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UCSD Site Report to the IAB Sheldon Brown Site Director Daniel Tracy CHMPR Programmer May 11, 2011 Baltimore, MD.

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Presentation on theme: "UCSD Site Report to the IAB Sheldon Brown Site Director Daniel Tracy CHMPR Programmer May 11, 2011 Baltimore, MD."— Presentation transcript:

1 UCSD Site Report to the IAB Sheldon Brown Site Director Daniel Tracy CHMPR Programmer May 11, 2011 Baltimore, MD

2 Overview 2 Ongoing Projects Multi-User Extensible Virtual Worlds Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games Extending the CHMPR Future Cinema – has revised focus on Augmented Reality FRP and RapidMRI projects underway REU – two new undergraduates involved in research Complementary project with NSF EAGER grant –“Identifying and Integrating Creative Patterns of User Behavior and

3 Staff Sheldon Brown, Site Director –Erik Hill, Programmer Analyst –Daniel Tracy, Programmer Analyst –Todd Margolis, Progammer Analyst –Kristen Kho, Programmer Analyst –Jeremy Douglass, Post-Doc Researcher –Vivek Ramavajjala, Graduate Student –Sam Kronik, Graduate Student –Robin Betz, Undergraduate Student –Bradley Ruoff, Undergradauate Student –Lourdes Guardiano-Durkin, Administrator 3

4 Projects Ongoing projects: Multi-user Extensible Virtual Worlds Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games Revised Project Future Cinema as Augmented Reality Affiliated Projects Identifying and Integrating Creative Patterns of User Behavior and Experience in Virtual Worlds 4

5 Products and Activities Last six months: Virtual World Exhibitions CSU Sacramento UCSD 50 th Anniversary Innovation Expo Next Generation Cinema Presentations presentation by Justin Rattner, Intel Featured on French/German TV: Souvenirs from Earth Ukraine: Video Art in a Global Context Exhibition Mexico Moving Forward College Art Association New York 3D movie featured at Seoul Korea Film Festival Scalable City wins first prize in Sony Europe 3D movie competition Lectures Varieties of Virtual World Experience via Multicore Computing at the Frontiers of Multicore Computing Intel Labs Radio Show Keynote talk for NEA/NSF Summit at RPI EMPAC. I gave one of the keynote talks Publications Tracy D., Brown S. Combining Parallel & Incremental Techniques for Real-Time Physics in Large, Continuous Virtual Environments. Journal of Computing and Concurrancy – pending publication. Website:

6 Multi-user Extensible Virtual Worlds Status: Continuing Project Description: Multi-user Extensible Virtual Worlds In order for virtual worlds to realize their potential across a number of areas of industry and research domains, along with serving as generally effective social forums, their expressive qualities need to be significantly improved upon. They require a considerable increase in the quantity and quality of entities and their interactions. This also entails a substantial increase in the sizes of virtual worlds, the number of users that are able to be supported, the variety of objects and behaviors and the simultaneity of entity interactions. Sponsors: IBM, Intel Deliverables: –Prototype Multi-user Virtual World ongoing development 6

7 Multi-user Extensible Virtual Worlds Status: Continuing Sponsors: IBM, Intel Deliverables: –Prototype Multi-user Virtual World ongoing development Major results –Optimizing Client Server operations. Integrating Compute accelerators. 7

8 Scalable City: Massive Scale Virtual Worlds Massively multiplayer continuous world Hundreds of thousands of interactive objects Large aggregate bandwidth requirements Challenges/Issues Optimization, feature development, workable across heterogeneous clients 8

9 Goals Scalability –Support large environments, massively multi- player Hybrid, Multi-platform server –z10, x86, CellBE, Tesla accelerators Performance –Clients need to perform well on a range of desktop computer configurations 9

10 Increasing complexity of objects and interactions with increasing world size, users, numbers of objects and types of interactions. Server services are distributed across cloud clusters, and redistributed across clients as performance or local work necessitates. Coherency with overall system is pursued, managed by centralized server. Virtual world components have dynamic tolerance levels for discoherency and latency. compute accelerators for asset transformation, physics and behaviors. Multiple 10gb interfaces to compute accelerators, storage clusters and compute cloud. Server system keeps track of world state. 10

