XLcloud: Remote rendering for games and 3D graphics applications in the cloud, OW2con'12, Paris, November 2012
- 1. Date to be set via "View/Header and Footer" Remote rendering for games and 3D graphics applications in the cloud Patrick Petit (Bull) Marius Preda (Telecom Sud Paris) OW2 Annual Conference 2012 (OW2con'12), November 27-29, 2012
- 2. Slide 2/7 Agenda of presentation Project Organization Key Tenets and Objectives Remote Rendering Principle Platform Logical Architecture
- 3. Slide 3/7 Project Organization Winner of Call for Projects #1 “Cloud Computing” by the FSN (5 projects selected nationwide) Project length: 36 months Official Start: 01/01/2012 Coordinator: Bull Open Source (Apache V2) http://gitorious.ow2.org/xlcloud http://xlcloud.org/ http://gitorious.ow2.org/xlcloud ATEME: H264/MPEG-4/AVC low latency compression algorithms Bull: cloud infrastructure, distributed systems architecture and HPC cluster CEA List: interactive simulation of natural phenomenons, virtual reality EISTI: marketplace, OpenERP integration Inria Reso: energy efficiency TSP (Lab Artemis): MPEG standardization, video compression, multimodality Silkan: massively distributed (HPC) software architecture for interactive simulation OW2: communication, dissemination
- 4. Slide 4/7 Key Tenets and Objectives Provide virtual cluster instances on-demand through self-service API and Web UI Point to point application latency (lag) < 200 ms (pipeline, capture/encode, network, decode, display) Standard compliance (Eg. SAML V2, OAuth 2.0, XACML) Layered and modular design to allow for seamless support of many types of applications and workloads (purpose-built PaaS computing environment) Policy-based Service Level Management (SLM) with automatic scale-up / scale-down Business applications integration framework for service composition and aggregation Secure multi-tenant environment (isolation, strong authentication and access control) Adaptation of the Cloud Management System to best leverage the underlying infrastructure performance (HPC cluster) Fine-grained resource usage metering and accounting for chargeback Energy efficient meaning produce the most output for the least cost
- 5. Scene analyzer User interaction Scene descriptio n Dat a AI Local Input Network parameters Remote Input Segmentation map Depth map Motion vectors Application Engine Scene Graph Rendering engine 2D/3D graphics Video Encoder Graphics Encoder RTP/UDP Packetizer Streamer Network ready packets Compressed stream Player Interactivity Terminal parameters Network Server Client Network How remote rendering works? Slide 5/7
- 6. Example of games played in Remote Rendering Slide 6/7
- 8. Thank you for your attention