; publicclassBulkImageProcAsync { publicconstStringImageBaseName = "tmpImage-"; publicconstintnumImages = 200; publicconstintnumPixels = 512 * 512; publicstaticintprocessImageRepeats = 20; publicstaticintNumImagesToFinish = numImages; publicstaticObject[] NumImagesMutex = newObject[0]; publicstaticObject[] WaitObject = newObject[0]; publicclassImageStateObject   { publicbyte[] pixels; publicintimageNum; publicFileStreamfs;   } “Asynchronous File I/O”http://msdn.microsoft.com/en-us/library/kztecsys.aspx State of Asynchronous I/O
letProcessImageAsynci = async { useinStream = File.OpenRead(sprintf"Image%d.tmp"i) let! pixels = inStream.AsyncRead(numPixels) let pixels' = ProcessImage(pixels, i) useoutStream = File.OpenWrite(sprintf"Image%d.done"i) do!outStream.AsyncWrite(pixels') } letProcessImagesAsync() = let tasks = [ foriin 1..numImages ->ProcessImageAsync(i) ] letparallelTasks = Async.Parallel tasks Async.RunSynchronouslyparallelTasks Why Isn’t it This Easy?
Read stream asynchronously letProcessImageAsynci = async { useinStream = File.OpenRead(sprintf"Image%d.tmp"i) let! pixels = inStream.AsyncRead(numPixels) let pixels' = ProcessImage(pixels, i) useoutStream = File.OpenWrite(sprintf"Image%d.done"i) do!outStream.AsyncWrite(pixels') } letProcessImagesAsync() = let tasks = [ for i in 1..numImages ->ProcessImageAsynci ] letparallelTasks = Async.Parallel tasks Async.RunSynnchronouslyparallelTasks This object coordinates Write stream asynchronously Generate the tasks and queue them in parallel “!”  = “asynchronous” Digging Deeper…
letgetHtml (url:string) = async { let request = WebRequest.Createurl use! response = request.AsyncGetResponse() use stream = response.GetResponseStream() use reader = newStreamReader(stream) return! reader.AsyncReadToEnd() } What we’re really writing letgetHtml (url:string) = async.Delay(fun () -> let request = WebRequest.Createurl async.Bind(request.AsyncGetResponse(), funresponse -> async.Using(response, fun response -> async.Using(response.GetResponseStream(), fun stream -> async.Using(new StreamReader(stream), fun reader -> reader.AsyncReadToEnd())))))
How does it work? Success Continuation Async<T> Execution Request Exception Continuation Cancellation Continuation
Anatomy of an Async Operation Async operations Begin/End typeSystem.Net.WebRequestwith memberthis.AsyncGetRequestStream() = Async.BuildPrimitive( this.BeginGetRequestStream,  this.EndGetRequestStream)
What Do We Get For Free? Code that makes sense Exception propagation Cancellation checking Simple resource lifetime management
Twitter Example
Parallel Programming Task Parallel Data Parallel
Data Parallel ProgrammingPLINQ Enable F# developers to leverage parallel hardware Abstracts away parallelism details Partitions and merges data intelligently Works on any seq<'a>/IEnumerable<T> let q = ratings   |> PSeq.adapt   |> PSeq.filter(funp ->p.Name = movieName && p.Rating >= 3.0 && p.Rating <= 5.0)   |> PSeq.sortBy(fun p ->p.Rating)   |> PSeq.map(funp ->p.CustomerId)
Task Parallel Programming Enable F# developers to create tasks in parallel letcomputeHash path algorithm = async { use stream = File.OpenRead path let! bytes = stream.AsyncRead(intstream.Length) let crypt = HashAlgorithm.Create algorithm returncrypt.ComputeHash bytes } let algorithms = ["MD5";"SHA1";"SHA256";"SHA384";"SHA512"] let [|md5;sha1;sha256;sha384;sha512|] = Async.RunSynchronously( Async.Parallel      [for algorithm in algorithms -> computeHash path algorithm])
Task Parallel + Async Workflows TPL Tasks integrated in .NET 4.0 Async Workflows Integrate with pre-defined tasks Calculate Futures letgetStreamData (uri:string) = async { let request = WebRequest.Createuri use! response = request.AsyncGetResponse() return [use stream = response.GetResponseStream() use reader = new StreamReader(stream) while not reader.EndOfStream doyieldreader.ReadLine()] } let result = Async.CreateAsTask <| getStreamDatamyUri do result.Start() letresultValue = result.Value
Bing Translator Example
Actor Model Concurrency Lots of little tasks Each process does one task Ant Colony Ants are processes sending messages to each other
Actor Model in Action… let (<--) (m:'aMailboxProcessor) msg = m.Post(msg) typePinger = Pong typePonger = Ping ofMailboxProcessor<Pinger> | Stop letponger =  newMailboxProcessor<Ponger>(funinbox -> let rec loop pongCount = async { let! msg = inbox.Receive() matchmsgwith               | Ping outbox ->                   outbox <-- Pong return! loop(pongCount + 1)               | Stop -> return () }     loop 0)
Actor Model in Action… letpinger count pong =   newMailboxProcessor<Pinger>(funinbox ->     let rec sendPing() =        async { pong <-- Ping(inbox)               return! loop (count - 1) }     and loop pingsLeft =       async { let! msg = inbox.Receive()               matchmsgwith               | Pong ->                   ifpingsLeft > 0 then                     pong <-- Ping(inbox)                     return! loop(pingsLeft - 1)                   else                                        pong <-- Stop                     return () }     sendPing())
Web Crawling Example
Ant Colony Example
High Performance Computing MPI.NET Dryad/DryadLINQ
What’s in Store for 2010?
