A study of FPGA-based cluster computing by high-speed serial-link communication
Ruochong FAN, Yoshiki Yamaguchi · 2020
With demand growing applications of Big Data and Machine Learning, an enormous amount of computational effort is required in those systems. High-performance computing systems like a data center adopts massively parallel computing that can bring them significant performance improvement. However, it faces making HPC systems based on the same acceleration approach more difficult to achieve further speedup since it generally troubled by its inter-node network due to its latency and insufficient bandwidth. It means this constrains the number of computing nodes in a system, namely system scalability. This article focuses on the flexible and extensible FPGA accelerator, which is widely used in the current supercomputers and data centers. The proposed approach is a communication framework by using an FPGA system with high-speed optical connections which connect among multiple FPGAs. The proposed concept is evaluated on a prototype cluster.