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In computer science, performance prediction means to estimate the execution time or other performance factors (such as cache misses) of a program on a given computer. It is being widely used for computer architects to evaluate new computer designs, for compiler writers to explore new optimizations, and also for advanced developers to tune their programs. There are many approaches to predict program 's performance on computers. They can be roughly divided into three major categories: * simulation-based prediction * profile-based prediction * analytical modeling ==Simulation-based prediction== Performance data can be directly obtained from computer simulators, within which each instruction of the target program is actually dynamically executed given a particular input data set. Simulators can predict program's performance very accurately, but takes considerable time to handle large programs. Examples include the (PACE ) and (Wisconsin Wind Tunnel ) simulators as well as the more recent (WARPP ) simulation toolkit which attempts to significantly reduce the time required for parallel system simulation. Another approach, based on trace-based simulation does not run every instruction, but runs a trace file which store important program events only. This approach loses some flexibility and accuracy compared to cycle-accurate simulation mentioned above but can be much faster. The generation of traces often consumes considerable amounts of storage space and can severely impact the runtime of applications if large amount of data are recorded during execution. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「performance prediction」の詳細全文を読む スポンサード リンク
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