一句话：针对 FPGA HLS 难以支持含指针、内存管理和递归的内核程序，提出自动重构以提升 HLS 兼容性并减少手工优化。
FPGA 异构计算能为许多应用带来数量级的能效提升，但硬件知识门槛使使用者受限。高层综合（HLS）将编程抽象从硬件语言提升到 C/C++，却通常无法编译和生成含指针、内存管理与递归的内核加速器，需要人工重构才能兼容 HLS。此外，专家还需大量手工优化以提高资源效率，这影响最高运行频率、并行化和功耗效率。论文 HeteroRefactor 针对这些限制，探索自动重构以降低 HLS 使用门槛并减少手工优化负担；给定摘要未展开具体方法与实验评估。
Heterogeneous computing with field-programmable gate-arrays (FPGAs) has demonstrated orders of magnitude improvement in computing efficiency for many applications. However, the use of such platforms so far is limited to a small subset of programmers with specialized hardware knowledge. High-level synthesis (HLS) tools made significant progress in raising the level of programming abstraction from hardware programming languages to C/C++, but they usually cannot compile and generate accelerators for kernel programs with pointers, memory management, and recursion, and require manual refactoring to make them HLS-compatible. Besides, experts also need to provide heavily handcrafted optimizations to improve resource efficiency, which affects the maximum operating frequency, parallelization, and power efficiency.