In this paper, we present a multi-FPGA graph processing framework and an accompanying performance model. Our framework emphasizes programmability, requiring minimal user input beyond providing the application kernel and the dataset. The framework predicts the performance of the system based on the algorithm characteristics and problem size and automatically selects the optimal FPGA configuration. We implement our system on an experimental 4-FPGA platform and compare the results to the predicted performance.