Ways to Learn F# http://www.fsharp.net F# Interactive (FSI) Language Specification F# Team Blogs F# (FSharp) Discussion DL http://cs.hubfs.net CodePlex F# Samples .NET Reflector Go to Definition
Books about F#
Resources - Blogs Don Symehttp://blogs.msdn.com/dsyme/ Luke Hobanhttp://blogs.msdn.com/lukeh/ Brian McNamarahttp://lorgonblog.spaces.live.com/ Chris Smithhttp://blogs.msdn.com/chrsmith/ Jomo Fisherhttp://blogs.msdn.com/jomo_fisher/ Planet F#http://feeds.feedburner.com/planet_fsharp

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Async and Parallel F#

  • 1. Async and Parallel Programming in F# Matthew Podwysocki Senior Consultant http://codebetter.com/ @mattpodwysocki
  • 2. Agenda F# in 15 Minutes Why is concurrent programming so hard? What can F# do to help?
  • 3. ...a functional, object-oriented, imperative and explorative programming language for .NET with influences from OCaml, C#, Haskell and Erlang Hi! I’m F#
  • 4.
  • 5. F# in 15 Minutes – The Facts F# is a general purpose .NETlanguage F# is a multi-paradigm language F# is a statically-typed language
  • 6. F# in 15 Minutes - The Syntax binding names to values let lets = "Hello World" let (x, y) = (45, 54) let answer = x + y let numbers = [1 .. 10] let odds = [1; 3; 5; 7; 9] let square x = x * x let squareOf4 = square 4
  • 7. F# in 15 Minutes - The Syntax functions as values fun let square x = x * x let squares = List.map (fun x -> x * x) [1..10] let squares = List.map square [1..10] Operators are functions too!
  • 8. F# in 15 Minutes – The Syntax |> bringing order to chaos let (|>) x f = f x letsumOfSquares = List.sum (List.map square [1..10]) letsumOfSquares = [1..10] |> List.map square |> List.sum <| >> << See also:
  • 9. F# in 15 Minutes – The Syntax discriminated unions type type Suit = | Spade | Heart | Club | Diamond type Rank = | Ace | King | Queen | Jack | Value ofint type Card = Card of Suit * Rank Microsoft Confidential
  • 10. F# in 15 Minutes – The Syntax pattern matching match letcardValue (Card(s,r)) = match r with | Ace -> 11 | King | Queen | Jack -> 10 | Value(x) -> x let (x, y) = ("x", "y") let [a; b] = [1 ; 2] Microsoft Confidential
  • 11. Concurrent programming with shared state… Is really hard! Microsoft Confidential
  • 12. Shared State Gives Us… Race conditions! Obscure error messages! Late night debugging! Locks, mutexes and semaphores, oh my! Microsoft Confidential
  • 13. How Can F# Help Us? Granularity Purity Immutability Libraries
  • 14. In Praise of Immutability Immutable objects ... can be relied upon ... can transfer between threads ... can be aliased safely ... lead to (different) optimization opportunities
  • 15. There is no silver bullet
  • 16. Concurrency Styles Asynchronous Programming Parallel Programming Data Task Actor Model Concurrency
