Dynamic software optimization methods are becoming increasingly popular for improving software performance and power. The first step in dynamic optimization consists of detecting frequently executed code, or "critical regions." Most previous critical region detectors have been targeted to desktop processors. We introduce a critical region detector targeted to embedded processors, with the unique features of being very size and power efficient and being completely nonintrusive to the software's execution-features needed in timing-sensitive embedded systems. Our detector not only finds the critical regions, but also determines their relative frequencies, a potentially important feature for selecting among alternative dynamic optimization methods. Our detector uses a tiny cache-like structure coupled with a small amount of logic. We provide results of extensive explorations across 19 embedded system benchmarks. We show that highly accurate results can be achieved with only a 0.02 percent power overhead, acceptable size overhead; and zero runtime overhead. Our detector is currently being used as part of a dynamic hardware/software partitioning approach, but is applicable to a wide variety of situations.
['Ann Gordon-Ross', 'Frank Vahid']
Frequent loop detection using efficient nonintrusive on-chip hardware