> Leaving data in GPU memory as long as possible between kernel invocations and avoiding transfers is one of the first optimizations that must be considered. T

> Leaving data in GPU memory as long as possible between kernel invocations and avoiding transfers is one of the first optimizations that must be considered. The absolute biggest bottleneck when doing anything with the GPU is the cost of transferring between the CPU and GPU. Thus, the more you do on the GPU at a time, the better off you are. Obviously, there are many things to optimize on the GPU side (e.g. taking advantage of locality), but if you just keep in mind that the more you do, the faster things are, you're going to be in a good place.