As technology geometries have shrunk to the deep sub-micron (DSM) region, the chip density and clock frequency of FPGAs have increased significantly. This makes computer-aided design (CAD) for FPGAs very important and challenging. Due to the increasing demands of portable devices and mobile computing, low power design is crucial in CAD nowadays. In this dissertation, we present a framework to optimize power consumption for technology mapping onto FPGAs. We propose a low-power technology mapping scheme which is able to predict the impact of choosing a subnetwork covering on the ultimate mapping solution. We dynamically update the power estimation for a sequence of options and choose the one that yields the least power consumption. This technique outperforms the best low-power mapping algorithms reported in the literature. We further extend this work to generate mapping solutions with optimal delay. We also propose placement algorithms to optimize the performance of the placed circuit. Net cluster based methodology is designed to ensure closely connected nets will be routed in the same region. Net cluster is obtained by clique partitioning on the net dependency graph. Net positions and consequent cell positions are computed with a force-directed approach which drags nets connected to closer positions. We further study the performance-driven placement problem for high level synthesis. We use the Automatic Design Instantiation (AUDI) high level synthesis system to generate a register-transistor level (RTL) netlist. This RTL netlist is fed into a CAD tool for physical synthesis. We do not necessarily go through the entire physical design process which is usually quite time-consuming. Instead, we have created an accurate wirelength/timing estimator working on the floorplan. If the estimated timing information does not meet the constraints, a guidance is generated and provided to AUDI system. The guidance consists of the estimated timing information and instructions to produce a new netlist in order to improve the performance. Finally the circuit is placed and routed on a satisfying design. This performance-driven placement framework yields better results as compared to a commercial CAD tool.