An Insiders View to Concurrency at Microsoft Stephen

An Insider’s View to Concurrency at Microsoft Stephen Toub (stoub@microsoft. com) Parallel Computing Platform Microsoft Corporation

Agenda • Why We (I) Care • What We’ve Built for Developers • What We’re Building for Developers

Moore’s Law: Alive and Well http: //upload. wikimedia. org/wikipedia/commons/2/25/Transistor_Count_and_Moore%27 s_Law_-_2008_1024. png

MS Apps Using Parallelism Example: Visual Studio • Unit testing • Background compilation • … • Regex-based file search • Graph layout • Reference highlighting • Intelli. Sense sorting • Project build system • Code analysis

But it’s not just about core count… • Increasingly connected applications • More latency • e. g. everything as a service • More UI responsiveness problems • e. g. the toilet bowl of death • More scalability issues • Server, Cloud • e. g. streaming data sources, data distribution • Client • e. g. modeling interacting biological entities • Async-only APIs • e. g. Silverlight

The Challenges of Concurrency • A different way of thinking • Forcing the square peg (concurrency) into the round hole (sequential) is a common (inadequate) mistake • Parallel patterns are not prevalent, well known, nor easy to implement • CS curriculum is still largely “sequential”: Cormen, et. al; Knuth; etc. • A different way of writing software • Indeterminate program behavior • No longer: “A happens, then B happens, then C happens” • It’s just: “A, B, and C happen” • With distinct costs, too • Deadlocks, livelocks, latent race conditions, priority inversions, hardware-specific memory model reordering, … • Businesses have little desire to go deep • Best devs should focus on business value, not concurrency • Need simple ways to allow all devs to write concurrent code

Example: Searching and Sorting IEnumerable<Race. Car. Driver> drivers =. . . ; var results = new List<Race. Car. Driver>(); foreach(var driver in drivers) { if (driver. Name == query. Name && driver. Wins. Count >= query. Win. Count) { results. Add(driver); } } results. Sort((b 1, b 2) => b 1. Age. Compare. To(b 2. Age));

Manual Parallel Solution IEnumerable<Race. Car. Driver> drivers = …; var results = new List<Race. Car. Driver>(); int partitions. Count = Environment. Processor. Count; int remaining. Count = partitions. Count; var enumerator = drivers. Get. Enumerator(); try { using (var done = new Manual. Reset. Event(false)) { for(int i = 0; i < partitions. Count; i++) { Thread. Pool. Queue. User. Work. Item(delegate { while(true) { Race. Car. Driver driver; lock (enumerator) { if (!enumerator. Move. Next()) break; driver = enumerator. Current; } if (driver. Name == query. Name && driver. Wins. Count >= query. Win. Count) { lock(results) results. Add(driver); } } if (Interlocked. Decrement(ref remaining. Count) == 0) done. Set(); } done. Wait. One(); results. Sort((b 1, b 2) => b 1. Age. Compare. To(b 2. Age)); } } finally { if (enumerator is IDisposable) ((IDisposable)enumerator). Dispose(); }

PLINQ Solution IEnumerable<Race. Car. Driver> drivers =. . . ; var results = from driver in drivers. As. Parallel() where driver. Name == query. Name && driver. Wins. Count >= query. Win. Count orderby driver. Age ascending select driver;

Demo PLINQ

Visual Studio 2010 Tools, Programming Models, Runtimes Visual Studio 2010 Profiler Concurrency Visualizer Parallel LINQ Task Parallel Library . NET Framework 4 Thread. Pool Data Structures Parallel Debugger Tool Windows Programming Models Data Structures Tools Parallel Pattern Library Async Agents Library Visual Concurrency C++ 2010 Runtime Task Scheduler Resource Manager Operating System Threads. Windows Key: Managed Native Tooling UMS Threads

Investigations for the future…

This is some synchronous code with. NET 4… public void Copy. Stream. To. Stream(Stream source, Stream destination) { byte[] buffer = new byte[0 x 1000]; int num. Read; while ((num. Read = source. Read(buffer, 0, buffer. Length)) != 0) { destination. Write(buffer, 0, num. Read); } }

This is an expert’s asynchronous code with. NET 4… public IAsync. Result Begin. Copy. Stream. To. Stream( Stream source, Stream destination) { var tcs = new Task. Completion. Source<object>(); byte[] buffer = new byte[0 x 1000]; Action<IAsync. Result> read. Write. Loop = null; read. Write. Loop = iar => { try { for (bool is. Read = iar == null; ; is. Read = !is. Read) { switch (is. Read) { case true: iar = source. Begin. Read(buffer, 0, buffer. Length, read. Result => { if (read. Result. Completed. Synchronously) return; read. Write. Loop(read. Result); }, null); if (!iar. Completed. Synchronously) return; break; public void Copy. Stream. To. Stream(Stream source, Stream destination) { byte[] buffer = new byte[0 x 1000]; int num. Read; while ((num. Read = source. Read(buffer, 0, buffer. Length)) != 0) { destination. Write(buffer, 0, num. Read); } } case false: int num. Read = source. End. Read(iar); if (num. Read == 0) { tcs. Try. Set. Result( null); return; } iar = destination. Begin. Write(buffer, 0, num. Read, write. Result => { if (write. Result. Completed. Synchronously) return ; destination. End. Write(write. Result); read. Write. Loop( null); }, null); if (!iar. Completed. Synchronously) return; destination. End. Write(iar); break; } } } catch (Exception e) { tcs. Try. Set. Exception(e); } }; read. Write. Loop(null); return tcs. Task; } public void End. Copy. Stream. To. Stream(IAsync. Result async. Result) { ((Task)async. Result). Wait(); }

A compiler could do the work for us… public void Copy. Stream. To. Stream(Stream source, Stream destination) { byte[] buffer = new byte[0 x 1000]; int num. Read; while ((num. Read = source. Read(buffer, 0, buffer. Length)) != 0) { destination. Write(buffer, 0, num. Read); } } public Task Copy. Stream. To. Stream(Stream source, Stream destination) { byte[] buffer = new byte[0 x 1000]; int num. Read; while ((num. Read = await source. Read. Async(buffer, 0, buffer. Length)) != 0) { await destination. Write. Async(buffer, 0, num. Read); } }

Q&A

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