Hardware platforms for computer graphics visualization F. Gareeboo Datapath Ltd., Alfreton Rd., Derby DE2 4AD,

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1 Hardware platforms for computer graphics visualization F. Gareeboo Datapath Ltd., Alfreton Rd., Derby DE2 4AD, UK ABSTRACT The purpose of this paper is to present the hardware platforms currently used at various levels for computer graphics visualization. The main parameters that characterize the different hardware platforms are described and methods explored to help in the selection of the most appropriate platform for particular visualisation tasks. The paper concludes with a methodology for the selection of appropriate hardware platforms for visualization. INTRODUCTION Visualization embraces both image understanding and image synthesis. That is visualisation is a tool both for interpreting image data fed into a computer, and for generating images from complex multi-dimensional data sets. It studies those mechanisms in humans and computers which allow them in concert to perceive, use and communicate visual information. Visualization unifies the largely independent but convergent fields of computer graphics, image processing, computer vision, computer-aided design, signal processing and user interface studies. McCormick et al [3]

2 282 Visualization and Intelligent Design History. Computer visualization probably started in 1950s, with the use of point-display screen on the MIT Whirlwind computer. The seminal work in the field was Ivan Sutherland's 1963 Ph.D dissertation 'Sketchpad'. In the mid 1960s, CRT displays were expensive ($50,000 - $100,000) but in 1968 Tektronix launched an inexpensive graphics terminal which encouraged expansion of the market. In the 1980s, the emergence of raster displays (as opposed to the previous generation of displays which was vector based) led to even cheaper solutions and further expansion of the market Since the publication of the NSF Panel on Graphics, Image Processing and Workstations report "Visualization in Scientific Computing", there has been a very high level of interest in both the computer industry and the user community in Visualization. Some current uses of computer visualization are : Discipline Planetary Science Pharmacology Mathematics Medicine Science in general Use by NASA JPL to accurately define optimal flight paths and camera positions of spacecraft. Dmg Design Fractals, Iterated Function Systems Volume visualization in diagnostic radiology To help define, compute and analyze simulations Table 1. Uses of Computer Visualization

3 Visualization and Intelligent Design 283 VISUALIZATION PROCESSES An understanding of the processes used to achieve computer visualization is vital for developing an appreciation of hardware requirements. ^Database V-^f Image CreationV>T Image Display! I Software User Interface Figure 1. Main components of a visualisation system. In this paper, we focus on the image creation and image display parts of the process. Simple Raster Display system In the most common type of display system (Figure 2), the image is created from a 'Raster', consisting of a matrix of pixels representing the entire screen. The matrix is scanned by the video controller sequentially from top to bottom (displaying the image concurrently on the monitor) continuously. (The number of times per second that the whole raster is scanned by the video controller is called the refresh rate). VIDEO BUFFER MAIN COMPUTER I DISPLAY CONTRO- LLER H I VIDEO CONTRO LLER T: Figure 2. A Raster display system

4 284 Visualization and Intelligent Design Table 2 below lists the main characteristics of raster display systems. Parameter Resolution Refresh rate Colours Description Greater resolution of the display allows you to see more detail. However, it also requires more expensive hardware and monitors. Typical resolutions of PCs for example is 640x480 (VGA), but 1280 x 1024 is more commonly used for visualization. For a static picture, the human eye requires a refresh rate of 70 frames per second to avoid eye strain due to screen flicker. Number of colours displayed varies between 16 to 16.7 million. This is an important parameter for volume visualisations, because of the use of colour and intensity to represent data variables. Table 2. Main characteristics of raster display systems. There are a number of different types of visualization; as listed in Table 3 below. Visualization type 2D lines 3D lines 3D shaded 3D rendered Volume Description Uses only 2 dimensional lines Uses 3 dimensional lines Displays 3D shaded objects/scenes Displays 'realistic' 3D objects/scenes uses textures, transparencies, etc Displays contents of 3D objects; not just surface. Table 3. Tvnes of Visualization

5 Visualization and Intelligent Design 285 Different processes are used to create the image in the video buffer, depending on the type of visualization being used. For example, for 3D shaded and 3D rendered visualization, Table 4 below illustrates the stages in the image creation process. ( The cost of each stage is characterized in terms of operations per vertex. 3D shading and rendering is typically applied to a collection of 3D polygons. See Foley,Van Dam,Feiner & Hughes [1] for more details.) Image Creation Stage Operations/ vertex. Database Traversal Modeling Transformation 25 x; 18 + Trivial Culling 18 x; 14 + Lighting 12x;5 + Viewing Transform 8 x; 6 + Clipping Perspective Transform 2 x; 2 +; 3 / Rasterization Table 4. The Image Creation Process The end result of the image generation process is a 'picture' in the display buffer. Using a simple PC, it is technically possible to generate images of unlimited complexity and realism given enough time (and memory). However, computer visualization is no longer a practical option if it takes too long to generate the visuals ( the length of time that is 'too long' depends on a number of factors eg importance of visualization, seniority of user, etc ).

