JOURNAL ARTICLE

A High Performance VLSI Computer Architecture For Computer Graphics

Chi-Yuan ChinWen-Tai Lin

Year: 1988 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 1001 Pages: 491-491   Publisher: SPIE

Abstract

A VLSI computer architecture, consisting of multiple processors, is presented in this paper to satisfy the modern computer graphics demands, e.g. high resolution, realistic animation, real-time display etc.. All processors share a global memory which are partitioned into multiple banks. Through a crossbar network, data from one memory bank can be broadcasted to many processors. Processors are physically interconnected through a hyper-crossbar network (a crossbar-like network). By programming the network, the topology of communication links among processors can be reconfigurated to satisfy specific dataflows of different applications. Each processor consists of a controller, arithmetic operators, local memory, a local crossbar network, and I/O ports to communicate with other processors, memory banks, and a system controller. Operations in each processor are characterized into two modes, i.e. object domain and space domain, to fully utilize the data-independency characteristics of graphics processing. Special graphics features such as 3D-to-2D conversion, shadow generation, texturing, and reflection, can be easily handled. With the current high density interconnection (MI) technology, it is feasible to implement a 64-processor system to achieve 2.5 billion operations per second, a performance needed in most advanced graphics applications.

Keywords:
Computer science Crossbar switch Very-large-scale integration Graphics Computer architecture Computer hardware Parallel computing Embedded system Computer graphics (images)

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Topics

Interconnection Networks and Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
CCD and CMOS Imaging Sensors
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Digital Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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