Abstract
Real-time Power Consumption in an embedded system is an important reference information that to optimize endurance and real-time performance. We use measurement-based power profiler to directly measure the actual power consumption, and also allows software developers to know the actual power consumption when their programs are executed. So that more effective power optimization can be done. So I adopt the real-time power the measurements of an embedded system [1] as our power measurement platform and make some improvements. First, we add API to let software can start/stop the function to measure power. However, the software time and power measurement system time are not synchronized, so that the time when power measurement measure power is not exactly the time when software issues the start command. So we proposed a synchronous model in which latency between driver to power measurement system is compensated. Our experiments show that the latency is constant between driver to power measurement system. Furthermore, because not all power consumption information is meaningful for us and only certain characteristic are useful. We apply the compressive sensing (CS) compression to compress power data. However, CS work well to sparse signals. But not all power signals are sparse. Besides, CS have to do IDCT which result in software overhead. Therefore, we proposed template- based compression to replace CS. The experimental results show that in most cases template-based compression ratio (CR) better than CS compression ratio. Finally, we combine CS with template- based compression to compress power signals and use power measurement for cpu executing 6 benchmarks. The experimental results show that in 6 cases CR is not above 0.1 when acceptable relative error rate is 15%. In 5 cases CR is not above 0.2 acceptable relative error rate is 10%. We use power measurement for memory executing 5 benchmarks. The experimental results show that in 5 cases CR is not above 0.3 when acceptable relative error rate is 15%. In 5 cases CR is not above 0.4 acceptable relative error rate is 10%. Finally, we compared CS with template-based 1software overhead. The experimental results show that template-based software overhead less than CS.