11 3 10gb interfaces to compute accelerators Development Server Framework 5/2010 IBM Z10 mainframe computer at San Diego Supercomputer Center 2- IFL’s with 128mb Ram, zVM virtual OS manager with Linux guests 6 tb storage fast local storage – 15K disks 4 SR and 2 LR 10gb ethernet interfaces 4 QS20 blades – 8 Cell CPU’s 2 QS22 blades - 4 Cell CPU’s 8HS22 blades - 16 Xeons – 96 cores 4 way Xeon Server – 32 core 1 10gb interfaces to internet nVidia Tesla accelerator – 4 GPU’s on linux host, external dual pci connection. Many Clients 11

12 How do you program a distributed heterogeneous system? Server manages various virtual world processes. Use compute accelerators for compute intensive, parallelizable subsystems such as physics. Two phase approach: –Different systems for different underlying architectures return compatible results Xeon blades running Scalable Physics Engine x86 optimized GPU’s or novel architectures run Bullet engine Distribute heavy computational stages Collision Detection on broad phase pair output Constraint solving/Integration on contact groups Long term approach : OpenCL plan –Develop physics system using algorithms well-suited to OpenCL parallelization –Applicable to both object collisions and deformation –Same code base for different hardware – host or server side accelerators –Parallelization occurs throughout the physics pipeline –Linearly scalable to availability of hardware resources –Similar approach for other aspects of asset computation 12

13 Multi-user Environment Server Goals: –10,000 players on 1,000 cities Performance Challenges –Communication: 14.2 GB/sec to clients –Physics: 200,000 active objects –Rendering: x10 particle system complexity 13

14 Communication Fast & non-redundant data marshalling/archiving –“Player data-sharing” optimizations Generating assets deterministically on client –Removes need to communicate resources Reduced c/s synchronization frequency –Client-side interpolation Further tweaks to reduce bandwidth –Messages consolidated, compressed Adaptability to Client Hardware 14

15 Heterogeneous Client Support Client machine profiling –Processing power (CPU, GPU, # of cores) –Rendering performance –Networking latency/bandwidth Dynamic fidelity adjustment –Graphics effects Shadows, volumetric rendering, particle systems… –Planned: Compute/synchronization trade-off 15

16 Future Work: Client-side Predictive Physics Interpolation smooths movement until server stalls –If server increases lag, there is nothing to interpolate to! Inject copy of Server functionality into Client –Performs same work on subset of data for prediction Server state may differ from prediction –Client interpolates what user sees during correction Allows us to decrease synchronization latency much further –Update frequency adjustable based on client process/network 16 Client Server

17 Tool of Interest: Growth Tracker 17

18 Stability Complex software subject to glitches Scalable City designed to run continuously Some bugs don’t manifest immediately –Scalable City grew virtual memory footprint Confirmed no memory leaks! Tools exist to detect memory leaks quickly 18

19 Stability Higher-level “memory leak” problems: –Aggregate structures that persist across processing cycles can grow unbounded –Not a detectable problem to the system! Scalable City uses massive number –STL & boost structures, strings, etc, etc. Data Structure Growth Tracking Tool –Override implementation of all aggregates! 19

20 Growth Tracker Growth tracker is a “singleton class” –One instance in each program (client/server) Every instance tracked by singleton class –Registers upon creation Every instance sampled periodically –Exponentially-increasing sample time Size of each instance tracked over time –Algorithm detects problem based upon history 20

21 Growth Tracker Practical implementation in large project –Cannot modify data structure usage code! Must be self-contained solution –Must override all aggregates in all files Required advanced C++ features –Complex, but small implementation –Little data extractable: address, complete type Remains installed: one command turns on 21

22 Growth Tracker Useful software tool –Generalizes to any long-running program Requires running application for 1-2 days –No general way to detect unintended growth Provides more useful output than a crash upon allocation! –This kind of problem can be impractical to find in large software without such a tool 22

23 Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games Status: Continuing Project Description: Digital media environments are increasingly authored by users while they interact with them. This means that components such as their media assets and their behavior is under real-time control, rather then authored in advance. Doing so presents computational challenges to insure ongoing real-time performance, it also creates challenges in tracking assets across multiple types of instantiations. Sponsors: IBM, Intel, Deliverables: –Improve dynamics and asset computation across virtual worlds and digital cinema 23

