A High-Performance Scalable Graphics Architecture Daniel R. McLachlan Director, Advanced Graphics Engineering SGI

Growth in Model Sizes Worldwide Production of Information Exabytes Source: Gartner Images courtesy of Parametric Technology Corporation; Photodisc, and Magic Earth, LLC

Problems Are Getting Increasingly Complex Over Time Bumper Bumper, hood, engine, wheelsEntire car Crash dummy Organ damage E-crash dummy Images courtesy of EAI; SCI Institute, NLM, Theoretical Biophysics Group of the Beckman Institute at UIUC; Livermore Software Technology Corporation

The Complexity of the Simple Images courtesy of Procter & Gamble Potato Chips Diapers

Graphic Cards Are Outpacing PC Architecture and Bandwidth Performance Gap Graph based on relative scale.

Performance 2003 Visualization Low cost Fast simple polygons Single screen image quality 1992 Extreme resolution Absolute visual quality VAN Solving complex problems Dense data sets Visualization Breaks The Cognitive Barrier For Better Decisions Addressing Real Needs Images courtesy of Advantage CFD; SCI institute; NLM; Theoretical Biophysics Group of the Beckman Institute at UIUC; Laboratory for Atmospheres, NASA Goddard Space Flight Center; Donghoon Shin, Art Center College of Design, Nvidia Corporation; ATI Technologies, Inc; and Nintendo Co., Ltd. Clusters Graphics

Cluster Comparison Pros Cheap Industry standard High display list performance Good for “embarrassingly parallel” problems Can potentially scale to 1000s of processors Cons Cumbersome to program High administration costs Few applications for visualization Difficult to scale for large problems Difficult to dynamically load balance Lack of software productivity tools Often requires data replication Reliability Limited to 2GB memory space

Traditional Clusters SGI ® NUMAflex™ node + OS... Fast NUMAflex™ interconnect Global shared memory node + OS... Commodity interconnect mem node + OS node + OS node + OS node + OS node + OS node + OS node + OS node + OS What is shared memory? All nodes operate on one large shared memory space, instead of each node having its own small memory space Shared memory is high-performance All nodes can access one large memory space efficiently, so complex communication and data passing between nodes aren’t needed Big data sets fit entirely in memory; less disk I/O is needed Shared memory is cost-effective and easy to deploy It requires less memory per node, because large problems can be solved in big shared memory Simpler programming means lower tuning and maintenance costs The Benefits of Shared Memory 1-2 CPUs per node < 64 CPUs per node

How SGI ® Onyx ® Enables the Role System at a Glance Scalable Graphics I/O Scalable Disk I/OScalable Resolution Appropriate Delivery Scalable Rendering Scalable Data CompositorNetworkCompositorNetwork Scalable Graphics Scalable Compute and Large Memory SGI Onyx Large Data Sets Scalable Interaction

Moving from a fixed rendering path… Images courtesy of Pratt and Whitney Canada and Magic Earth, LLC …to a scalable and programmable rendering path. Application accelerators Geometry Silicon Graphics ® Onyx4™ UltimateVision™ Changing the Application Paradigm

Scaling A Shift in Pipe Paradigm 3. Time-based decomposition Even more powerful in combination All modes can be used separately or combined in any number of ways Data courtesy of DaimlerChrysler, Images courtesy of MAK Visible Human public data set 1. Screen-based decomposition 2. Eye-based decomposition 4. Data-based decomposition

Multi-Tier Composition Composite output of multiple compositors e.g., first layer does 2D composition, second layer does anti-aliasing Visual Serving Composited output sent to workstations for viewing and/or editing Compositor Flexibility

Silicon Graphics ® Onyx4™ UltimateVision™ System Architecture 2 Graphics Pipes CPU 8GB RAM Memory Controller Memory Controller SGI ® NUMA scalability Standard I/O or 2 Graphics Pipes Optional

Silicon Graphics ® Onyx4™ UltimateVision™ Solving bigger and more complex problems World’s most scalable visualization system Up to 32 GPUs in an SSI architecture World-leading computational capability Up to 64 CPUs per node, scalable to 1024 processors Solves system b/w limitations of PCs and clusters Up to 8 NUMAlink 3 connections to a single shared memory pool New-generation programmable graphics architecture OpenGL Shading Language Conclusion