...
*Jaw drops to floor* Do you have any idea what you're talking about?
Sure, physics as used in gaming.
Physics calculation in gaming(collison, force, acceleration, displacement, etc) involves a fair amount of both scalar quanity and vector quanity, and conversion in bewteen.
I see that you will gain certain acceleration in vector dot product with dedicated dot product instructions, but they make up a relatively small percentage of overall calculations. Whereas T&L is almost all dot product, physics is not as dot product heavy and the computational acceleration gained from dot product is comparatively small.
In addition, there is another reason IBM shuns VFPUs in its designs. For a typical VFPU implementation, the speed gain observed over a comparable scalar FPU implementation is 2X. IBM implements a dualFPU architecture plus good load/store units to keep the FPUs going, so that the speed difference between a four-way VFPU and its dual FPUs is kept to minimum. A VFPU must be coded in assembly or in custom library, while dualFPUs can be coded in straight C++. This is why IBM insists on dualFPUs over VectorFPUs for its high end and even supercomputer applications.
IBM dual FPU scalar processors CAN ALMOST MATCH dedicated VFPUs in sustained vector computation, and this is why MS can safely drop Altivec without a performance penalty.
And AI? (I know you didn't say AI, but I'll mention it anyways). If the game uses any form of adaptive weighted decision network (neural networks, or other learning systems), the ENTIRE PREMISE of the AI is based on dot products.
I only learned the recursive solving of a weighted network. Sorry.