6 286 Visualization and Intelligent Design The three main bottlenecks in the image generation process are Stages 2-6 require extensive Floating-point processing. This is measured in MFLOPS (Million Floating point Operations Per Second). Most common hardware platforms have low MFlops ratings compared to MIPS rating. Stage 8 requires extensive Integer Pixel processing capability. This is a function of the Mips rating of the hardware. After Stage 7, we start to write the pixels that compose the picture into the display buffer. The Video-buffer memory bandwidth limits the speed at which the 'picture' can be composed. The performance of a visualization system can be improved by using: display processors, which are specialised for displaying graphics, integrated processors, which are general purpose processors with integrated support for graphics operations, multiple processors; and splitting the graphics tasks between them using pipelining or parallelism.

7 Visualization and Intelligent Design 287 A display processor (eg TI34020) is an inexpensive method of increasing the display performance of a system. Increased performance is achieved by purchasing a 'plug-in expansion card'. An integrated processor (eg Intel i860 which supports 3D graphics) is a more expensive option, but delivers a much higher performance. The most expensive option, (and highest performing) is the use of multiple processors (specialised or general purpose) for processing the visuals. The last two options usually require the purchase of complete high-performance visualization workstations. (Except for the Merlin plug-in card which uses the i860 as a display processor). HARDWARE PLATFORMS CHARACTERIZED The previous sections of this paper outlined the types of visualization currently used, and the processes used to implement them. We also looked at the performance bottlenecks in the visualization process, and hardware solutions to those performance problems. In this section, we look at the hardware platforms currently available and their suitability for computer visualization. Hardware platforms are usually characterized by their manufacturers in terms of peak processing power expressed in MIPS, MFLOPS, etc. Those figures can only hint at the visualization potential of those platforms, since a number of crucial layers come between the raw hardware performance, and visualization power: implementation of graphics libraries that use the hardware power to the maximum, and, availability of suitable software to perform visualization

8 288 Visualization and Intelligent Design To have a feel for the performance requirements, we look at a number of typical drawings (I choose some models shipped with AutoCAD as examples). Table 5 below lists some of those models, and the number of lines and number of triangles that they are made up of. Model Lines Triangles Airplane Site-3D Hook Table 5. Some typical models and sizes A medium complexity data set has of the order of lines/triangles. On average, the lines may be assumed to be 10 pixels long, and the triangles to have an area of 100 pixels. To display different views of this data set in real time (10 updates per second) would require performance of the order indicated in Table 6 below. WireFrame Smooth Shading 15 MFLOPS 34 MFLOPS 5 MIPS 33 MIPS 2MFBAS 51MFBAS Table 6. Performance required to visualize average model (MFBAS stands for Million Frame Buffer Accesses per Second) Table 7 below lists some of the currently available hardware platforms and their performance characteristics. The table lists only the Mips, Mflops ratings.

9 Visualization and Intelligent Design 289 Platform Mips M flops IBM PC 48650MHz 40 3 Merlin (i860) Mac (Quadra 950) Next Sun-SparcSation 10 Model SG (Indigo R4000) HP9000/ Other platforms : Tektronix, Evans and Sutherland,Convex,Stellar, Cray Table 7. Characteristics of Current Platforms As can be seen from Table 7 above, current 'low-cost' platforms can deliver reasonable solutions for 2D and 3D wireframe visualization. However, for 3D shading, rendering and volume visualisation, the cost of adequate hardware platforms starts to rise dramatically. Apart from raw graphics performance, there are a number of characteristics of hardware platforms that are relevant for visualization. These are listed below :- Display quality - Resolution and refresh rates. These characteristics are defined earlier. For adequate visualization, the minimum requirements are 1024 x 768 resolution, and 72Hz refresh rate.

