As technology scales further, multicore and many-core processors emerge as an alternative to keep up with performance demands. However, because of power and thermal constraints, we are obliged to power off remarkable area of chip. Many innovative techniques have been presented to improve energy efficiency and maintain utilization at the highest level. In this paper, we discuss different models and methods of exploiting dark silicon, and by using dynamic voltage and frequency scaling in Amdahl's law and considering memory overheads, we attempt to decrease amount of dark silicon and improve performance and performance per watt/joule. We propose high-performance and energy-efficient multicore architectures for variety of parallelisms and memory-intensities in workloads. According to the results, by voltage scaling, for a highly parallel CPU-intensive workload, we reach improvements of approximately 5.2× and 3.78× in performance per watt and performance per joule, respectively, while about 27 % reduction of performance should be tolerated. For memory-intensive applications, a negligible change in speedup is detected by scaling, while performance per watt and performance per joule for both serial and parallel applications lead to around 6× enhancements.