Multiprocessing & The.Net Parallel Extensions Guy Ben Haim Senior Application Engineer Intel Asaf Shelly Senior Consultant Pacific Software

Session Objectives and Agenda Multicore Parallel Software.Net Parallel Extensions Q&A Summary

What is Multicore Pentium Pentium Processor Dual Core Quad Core

Moore’s Law – GHz to Multicore Performance 2006 Intel MC Assistance Threading Multi-tasking Training Tools Performance Through Multi-Core frequency -+

Intel Processor Advancement Multiple execution cores ramping across Intel platforms

Why Multi Core? Power Performance 2 GHz 100%

CPU that is 20% Faster Power Performance 2.4 GHz2 GHz 174% 100% 113% 100%

CPU that is 20% Slower Power Performance 1.6 GHz 100% 2 GHz 50% 87% 2.4 GHz 174% 100% 113%

Multi Core: Energy Efficient Performance Power Performance 1.6 GHz 100% 2 GHz 100% 174% 2.4 GHz 174% 100% 113% 174%

What does it mean Multi Cores? Performance

Start Thinking Parallel Software Today Instructions – Assembly – Making it workInstructions – Assembly – Making it work Thinking like a CPUThinking like a CPU Functions – C, Pascal, Basic – Faster CodeFunctions – C, Pascal, Basic – Faster Code Procedural ThinkingProcedural Thinking Objects – C++, Java, C#, Delphi, VB – Manage CodeObjects – C++, Java, C#, Delphi, VB – Manage Code OOD, OOP – Thinking in objectsOOD, OOP – Thinking in objects Tasks - ? – Optimize RuntimeTasks - ? – Optimize Runtime Thinking Parallel

Situation Today Experts, Freelance Specialists, Skilled Groups API is not intuitive Hard to understand execution flow Problematic Design Patterns Little awareness of tools Hidden Problems Hard to test and debug

Understanding Parallel Computing Resources Ownership Global data / Shared data Collisions and Race Conditions Task Design Conjunction Points

Task Oriented Design Modify Write Open Modify Scan

Simple For for ( int y = 0; y < bmp.Height; y++ ) { for ( int x = 0; x < bmp.Width; x++ ) { Pixels[ x, y ] = bmp.GetPixel( x, y ); }

Parallel For Parallel.For( 0, bmp.Height, y => { for ( int x = 0; x < bmp.Width; x++ ) { Pixels[ x, y ] = bmp.GetPixel( x, y ); } });

.Net Parallel Extensions - Performance

Parallel Class Parallel.For Parallel.Do Parallel.ForEach Inplace code / Function Object Type

Parallel Do Parallel Quick Sort: void QuicksortParallel(,, ) { int pivot = Partition(arr, left, right); Parallel.Do( () => QuicksortParallel(arr, left, pivot - 1), () => QuicksortParallel(arr, pivot + 1, right)); }

PLINQ

.Net Parallel Extensions – PLINQ

Task Parallel Library Parallel For, Do, ForEach PLINQ Tasks over Threads Tasks over Cores TaskManager Conjunction Points

.Net Parallel Extensions – Tasks Parallel Library

.Net Parallel Extensions – RayTracer

Tips Shared are Globals Parallel Loops are not loops Define data as Loop internal Race Conditions are still here Don’t use Locks!! Don’t use MUTEXs

Threading Tools  Intel® Thread Checker Used to create correct multi- threaded code  Intel® Thread Profiler Used to analyze performance Intel Software Solutions Group:

Data Race example Serial program What is value of A_SUM: A_Sum = 4 R S1: x = 1.0; y = 2.0 ; A1 = 0; S2: A1 = x * y; S3: A_SUM = 2 * A1; x y A1

Data Race example (Cont.) Initiate x = 1.0; y = 2.0 ; A1 = 0; Thread1 A1 = x * y Thread2 A_SUM = 2 * A1 What is value of x if: Thread1 runs before Thread2? Thread2 runs before Thread1? Execution order is not guaranteed x y A_Sum = 4 A_Sum = 0 A1

Intel® Thread Checker Diagnostics

Source Code Viewer

Performance Profile Threads Speedup Possible causes for this scalability profile: 1.Insufficient parallel work 2.Load imbalance 3.Synchronization overhead 4.Memory bandwidth limitations

Finding Serial and Parallel Time

Load Imbalance Multi Threading should be managed Multi Threading should be managed  Programming should consider load imbalance

Load Imbalance Unequal work loads lead to idle threads and wasted time Busy Idle Time Thread 0 Thread 1 Thread 2 Thread 3 Start threads Join threads

Synchronization  Programming should consider Synchronizations issues

Synchronization By definition, synchronization serializes execution Lock contention means more idle time for threads Busy Idle In Critical Thread 0 Thread 1 Thread 2 Thread 3 Time

Real example : Before fix Serial Parallel Switching Overhead

Real example: After fix Serial Parallel 2 X Speed Up

Summary Parallelize or Perish !

Do we really want Parallel Code? Do users even care?

Change In Mindset Everything is stopped. Waiting for the photographer Everyone is working independently

Developers are writing functions Developers are managing tasks

Doing things the way we always have Things are going to be different

Keep yourself in the loop Public event by Pacific Software Register to the User Group Asynchronous Operations Web Site has all the online resources that you need... and more Register to my five day course titled Multiprocessing Traps and Pitfalls Use our poster to let people know that you know

Resources Download the Microsoft.Net Parallel Extensions bc7f180ba&displaylang=en bc7f180ba&displaylang=en Asynchronous Operations Web Site Intel’s Multicore Pacificsoft Training and Consulting Microsoft Forum for Parallel Computing

Make a difference Let us know what you think Feedback for the.Net Parallel Extensions Dev team Video blog about parallel computing Fill the feedback form …

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