24 Physical-based Simulation in the Massively Multi-player Scalable City Environment using OpenCL Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games 24

25 Review of work to date Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games 25

26 Scalable City: Physics Engine Evolution Open Dynamics Engine Open Source, Convenient, Good Reputation Augmented/Replaced subsystems over time Broad phase CD designed for large VR environ. Pipeline redesign for resting objects Multi-threaded subsystems for higher activity Only the core constraint solver remains ODE 26

27 Pipeline Redesign 27 Overhead proportional to level of activity, rather than environment scale Novel broad phase and pipeline methods

28 Multithreaded Stages 28 Thread-parallelism: limited scale Traditional physics methods allow limited parallelism

29 New Physics Engine 29 New physics engine from scratch in C++ Designed for massive parallelism –SIMD & massively threaded (via OpenCL) –Distributed Computing (MPI) Unique design for OpenCL physics –“Advanced Character Physics”, Thomas Jakobsen

30 Massively Parallel Physics Physics atoms are particles & constraints Objects represented as set of these atoms Rigid Body Dynamics behavior is “emergent” Soft bodies can also be modeled integrally 30

31 Advantages Massive, simple, evenly divided computations –Collision detection and constraints operate on particles –All constraints are solved independently Eliminates most OpenCL buffer transfers –No contact graph generation stage –Broad phase collision detection integrated with collision constraint solving 31 Contact Graph Coll. Det.IntegrationN-BodyIntegrationColl. Det.N-Body

32 Implementation Progress Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games 32

33 Progress: Last Meeting What we had finished: Particle system with Verlet integration Heightmap constraint w/ interpolation, friction, bounce Stick constraints Rigid body construction from particles + sticks Multi-pass relaxation solver Object transform extraction from particles Dynamic object insertion & removal during simulation 33

34 Progress: Last Meeting What we were lacking:  Support for multiple object topologies in OpenCL  Efficient OpenCL transfers for object migration  Parallel OpenCL broad phase collision detection  Integration into Scalable City incremental physics  MPI layer for distributed processing 34

35 Progress: Current Additional Progress: Support for multiple object topologies in OpenCL Efficient OpenCL transfers for object migration Parallel OpenCL broad phase collision detection  Integration into Scalable City incremental physics  MPI layer for distributed processing 35

36 Object Multi-topology Support Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games 36

37 Object Multi-Topologies 37 Requires indirection in accessing object info –Single buffer per format (sticks, particles, forces) –Mapping from object to ranges in each in CL Hole-tracking on host to re-use regions –Supports dynamic object insertion-removal –Exact fit replacement Efficient for small # of discrete topologies

38 Object Multi-Topologies 38 Particles: positions, forces, mappings Objects: track allocations, object identity Sticks: rest length, mappings StickAccum: calculation results particle x stick Collision Detection Collision Detection: filter self collisions Average Constraints Produce Constraints OpenCL Host: Hole tracking for Particles, Sticks, StickAccum OpenCL Memory Host Memory

39 Efficient OpenCL Communication Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games 39

40 OpenCL Communication 40 Most communication has been eliminated –All operations performed in CL Updating multiple buffers req’d for insertion –Supports distributed & incremental systems –Object insertion requires small blits to 9 buffers Multiple insertions will be non-contiguous Extremely slow when CL is mapped to GPU devices!

41 Transfer Optimizations 41 Must consolidate multi-buffer writes –One buffer contains data & destination metadata –A single, contiguous transfer to CL device Host-directed Transfers –Multiple asynchronous clEnqueueCopyBuffer() Kernel-directed Transfers –Kernel execution performs all transfers on card

42 Transfer Optimizations 42 Both methods much preferable to naïve buffer updates!

43 Transfer Optimizations 43 Kernel-driven buffer updates 40% faster in test case

44 OpenCL Communication 44 Future Kernel-Driven Optimizations –Better load balancing Better control of transfer size for each entry –Lower space overhead Reduce meta-data overhead Reduces time to transfer single buffer of updates Ordering entries by destination buffer is a good start

