Component overclocking is an effective approach to speed up the components of a system to realize a higher program performance; it includes processor overclocking or memory overclocking. However, overclocking will unavoidably result in increase in power consumption. Our goal is to optimally improve the performance of scientific computing applications without increasing the total power consumption for a processor-memory system. We built a processor-memory energy efficiency model for multicore-based systems, which coordinates the performance and power of processor and memory. Our model exploits performance boost opportunities for a processor-memory system by adopting processor overclocking, processor Dynamic Voltage and Frequency Scaling (DVFS), memory active ratio adjustment, and memory overclocking, according to different scientific applications. This model also provides a total power control method by considering the same four factors mentioned above. We propose a processor and memory Coordination-based holistic Energy-Efficient (CEE) algorithm, which achieves performance improvement without increasing the total power consumption. The experimental results show that an average of 9.3% performance improvement was obtained for all 14 benchmarks. Meanwhile the total power consumption does not increase. The maximal performance improvement was up to 13.1% from dedup benchmark. Our experiments validate the effectiveness of our holistic energy-efficient model and technology.