As the benefits of Moore's Law diminish, computing performance, and efficiency gains are increasingly achieved through specializing hardware to a domain of computation. However, this limits the hardware's generality and flexibility. Field-programmable gate arrays (FPGAs), microchips which can be reprogrammed to implement arbitrary digital circuits, enable the benefits of specialization while remaining flexible. A challenge to using FPGAs is the complex computer-aided design flow required to efficiently map a computation onto an FPGA. Traditionally, these design flows are closed-source and highly specialized to a particular vendor's devices. We propose an alternate data-driven approach, which uses highly adaptable and retargettable open-source tools to target both commercial and research FPGA architectures. While challenges remain, we believe this approach makes the development of novel and commercial FPGA architectures faster and more accessible. Furthermore, it provides a path forward for industry, academia, and the open-source community to collaborate and combine their resources to advance FPGA technology.

中文翻译：

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SymbiFlow 和 VPR：适用于商业和新型 FPGA 的开源设计流程


随着摩尔定律的优势逐渐减弱，计算性能和效率的提高越来越多地通过计算领域的专用硬件来实现。然而，这限制了硬件的通用性和灵活性。现场可编程门阵列 (FPGA) 是一种可以重新编程以实现任意数字电路的微芯片，可以在保持灵活性的同时实现专业化的优势。使用 FPGA 的一个挑战是高效地将计算映射到 FPGA 所需的复杂计算机辅助设计流程。传统上，这些设计流程是闭源的，并且针对特定供应商的设备高度专业化。我们提出了一种替代的数据驱动方法，该方法使用高度适应性和可重定向的开源工具来针对商业和研究 FPGA 架构。尽管挑战仍然存在，但我们相信这种方法可以使新颖的商业 FPGA 架构的开发更快、更容易。此外，它还为工业界、学术界和开源社区提供了一条合作和整合资源以推进 FPGA 技术的前进道路。