45 Parallel OpenCL Broad Phase Collision Detection Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games 45

46 OpenCL Broad Phase 46 Lack of OpenCL BP is now largest overhead –Communication, Nonparallel execution –30-50% of execution time Learning from well-engineered examples –nVidia: OpenCL Particle Collision Simulation Hash grid: High Performance, Feature Poor

47 OpenCL Broad Phase 47 Grid Limitation: Cell based on object size –Scalable City uses vastly different object sizes House pieces, cyclones, lot entities, gravity fields Not an “incremental algorithm” –Almost impossible in OpenCL: give up –Some acceleration from temporal coherence? Sorting strategy

48 Parallel Sweep & Prune 48 Utilizes intervals for some size variation Sort & implicitly subdivide along one axis Sort partial buffer along another axis Parallel second pass detects overlaps

49 Space Filling Curve Sort 49 Modified Morton numbers provide –Spatial locality order in one sort pass –Conservative interval calculation eliminates false negatives

50 Hash Grid with Queries 50 Majority of objects have similar size –House pieces: mapped to grid for n-body Medium size objects queried against range of grid cells in separate kernel –Lots, cyclones collide with house pieces, but not with each other –Unit of parallelism improved to Object/Cell pair Gravity fields done in different subsystem

51 OpenCL Broad Phase 51 Overlap reporting challenge –Reporting subset of n 2 possible pairs efficiently Known solution: predict overlaps per object –Potentially missed overlaps or multiple passes –Inefficient storage includes gaps Does not apply to our use case!

52 OpenCL Broad Phase 52 Our physics solves constraints individually –No assembling or reporting of pairs necessary –Kernel solves constraints as they are detected –Pre-sorted or binned data can be re-used during iterative constraint solving Narrow Ph.Broad PhaseResolution CD Kernel:

53 Dynamic asset generation in the Scalable City environment Assets, Dynamics and Behavior Computation for Virtual Worlds and Computer Games 53

54 Dynamic Land Modification Constrained Delaunay Triangulation 54

55 Dynamic Land Modification Constrained Delaunay Triangulation –Uses Dynamic mesh patching Fast mesh reduction of flat regions –Optimizations Geared to reduce copying with our internal data structures Parallelized across compute nodes. 55

56 Dynamic Land Modification Constrained Delaunay Triangulation –Divide & conquer approach, highly parallelizable –Multi-threaded version is significantly faster 56

57 Dynamic Land Modification 57

58 Dynamically Generated Avatars Exploring new sources and techniques for automatic avatar generation Current avatar made up of vehicles –3D structure generated from several photographs of each vehicle 58

59 Dynamically Generated Avatars Hand Avatars Extract Hand from video using Foreground Object Detection Map hand to 3D model Animate individual fingers into walking motion 59

60 Future Cinema As Augmented Reality Status: Revised Sponsors: IBM, Intel Potential Members – Sony and Qualcomm providing In-Kind support Deliverables: –Create New Approaches for Creating Augmented Reality. Major results –3D 4K movie produced and exhibited –Wins First Prize from Sony Europe. 60

61 Future Cinema As Augmented Reality Status: Revised 61

62 62 Future Cinema As Augmented Reality Status: Revised Architects have been “augmenting reality” for decades “Spatial City” Yona Friedman Hand-drawn sketch over photograph

63 63 Geodesic Dome over NYC Buckminster Fuller Collage over aerial photo Future Cinema As Augmented Reality Status: Revised

64 64 Contemporary mobile devices can do this in real time Future Cinema As Augmented Reality Status: Revised

65 65 Future Cinema As Augmented Reality Status: Revised User-created augmentations inserted into a real scene

66 66 Future Cinema As Augmented Reality Status: Revised Taking AR off the Desktop... Into the City building facades as computer-readable markers

67 67 Future Cinema As Augmented Reality Status: Revised Vision OnlySensors Only Both, but not at the same time Current Approaches Don’t Maximize the Devices’ Potential a hybrid approach Is needed! GPS doesn’t give pixel-perfect alignment Vision is slow and requires clear line- of-sight

