Low-power, high-performance computing nowadays relies on accelerator cards to speed up the calculations. Combining the power of GPUs with the flexibility of FPGAs enlarges the scope of problems that can be accelerated. We describe the performance analysis of a desktop equipped with a GPU Tesla 2050 and an FPGA Virtex- 6 LX 240T. The balance between the I/O and the raw peak performance is analyzed using the roofline model. A well-tuned accelerator- based codesign, identifying the parallelism, the computation and data patterns of different classes of algorithms, will enable to maximize the performance of the combined GPU/FPGA system.