FPGA-based accelerators are increasingly popular across a broad range of applications, because they offer massive parallelism, high energy efficiency, and great flexibility for customizations. However, difficulties in programming and integrating FPGAs have hindered their widespread adoption. Since the mid 2000s, there has been extensive research and development toward making FPGAs accessible to software-inclined developers, besides hardware specialists. Many programming models and automated synthesis tools, such as high-level synthesis, have been proposed to tackle this grand challenge. In this survey, we describe the progression and future prospects of the ongoing journey in significantly improving the software programmability of FPGAs. We first provide a taxonomy of the essential techniques for building a high-performance FPGA accelerator, which requires customizations of the compute engines, memory hierarchy, and data representations. We then summarize a rich spectrum of work on programming abstractions and optimizing compilers that provide different trade-offs between performance and productivity. Finally, we highlight several additional challenges and opportunities that deserve extra attention by the community to bring FPGA-based computing to the masses.

中文翻译：

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软件定义 FPGA 加速的编程和综合：现状和未来展望

基于 FPGA 的加速器在广泛的应用中越来越受欢迎，因为它们提供了大规模的并行性、高能效和极大的定制灵活性。然而，编程和集成 FPGA 的困难阻碍了它们的广泛采用。自 2000 年代中期以来，除了硬件专家外，已经进行了广泛的研究和开发，以使倾向于软件的开发人员可以使用 FPGA。已经提出了许多编程模型和自动化综合工具，例如高级综合，以应对这一巨大挑战。在本次调查中，我们描述了在显着提高 FPGA 软件可编程性方面正在进行的旅程的进展和未来前景。我们首先对构建高性能 FPGA 加速器的基本技术进行分类，这需要对计算引擎、内存层次结构和数据表示进行自定义。然后，我们总结了关于编程抽象和优化编译器的丰富工作，这些工作在性能和生产力之间提供了不同的权衡。最后，我们强调了一些值得社区额外关注的额外挑战和机遇，以将基于 FPGA 的计算推向大众。