Control independence has been put forward as a significant new source of instruction-level parallelism for future generation processors. However, its performance potential under practical hardware constraints is not known, and even less is understood about the factors that contribute to or limit the performance of control independence. Important aspects of control independence are identified and singled out for study, and a series of idealized machine models are used to isolate and evaluate these aspects. It is shown that much of the performance potential of control independence is lost due to data dependences and wasted resources consumed by incorrect control dependent instructions. Even so, control independence can close the performance gap between real and perfect branch prediction by as much as half. Next, important implementation issues are discussed and some design alternatives are given. This is followed by a more detailed set of simulations, where the key implementation featur...
Eric Rotenberg, Quinn Jacobson, James E. Smith