  • 18. publicstaticvoidProcessImagesInBulk() { Console.WriteLine("Processing images... "); long t0 = Environment.TickCount; NumImagesToFinish = numImages; AsyncCallbackreadImageCallback = newAsyncCallback(ReadInImageCallback); for (inti = 0; i < numImages; i++) { ImageStateObject state = newImageStateObject(); state.pixels = newbyte[numPixels]; state.imageNum = i; FileStreamfs = newFileStream(ImageBaseName + i + ".tmp", FileMode.Open, FileAccess.Read, FileShare.Read, 1, true); state.fs = fs; fs.BeginRead(state.pixels, 0, numPixels, readImageCallback, state); } boolmustBlock = false; lock (NumImagesMutex) { if (NumImagesToFinish > 0) mustBlock = true; } if (mustBlock) { Console.WriteLine("All worker threads are queued. " + " Blocking until they complete. numLeft: {0}", NumImagesToFinish); Monitor.Enter(WaitObject); Monitor.Wait(WaitObject); Monitor.Exit(WaitObject); } long t1 = Environment.TickCount; Console.WriteLine("Total time processing images: {0}ms", (t1 - t0)); } publicstaticvoidReadInImageCallback(IAsyncResultasyncResult) { ImageStateObject state = (ImageStateObject)asyncResult.AsyncState; Streamstream = state.fs; intbytesRead = stream.EndRead(asyncResult); if (bytesRead != numPixels) thrownewException(String.Format ("In ReadInImageCallback, got the wrong number of " + "bytes from the image: {0}.", bytesRead)); ProcessImage(state.pixels, state.imageNum); stream.Close(); FileStreamfs = newFileStream(ImageBaseName + state.imageNum + ".done", FileMode.Create, FileAccess.Write, FileShare.None, 4096, false); fs.Write(state.pixels, 0, numPixels); fs.Close(); state.pixels = null; fs = null; lock (NumImagesMutex) { NumImagesToFinish--; if (NumImagesToFinish == 0) { Monitor.Enter(WaitObject); Monitor.Pulse(WaitObject); Monitor.Exit(WaitObject); } } } using System; using System.IO; usingSystem.Threading; usingSystem.Runtime.InteropServices; usingSystem.Runtime.Remoting.Messaging; usingSystem.Security.Permissions; publicclassBulkImageProcAsync { publicconstStringImageBaseName = "tmpImage-"; publicconstintnumImages = 200; publicconstintnumPixels = 512 * 512; publicstaticintprocessImageRepeats = 20; publicstaticintNumImagesToFinish = numImages; publicstaticObject[] NumImagesMutex = newObject[0]; publicstaticObject[] WaitObject = newObject[0]; publicclassImageStateObject { publicbyte[] pixels; publicintimageNum; publicFileStreamfs; } “Asynchronous File I/O”http://msdn.microsoft.com/en-us/library/kztecsys.aspx State of Asynchronous I/O
  • 19. letProcessImageAsynci = async { useinStream = File.OpenRead(sprintf"Image%d.tmp"i) let! pixels = inStream.AsyncRead(numPixels) let pixels' = ProcessImage(pixels, i) useoutStream = File.OpenWrite(sprintf"Image%d.done"i) do!outStream.AsyncWrite(pixels') } letProcessImagesAsync() = let tasks = [ foriin 1..numImages ->ProcessImageAsync(i) ] letparallelTasks = Async.Parallel tasks Async.RunSynchronouslyparallelTasks Why Isn’t it This Easy?
