Toward High-Performance Network Coding: FPGA Acceleration With Bounded-Value Generators

The network coding enhances performance in network communications and distributed storage by increasing throughput and robustness while reducing latency. Batched sparse (BATS) codes are a class of capacity-achieving network codes, but their practical applications are hindered by their structure, computational intensity, and power demands of finite field (FF) operations. Most literature focuses on algorithmic-level techniques to improve the coding efficiency. Optimization with an algorithm/hardware co-designing approach has long been neglected. Leveraging the unique structure of BATS codes, we first present cyclic-shift BATS (CS-BATS), a hardware-friendly variant. Next, we propose a simple but effective bounded-value (BV) generator, to reduce the size of a finite field multiplier by up to 70%. Finally, we report on a scalable and resource-efficient field-programmable gate array (FPGA)-based network coding accelerator that achieves a throughput of 27 Gb/s, a speedup of more than 300 over software.