Abstract

Abstract

Abstract
On a CPU-FPGA system, C/C++ applications are typically accelerated by offloading specific code regions onto the FPGA using High-level Synthesis (HLS). Although modern FPGAs can implement increasingly large and complex designs, the size and variety of potential offloading code regions remain constrained by the limitations of HLS tools (e.g., no support for dynamic memory allocation and system calls). This paper proposes automated C/C++ source-to-source transformations that tackle these limitations in two steps. Firstly, transformations reduce the entropy of an input C/C++ application by converting it into a subset of C, e.g., by flattening arrays and structs. Secondly, additional transformations make a selected code region synthesizable, e.g., by moving dynamic memory allocations out of the region, converting them to static memory, and offloading non-synthesizable C standard library calls, such as printf(), to the CPU. We evaluate the impact of these transformations showing results obtained through Vitis HLS for four real-world examples: the disparity and texture-synthesis benchmarks from CortexSuite, which contain dynamic memory allocations and indirect pointers in their hotspots; llama2, a Large Language Model that calls printf() every time it predicts a new word; and the spam-filter benchmark from Rosetta, as a debugging showcase. © 2025 IEEE.