Is there a tradeoff between programmability and performance?

While the computational power of Field Programmable Gate Arrays (FPGA) makes them attractive as code accelerators, the lack of high-level language programming tools is a major obstacle to their wider use. Graphics Processing Units (GPUs), on the other hand, have benefitted from advanced and widely used high-level programming tools. This paper evaluates the performance, throughput and energy of both FPGAs and GPUs on image processing codes using high-level language programming tools for both.