GPU evolution

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In the last several years GPU devices have started to evolve into supercomputers. New, non-graphics, features are rapidly appearing along with new more general programming languages. One reason for the quick pace of change is that, games and hardware evolve together: Hardware vendors review the most popular games, looking for places to add hardware while game developers review new hardware, looking for places to add more realism. Today, we see both GPU devices and games moving from a model of looks real to one of acts real. One consequence of acts real is that evaluating physics, simulations, and artificial intelligence on a GPU is becoming an element of future game programs. We will review the difference between a CPU and a GPU. Then we will describe hardware changes added to the current generation of AMD graphics processors, including the introduction of traditional compute operations such as double precision, scatter/gather and local memory. Along with new features, we have added new metrics like performance/watt and performance/dollar. The current AMD GPU processor delivers 9 gigaflops/watt and 5 gigaflops/dollar. For the last two generations, each AMD GPU has provided double the performance/watt of the prior machine. We believe the software community needs to become more aware and appreciate these metrics.Because this has been a kind of co-evolution and not a process of radical change, current GPU devices have retained a number of odd sounding transitional features, including fixed functions like memory systems that can do filtering, depth buffers, a rasterizer and the like. Today, each of these remain because they are important for graphics performance. Software on GPU devices also shows transitional features. As AI/physics virtual reality starts to become important, development frameworks have started to shift. Graphics APIs have added compute shaders. Finally, there has been a set of transitional programs implemented by graphics programmers but whose only real connection with graphics is that the result is rendered. One early example is toy shop which contains a weak physical simulation of rain on window (it looks great but the random number generator would not pass any kind of test). A more recent and better acting program is March of the Froblins an AI program related to robotic path calculations. This program both simulates large crowds of independent creatures and shows how massively parallel compute can benefit character-centric entertainment.