Evaluating power and energy consumption of FPGA-based custom computing machines for scientific floating-point computation

This paper evaluates the actual power consumption and the total energy for scientific floating-point computations accelerated by FPGA-based custom computing machines. With our FPGA-based machines: the streaming accelerator for computational fluid dynamics and the programmable systolic-array processor for numerical simulations based on difference schemes, we measure the power of the entire systems including a host PC and an FPGA board, and obtain the total energy for each computation. We report that the FPGAs perform the same computation with 5% to 30% of the total energy consumed by a microprocessor, while the FPGAs accelerate the computation.