F# for Parallel and Asynchronous Programming

F# for Parallel and Asynchronous Programming

Luke HobanF# Program ManagerMicrosoft Corporation

FT20

F#: Productive, Functional, Scalable

Luke HobanF# Program ManagerMicrosoft

demo

Parallel Computing and PDC09

Parallel Pattern Library

Resource Manager

Task Scheduler

Task Parallel Library

Parallel LINQ

Threads

Operating System

Native Concurrency Runtime

Managed Libraries

ThreadPool

Data Structures D

ata

Stru

ctur

es

Tools

AsyncAgentsLibrary

UMS Threads

MicrosoftResearch

Visual Studio 2010Parallel

Debugger

WindowsProfiler

Concurrency

Analysis

Race DetectionFuzzing

AxumVisual F#Managed Languages

Rx

Native Libraries

Managed Concurrency Runtime

DryadLINQ

Key: Research / Incubation

Visual Studio 2010 / .NET 4 Windows 7 / Server 2008 R2

HPC Server Operating System

Four Big Concurrency Challenges

Shared State

Inversion of ControlI/O ParallelismScaling to multi-machine

Concurrency ChallengesShared State

Inversion of ControlI/O ParallelismScaling to Multi-Machine

o Difficult to maintain and testo Very difficult to parallelize!o Locking is fundamentally error prone:

o Must guess where parallelism will be neededo All consumers need to participate

F#: Immutability and Functional Programming

Luke HobanF# Program ManagerMicrosoft

demo

Concurrency ChallengesShared StateInversion of Control

I/O ParallelismScaling to Multi-Machine

o We’re used to writing code linearlyo Async requires decoupling Begin from Endo Very difficult to

o Combine multiple asynchronous operationso Deal with exceptions and cancellation

Concurrency ChallengesShared StateInversion of ControlI/O Parallelism

Scaling to Multi-Machine

o Software is often I/O-bound o Leveraging web serviceso Working with data on disk

o Network and disk speeds increasing slowero I/O resources are inherently parallel

o Huge opportunity for performance

F#: async { … }

Luke HobanF# Program ManagerMicrosoft

demo

Concurrency ChallengesShared StateInversion of ControlI/O ParallelismScaling to Multi-Machineo To scale up, must to go beyond a single

machineo Multi-machine resources becoming common

o Roll-you-own clusters with cheap hardwareo On-demand cloud compute with Azure

o Buto Shared memory doesn’t scale

F#: Agents and Azure

Luke HobanF# Program ManagerMicrosoft

demo

Recap: Some Concurrency ChallengesShared State

Inversion of ControlI/O ParallelismScaling to Multi-Machine

immutabilityasync { … }async { … }agents

In Summary

Simple, powerful, and productive

Ready for production use with VS2010

F# + .NET 4.0 radically simplify

parallelism

Parallelism and asynchrony – for

today and tomorrow

F#

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