Supercomputers are coming into wider use for generating realistic imagery for commercial animation, special effects, and scientific simulation. The Connection Machine requires a more radical rethinking of rendering algorithms than previous supercomputers since it is not intended to function as a scalar processor. A fascinating mix of changes from conventional approaches is emerging. Some procedures can run virtually unchanged while others must be turned completely inside out. We have confidence in the viability of the Connection Machine as an architecture for high-end computer graphics. For complex scenes resulting in at least tens of thousands of polygons per frame, most steps of the rendering pipeline can make effective use of the massive number of processors available. Early approaches to massively parallel graphics systems have focused on processor per pixel organizations. We show that a dynamic mix of organizations, including processor per pixel, processor per vertex, and processor per polygon are necessary. Additionally, we note that an apparent consequence of the style of algorithm enforced by the Connection Machine is an enormously increased appetite for memory. We explore standard algorithms for image generation and note the differences that arise in an implementation for the Connetion Machine. We conclude by attempting a comparison of the viability of alternative computing environments for our application.