  • 20. Read stream asynchronously letProcessImageAsynci = async { useinStream = File.OpenRead(sprintf"Image%d.tmp"i) let! pixels = inStream.AsyncRead(numPixels) let pixels' = ProcessImage(pixels, i) useoutStream = File.OpenWrite(sprintf"Image%d.done"i) do!outStream.AsyncWrite(pixels') } letProcessImagesAsync() = let tasks = [ for i in 1..numImages ->ProcessImageAsynci ] letparallelTasks = Async.Parallel tasks Async.RunSynnchronouslyparallelTasks This object coordinates Write stream asynchronously Generate the tasks and queue them in parallel “!” = “asynchronous” Digging Deeper…
  • 21. letgetHtml (url:string) = async { let request = WebRequest.Createurl use! response = request.AsyncGetResponse() use stream = response.GetResponseStream() use reader = newStreamReader(stream) return! reader.AsyncReadToEnd() } What we’re really writing letgetHtml (url:string) = async.Delay(fun () -> let request = WebRequest.Createurl async.Bind(request.AsyncGetResponse(), funresponse -> async.Using(response, fun response -> async.Using(response.GetResponseStream(), fun stream -> async.Using(new StreamReader(stream), fun reader -> reader.AsyncReadToEnd())))))
  • 22. How does it work? Success Continuation Async<T> Execution Request Exception Continuation Cancellation Continuation
  • 23. Anatomy of an Async Operation Async operations Begin/End typeSystem.Net.WebRequestwith memberthis.AsyncGetRequestStream() = Async.BuildPrimitive( this.BeginGetRequestStream, this.EndGetRequestStream)
  • 24. What Do We Get For Free? Code that makes sense Exception propagation Cancellation checking Simple resource lifetime management
  • 26. Parallel Programming Task Parallel Data Parallel
  • 27. Data Parallel ProgrammingPLINQ Enable F# developers to leverage parallel hardware Abstracts away parallelism details Partitions and merges data intelligently Works on any seq<'a>/IEnumerable<T> let q = ratings |> PSeq.adapt |> PSeq.filter(funp ->p.Name = movieName && p.Rating >= 3.0 && p.Rating <= 5.0) |> PSeq.sortBy(fun p ->p.Rating) |> PSeq.map(funp ->p.CustomerId)
  • 28. Task Parallel Programming Enable F# developers to create tasks in parallel letcomputeHash path algorithm = async { use stream = File.OpenRead path let! bytes = stream.AsyncRead(intstream.Length) let crypt = HashAlgorithm.Create algorithm returncrypt.ComputeHash bytes } let algorithms = ["MD5";"SHA1";"SHA256";"SHA384";"SHA512"] let [|md5;sha1;sha256;sha384;sha512|] = Async.RunSynchronously( Async.Parallel [for algorithm in algorithms -> computeHash path algorithm])
  • 29. Task Parallel + Async Workflows TPL Tasks integrated in .NET 4.0 Async Workflows Integrate with pre-defined tasks Calculate Futures letgetStreamData (uri:string) = async { let request = WebRequest.Createuri use! response = request.AsyncGetResponse() return [use stream = response.GetResponseStream() use reader = new StreamReader(stream) while not reader.EndOfStream doyieldreader.ReadLine()] } let result = Async.CreateAsTask <| getStreamDatamyUri do result.Start() letresultValue = result.Value
  • 31. Actor Model Concurrency Lots of little tasks Each process does one task Ant Colony Ants are processes sending messages to each other
  • 32. Actor Model in Action… let (<--) (m:'aMailboxProcessor) msg = m.Post(msg) typePinger = Pong typePonger = Ping ofMailboxProcessor<Pinger> | Stop letponger = newMailboxProcessor<Ponger>(funinbox -> let rec loop pongCount = async { let! msg = inbox.Receive() matchmsgwith | Ping outbox -> outbox <-- Pong return! loop(pongCount + 1) | Stop -> return () } loop 0)
  • 33. Actor Model in Action… letpinger count pong =   newMailboxProcessor<Pinger>(funinbox ->     let rec sendPing() =       async { pong <-- Ping(inbox)               return! loop (count - 1) }     and loop pingsLeft =       async { let! msg = inbox.Receive()               matchmsgwith               | Pong ->                   ifpingsLeft > 0 then                     pong <-- Ping(inbox)                     return! loop(pingsLeft - 1)                   else                     pong <-- Stop                     return () }     sendPing())
  • 36. High Performance Computing MPI.NET Dryad/DryadLINQ
  • 37. What’s in Store for 2010?
  • 38. Ways to Learn F# http://www.fsharp.net F# Interactive (FSI) Language Specification F# Team Blogs F# (FSharp) Discussion DL http://cs.hubfs.net CodePlex F# Samples .NET Reflector Go to Definition
  • 40. Resources - Blogs Don Symehttp://blogs.msdn.com/dsyme/ Luke Hobanhttp://blogs.msdn.com/lukeh/ Brian McNamarahttp://lorgonblog.spaces.live.com/ Chris Smithhttp://blogs.msdn.com/chrsmith/ Jomo Fisherhttp://blogs.msdn.com/jomo_fisher/ Planet F#http://feeds.feedburner.com/planet_fsharp

Notas do Editor

  1. What is the Problem?Multithreaded programming is hard todayDoable by only a subgroup of senior specialistsParallel patterns are not prevalent, well known, nor easy to implementSo many potential problemsRaces, deadlocks, livelocks, lock convoys, cache coherency overheads, lost event notifications, broken serializability, priority inversion, and so on…Businesses have little desire to go deepBest developers should focus on business value, not concurrencyNeed simple ways to allow all developers to write concurrent code