Flexible High-Level Synthesis Library for Linear Transformations

Despite decades pursuing efficient hardware design for signal processing based on linear algebra, traditional hardware description languages (HDLs)-based design workflows remain challenging and time-consuming. High-level synthesis (HLS) provides an easier approach but still requires thorough designs of basic modules concerning linear transformations to achieve acceptable hardware efficiency. To simplify the HLS workflow, we propose the FLAMES library, which provides efficient ready-to-use linear transformation modules. Users can implement algorithms with significantly higher code-writing efficiency via the FLAMES library. We demonstrate its effectiveness by implementing the orthogonal matching pursuit list (OMPL) algorithm for compressed sensing in FPGA, achieving 1.56× and 1.12× throughput/slice compared with traditional HLS for the sequential and parallel architecture, respectively.