Optimizing data layout and system configuration on FPGA-based heterogeneous platforms

The most attractive feature of field-programmable gate arrays (FPGAs) is their configuration flexibility. However, if the configuration is performed manually, this flexibility places a heavy burden on system designers to choose among a vast number of configuration parameters and program transformations. In this paper, we improve the state-of-the-art with two main innovations: First, we apply compiler-automated transformations to the data layout and program statements to create streaming accesses. Such accesses are turned into streaming interfaces when the kernels are implemented in hardware, allowing the kernels to run efficiently. Second, we use two-step mixed integer programming to first minimize the execution time and then to minimize energy dissipation. Configuration parameters are chosen automatically, including several important ones omitted by existing models. Experimental results demonstrate significant performance gains and energy savings using these techniques. This work is sponsored in part by the National Science Foundation (Grant 1533822).