This paper presents a many-core visual computing architecture code named Larrabee, a new software rendering pipeline, a manycore programming model, and performance analysis for several applications. Larrabee uses multiple in-order x86 CPU cores that are augmented by a wide vector processor unit, as well as some fixed function logic blocks. This provides dramatically higher performance per watt and per unit of area than out-of-order CPUs on highly parallel workloads. It also greatly increases the flexibility and programmability of the architecture as compared to standard GPUs. A coherent on-die 2nd level cache allows efficient inter-processor communication and high-bandwidth local data access by CPU cores. Task scheduling is performed entirely with software in Larrabee, rather than in fixed function logic. The customizable software graphics rendering pipeline for this architecture uses binning in order to reduce required memory bandwidth, minimize lock contention, and increase opportunities for parallelism relative to standard GPUs. The Larrabee native programming model supports a variety of highly parallel applications that use irregular data structures. Performance analysis on those applications demonstrates Larrabee's potential for a broad range of parallel computation.

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Larrabee: a many-core x86 architecture for visual computing

We describe initial results which show “live” ultrasound echography data visualized within a pregnant human subject. The visualization is achieved by using a small video camera mounted in front of a conventional head-mounted display worn by an observer. The camera’s video images are composite with computer-generated ones that contain one or more 2D ultrasound images properly transformed to the observer’s current viewing position. As the observer walks around the subject. the ultrasound images appear stationary in 3-space within the subject. This kind of enhancement of the observer’s vision may have many other applications, e.g., image guided surgical procedures and on location 3D interactive architecture preview. CR Categories: 1.3.7 [Three-Dimensional Graphics and Realism] Virtual Reality, 1,3.I [Hardware architecture]: Three-dimensional displays, 1.3.6 [Methodology and Techniques]: Interaction techniques, J.3 ILife and Medical Sciences]: Medical information systems. Additional

Merging virtual objects with the real world: seeing ultrasound imagery within the patient

We describe a classification scheme that we believe provides a more structured framework for reasoning about parallel rendering. The scheme is based on where the sort from object coordinates to screen coordinates occurs, which we believe is fundamental whenever both geometry processing and rasterization are performed in parallel. This classification scheme supports the analysis of computational and communication costs, and encompasses the bulk of current and proposed highly parallel renderers - both hardware and software. We begin by reviewing the standard feed-forward rendering pipeline, showing how different ways of parallelizing it lead to three classes of rendering algorithms. Next, we consider each of these classes in detail, analyzing their aggregate processing and communication costs, possible variations, and constraints they may impose on rendering applications. Finally, we use these analyses to compare the classes and identify when each is likely to be preferable. >

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A sorting classification of parallel rendering

We describe PixelFlow, an architecture for high-speed image generation that overcomes the transformationand frame-buffer– access bottlenecks of conventional hardware rendering architectures. PixelFlow uses the technique of image composition: it distributes the rendering task over an array of identical renderers, each of which computes a fill-screen image of a fraction of the primitives. A high-performance image-composition network composites these images in real time to produce an image of the entire scene. Image-composition architectures offer performance that scales linearly with the number of renderers; there is no fundamental limit to the maximum performance achievable using this approach. A single PixelFlow renderer rasterizes up to 1.4 million triangles per second, and an n-renderer system can rasterize at up to n times this basic rate. PixelFlow performs antialiasing by supersampling. It supports defemed shading with separate hardware shaders that operate on composite images containing intermediate pixel data. PixelFlow shaders compute complex shading algorithms and procedural and image-based textures in real-time. The shading rate is independent of scene complexity. A Pixel Flow system can be coupled to a parallel supercomputer to serve as an immediatemode graphics server, or it can maintain a display list for retainedmode rendering. The PixelFlow design has been simulated extensively at high level. Custom chip design is underway. We anticipate a working system by late 1993. CR

/pdf/pixelflow-high-speed-rendering-using-image-composition-16abtykuw5.pdf

PixelFlow: high-speed rendering using image composition

3dm is a three dimensional (3D) surface modeling program that draws techniques of model manipulation from both CAD and drawing programs and applies them to modeling in an intuitive way. 3dm uses a head-mounted display (HMD) to simplify the problem of 3D model manipulation and understanding. A HMD places the user in the modeling space, making three dimensional relationships more understandable. As a result, 3dm is easy to learn how to use and encourages experimentation with model shapes.

3DM: a three dimensional modeler using a head-mounted display

This paper introduces the architecture and initial algorithms for Pixel-Planes 5, a heterogeneous multi-computer designed both for high-speed polygon and sphere rendering (1M Phong-shaded triangles...

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Pixel-planes 5: a heterogeneous multiprocessor graphics system using processor-enhanced memories