68 68 Future Cinema As Augmented Reality Status: Revised Sensor Fusion Hybrid AR Is Inherently Multithreaded GPS/Sensor Processing 3D Graphics Rendering Network Communication That’s just about everything a modern mobile device can do! Computer Vision

69 69 Future Cinema As Augmented Reality Status: Revised

70 70 Future Cinema As Augmented Reality Status: Revised

71 71 Future Cinema As Augmented Reality Status: Revised Video:

72 User Behavior Patterns Status: Continuing Project Description: Analyze and predict user behavior in the virtual world to inform dynamic modifications to the environment to create a richer virtual experience. Research: Focus on responding to observed correlations of behaviors with: –State of the virtual world –Recent and future in-world events –Visual appearance of the world (user view) –Previous patterns in user input 72

73 User Behavior Patterns Support Complimentary grant support: NSF EAGER (EArly Grants for Exploratory Research): “Identifying and Integrating Creative Patterns of User Behavior and Experience in Virtual Worlds” Grant description: A new interdisciplinary methodology for both the analysis of user’s experiences in virtual worlds and the design of such worlds. It combines ideas from games design, computer science, information visualization, new media art and media theory. 73

74 User Behavior Patterns Support Grant description (continued): If successful, game designers, HCI researchers, and games and media scholars will be able to analyze, visualize and interpret the dimensions of user experiences with interactive time-based cultural artifacts such as video games, animated interfaces, and interactive artworks which are not captured with current analytics techniques. At the same time, by incorporating the new analytics techniques in virtual world generation software, the project aims to advance the current research on how to create interfaces and simulations which analyze user performance and dynamically adapt based on the results of the analysis. 74

75 User Behavior Patterns Background Present state of knowledge in virtual world analysis –network analysis (connectivity, load, latency) –econometrics on virtual economies –profiling player game play Primarily driven by game companies –during development (Microsoft Labs, Halo series) –for an ongoing MMOG (Blizzard, World of Warcraft) –over a game network service (Steam, Xbox Live) 75

76 User Behavior Patterns Methodology New methods: Cultural Analytics –“the use of computational methods for the analysis of patterns in visual and interactive media.” –Data mining, knowledge exploration, and information visualization as applied to cultural artifacts and experiences such as paintings, cartoons, or virtual worlds. Logging, visualizing, designing –Record events in the world and telemetry on the user –Visualize spatial, temporal, and narrative patterns –Explore mechanisms to dynamically accommodate behavior patterns in virtual world design 76

77 User Behavior Patterns Logging Event logging –Server-side code hooks fire when an event occurs –Events logged as time-stamped “triples” (subject-verb-object) Object / user interactions (Player1 activates Object5) World state changes User telemetry logging –Data is polled from client at set rate (1/sec) and logged on server User input (trackball direction, velocity) User avatar position / orientation User camera position / orientation / type 77

78 User Behavior Patterns Event Logging 78

79 User Behavior Patterns Event Logging 79

80 User Behavior Patterns 2D projection of virtual world coordinates 80 Logging data of user positions as tracked in abstract space

81 User Behavior Patterns 2D and 3D projection 81 Coordinate spaces for information visualization –Virtual world is computed and rendered on a complex 3D surface –2D projects are important to visual understanding –Example: 3D “box world”  2D “unfolded box” projection

82 User Behavior Patterns 2D and 3D projection 82 Coordinate spaces for information visualization –Automatically generated interactive animations and timelines for user paths through the virtual world space

83 User Behavior Patterns 2D and 3D projection 83 Coordinate spaces for information visualization –Multiple path views or overlays –Time-based trails with past- present-future coloring –“Heatmap” density overlay to indicate amount of time spent in each place –Spectral coloring to passage of time during player path without animation

84 User Behavior Patterns 2D and 3D projection 84 Coordinate spaces for information visualization –Interactive viewer –Multiple information overlays –Dynamically transform from one coordinate space to another

85 User Behavior Patterns Issues Challenge: exact replay of sessions from log data, or exact parallel playback in different visual modes –Client and network optimizations create special classes of synced vs. non-synced world objects and events –Each client sees the same world, yet a different world Particle systems Lag Precision Randomization Deducing implicit cause-effect relationships that aren’t modeled by the server –e.g. “The last user to touch it is the one that did it” 85


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