1. Orion Granatir Omar Rodriguez GDC 3/12/10 Don’t Dread Threads

2. Agenda Threading is worthwhile Data decomposition is a good place to start Think tasks!! Intel tools help make things easy 2

3. Threading is important!! 3

4. Multi-core Needs Parallel Applications Threading is required to maximize performance GHz EraMulti-core Era APP PERFORMANCE TIME PLATFORM POTENTIAL PERFORMANCE Parallel Serial 33 FPS in our demo 104 FPS in our demo 4

5. Follow these steps to add threading… 1.Use data decomposition 2.Use tasks 5

6. Functional decomposition is limited Core 6

7. Functional decomposition is limited Core 7

8. Functional decomposition is limited Core Potential latency with pipelining Poor load balancing Doesn’t scale on varying core counts 8

9. Data decomposition can scale to n-cores Core 9

10. Big loops are ideal cases for data decomposition // Loop through each AI for( int Index = 0; Index < g_NumAI; Index++ ) { // Update each AI for this frame g_AI[ Index ].Update(); } 10

11. Minimize interactions // Loop through each AI for( int Index = 0; Index < g_NumAI; Index++ ) { // Update each AI for this frame g_AI[ Index ].Update(); } AI 0AI 1 Set m_HP to 10 11

12. Minimize interactions // Loop through each AI for( int Index = 0; Index < g_NumAI; Index++ ) { // Update each AI for this frame g_AI[ Index ].Update(); } AI 0AI 1 Set m_HP to 10 12

13. Avoid locking // Loop through each AI for( int Index = 0; Index < g_NumAI; Index++ ) { // Update each AI for this frame g_AI[ Index ].Update(); } AI 0AI 1 Set m_HP to 10 13

14. Read global data, don’t write // Loop through each AI for( int Index = 0; Index < g_NumAI; Index++ ) { // Update each AI for this frame g_AI[ Index ].Update(); } 14

15. OpenMP is a great way to get started // Loop through each AI #pragma omp parallel for for( int Index = 0; Index < g_NumAI; Index++ ) { // Update each AI for this frame g_AI[ Index ].Update(); } Serial6 Core 1.00x2.31x Algorithm ~12.0x 15

16. The next step is to use tasks Core 16

17. The next step is to use tasks Core 17

18. The next step is to use tasks Core 18

19. The next step is to use tasks Core Needed for load balancing (avoid oversubscription) Support large chucks of work Better utilization of cache 19

20. Task can be used to parallelize complex problems Texture Lookup Data Parallelism Processing Setup 20

21. Tasks can be arranged in a dependency graph Texture Lookup Data Parallelism Processing Setup 21

22. Dependency graph can be mapped to a thread pool 22

23. Dependency graph can be mapped to a thread pool Core 23

24. Think of a task as a unit of work A task is a unit of work It’s run on a thread pool It runs to completion It has heavy penalties for blocking It’s an efficient way to avoid oversubscription They adapt to any number of threads/cores … regardless of CPU topology 24

25. // Update all AI void UpdateAI( float DeltaTime ) { for( int Index = 0; Index < g_NumAI; Index++ ) { // Update each AI for this frame g_AI[ Index ].Update(); } Data decomposition makes defining tasks easy 25

26. // Update all AI void UpdateAI( float DeltaTime ) { // Determine the number of AI tasks we want to create unsigned int AIGroups = g_NumAI / MAX_AI_PER_GROUP; for( unsigned int Index = 0; Index < AIGroups; Index++ ) { // Build the task specific data AITaskData* pData = new AITaskData(); pData->m_Start = Index * MAX_AI_PER_GROUP; pData->m_DeltaTime = DeltaTime; // Submit task SubmitTask( Task_UpdateAI, (void*)pData ); } Data decomposition makes defining tasks easy 26

27. void Task_UpdateAI( void* pTaskData ) { // Read data AITaskData* pData = (AITaskData*)pTaskData; unsigned int Start = pData->m_Start; unsigned int End = pData->m_Start + MAX_AI_PER_GROUP; // Gap End with max number of AI End = ( End > g_NumAI ) ? g_NumAI : End; // Loop through all of our AI and update for( unsigned int Index = Start; Index < End; Index++ ) { g_AI[ Index ].Update(); } // Cleanup delete pData; } Individual task are run by the thread pool 27

28. Intel Threading Building Blocks is a good for tasks Intel® Threading Building Blocks (Intel® TBB) has a low-level API to create and process trees of work – each node is a task. Root Task More Callback Spawn & Wait Root Task More Spawn Wait Blocking calls go down Continuations go up Root 28

29. Learn more about tasking… … or get Game Engine Gems 1 and read Brad Werth’s article. … or get Game Engine Gems 1 * and read Brad Werth’s article. Task-based Multithreading – How to Program for 100 Cores Presented by Ron Fosner Friday, March 12 @ 4:30PM South 300 29 * Other names and brands may be claimed as the property of others.

30. Time to look at our example… 30

31. Hotspots are good candidates for threading Use tools like Intel® Vtune™ and Intel®Parallel Studio to locate hotspots. 31

32. Hotspots are good candidates for threading Use tools like Intel® Vtune™ and Intel®Parallel Studio to locate hotspots. Intel® Parallel Studio inspector shows that Flock() is the main bottleneck. This is a good place to investigate threading. 32

33. Validate threading results with Parallel Amplifier 1. 2. 33

34. Use Parallel Amplifier to validate concurrency 34

35. Use Parallel Amplifier to validate concurrency We have “ideal” CPU utilization for Flocking. Now we can start looking for other hotspots to optimize. 35

36. Use Parallel Amplifier to validate concurrency We have “ideal” CPU utilization for Flocking. Now we can start looking for other hotspots to optimize. There is still a lot of serial code… 36

37. Use Parallel Inspector to find threading errors 37

38. Use Parallel Inspector to find threading errors 38

39. Use Parallel Inspector to find threading errors Have a lot of system memory Use a reduced data set Workload should be repeatable 39

40. Use other tools as needed… I like Intel® GPA Intel® Graphics Performance Analyzer is designed for games. System Analyzer gives a complete view of system resources (CPU, GPU, Bus) Frame Analyzer allows you to dive into a DX frame Platform View allow you to instrument code to analyze workload balance and execution time. 40

41. Conclusion Threading is required to maximize your game Use data decomposition to scale to n-cores Use tasks for load balancing and to be platform independent Use Intel tools to make your life easier Attend: “Task-based Multithreading – How to Program for 100 Cores” this Friday. 41

42. Email: Orion.R.Granatir@Intel.comOrion.R.Granatir@Intel.com Omar.A.Rodriguez@intel.com http://www.intel.com/software/gdc See Intel at GDC: Intel Booth at Expo, North Hall Intel Interactive Lounge Contact Information 42

43. Other Sessions A Visual Guide to Game and Task Performance on Mass-market PC Game Platforms Thursday, March 11 @ 4:30PM North 122 Building Games for Netbooks Friday, March 12 @ 9AM South 310 Simpler Better Faster Vector Friday, March 12 @ 1:30PM North 122 43

44. Other Sessions Tuning Your Game for Next Generation Intel Graphics Friday, March 12 @ 1:30PM South 302 Task-based Multithreading – How to Program for 100 Cores Friday, March 12 @ 4:30PM South 300 44

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