In recent years, the most powerful supercomputers have already reached megawatt power consumption levels, an important issue that challenges sustainability and shows the impossibility of maintaining this trend. To this date, the prevalent approach to supercomputing is dominated by CPUs and GPUs. Given their fixed architectures with generic instruction sets, they have been favored with lots of tools and mature workflows which led to mass adoption and further growth. However, reconfigurable hardware such as FPGAs has repeatedly proven that it offers substantial advantages over this supercomputing approach concerning performance and power consumption. In this survey, we review the most relevant works that advanced the field of heterogeneous supercomputing using FPGAs focusing on their architectural characteristics. Each work was divided into three main parts: network, hardware, and software tools. All implementations face challenges that involve all three parts. These dependencies result in compromises that designers must take into account. The advantages and limitations of each approach are discussed and compared in detail. The classification and study of the architectures illustrate the trade-offs of the solutions and help identify open problems and research lines.