10 290 Visualization and Intelligent Design Openness of the system. This is an important consideration to safeguard any software development investment that you may have to make in the system. The issue of openness can be considered at various levels; hardware : eg use of industry standard bus architecture like ISA,EISA,VL, VME,etc.. operating system : use of 'industry standard* operating system; POSIX compliance. Graphics API : use of standard Application Programming interface to display graphics (eg PfflGS3D,PEX,GL) Connectivity The ability to connect to other Identical* stations, or different ones electronically is an important consideration. This may be particularly important if the visualization facilities are to be made available to a large number of users, and if the data is generated from another station and need to be viewed in 'real-time'. Software solution - Features The visualization hardware on its own is completely useless without usable software that gives you access to the functionality (unless you are prepared to develop your own visualization software). Video compatible computers The ability to record the visualization sequence(s) onto video tape is of relevance to a number of applications.

11 Visualization and Intelligent Design 291 SELECTION OF HARDWARE PLATFORM The first step in the selection of a hardware platform for Computer Visualization (and for any other application for that matter) is a precise definition of your requirements. These must include the data, the form(s) of output, functionality, ease of use, support, upgrade paths, and budget. Visualization Software Most of the requirements are satisfied by the software component(s) of the system rather that the hardware. See Appendix A for a list of commonly available visualization software, and reference 4 for an evaluation of some of them. In most scenarios, the need for visualization arises after the user has already made significant investments in hardware, so that the search for appropriate software that runs on existing machine is the most important task. In fact, the origination of some of the current crop of visualization software from Academia means that some of them (eg Khoros) are available free of charge. When there is an opportunity to pick both the software and a new hardware platform, some of your requirements may have important implications for the hardware platform (See Table 8 on the following page).

12 292 Visualization and Intelligent Design ITEM ASPECT IMPLICATION Data Origineg on Tape Format Tape drive Is it readable by platform? Real-time Network, HIPPI channel Size Hard-disk size Memory size Output Type Update speed Hardcopy Video Raw performance Performance Driver for hardcopy device Video interface Budget Tightness Prevents us from getting what we really want! Table 8. Reauirements and hardware implications

13 Visualization and Intelligent Design 293 FUTURES The nature of the computing industry is such that the future holds out some very exciting prospects. For example, more powerful chip-sets allowing better price-performance ratios are being announced now, and we can look forward to desktop stations of 8,000 with a rating of 200 MIPS and 100MFLOPS by the middle-end of next year. (A MHz and Merlin currently delivers 80MIPS and 80MFLOPS for 8,000). This will, for example, allow volume visualization (the most processor intensive type) on an affordable desktop platform. New and exotic displays and input devices are also appearing over the horizon. For example, Deering[7] describes a 3D holographies station integrated with a 3D pointing device in his paper on "High resolution Virtual Reality". Stereoscopic specs are also available from a number of manufacturers. The physical display side of Visualization has now seen as much change as for example the hardware processors, but this may change soon with better LCD technology.

14 294 Visualization and Intelligent Design REFERENCES 1. Foley James D., van Dam Andries, Feiner Steven K., Hughes John K. Computer Graphics Principles and Practice. Addison- Wesley Defanti Thomas A, Brown Maxine D. Visualization in Scientific Computing. Advances in Computing Vol McCormick, B.H., DeFanti, T.A. and Brown, M.D., eds Visualization in Scientific computing. Computer Graphics 20 (6) (1987). 4. Advisory Group on Computer Graphics Technical Report Series, Evaluation of Visualization Systems No 9, May Rae A. Earnshaw (Ed) Fundamental Algorithms for Computer Graphics, Springer-Verlag (Section 6 - Hardware Architecture and Algorithms) Ian Hirschsohn, Personal Supercomputing,Dr. Dobb's Journal, June Michael Deering, High Resolution Virtual Reality, SIGGRAPH '92.

15 Visualization and Intelligent Design 295 APPENDIX A List of currently available visualization software and graphics libraries. Alias's 3D software AVS MOVIE.BYU DISSPLA PC-MGL H Visualization Data Explorer AVS Inc. Brigham Young University. Computer Associates. Datapath Ltd. IBM. PHIGS+ RenderMan and CubeTool PV-WAVE Iris Explorer Open GL DORE MatLab ape FIGARO Khoros Pixar. Precision Visuals. Silicon Graphics. Silicon Graphics. Stardent. Stardent. TaraVisual Corporation. Template Graphics System. University of New Mexico. Wavefront Techology. Mathematica Wolfram Associates.